ADB TA 8287-INO: Scaling Up Renewable Energy Access in Eastern Indonesia Final Report

The Government of Indonesia & Asian Development Bank ADB TA 8287-INO: Scaling Up Renewable Energy Access in Eastern Indonesia

Final Report 31 December 2015

ADB TA 2 I calin p ene able ner Access in astern Indonesia Final Report 31 December 2015

repared for

repared b

The Government of Indonesia and Asian Development Bank T astlerock ons ltin

astlerock ons ltin Graha Iskandars ah th floor l Iskandars ah a a o akarta 121 0 Indonesia Tel 2 21 2 0 2 0 a 2 21 2 0 2 05 castlerockasia com ersion 1 0

Government of Indonesia and ADB

December 2015

FOREWORD This report has been prepared b astlerock ons ltin for the Government of Indonesia and the Asian Development Bank ADB nder ADB Technical Assistance TA o 2 I calin p ene able ner Access in astern Indonesia The report directl s pports the mba Iconic Island Initiative b presentin pre feasibilit st dies for selected ind biomass and off rid micro h dro opport nities These st dies dra on earlier reso rce st dies and least cost plannin anal sis The report also compiles presentation materials from the first inter ministerial electricit access orkshop cond cted in April 2015 as ell as from the mba Investor or m cond cted in December 2015 and doc mentation of ork prepared for the enter of cellence that is bein established b the inistr of ner and ineral eso rces re ardin a preliminar biomass reso rce assessment for Bali and ap a and eospatial data preparation on ener reso rces and electricit access ther principal deliverables prod ced nder this ADB TA assi nment incl de Inception eport ovember 2013 Deliverable B ner eso rces for Grid ppl & lectricit Demand Anal sis for mba eptember 201 id Term eport east ost lectrification lan for the Iconic Island December 201 Deliverable A Achievin niversal lectricit Access in Indonesia l 2015 to be p blished as an ADB no led e rod ct and Inp ts to the mba Iconic Island oad ap December 2015 Back ro nd and doc mentation on the mba Iconic Island Initiative incl din the above reports can be do nloaded from s mbaiconicisland or The astlerock team ratef ll ackno led es the leadership and s pport provided s arit e tapea Director of ario s ner and staff from thro ho t the Directorate General of e and ene able ner and ner onservation personnel from ila ah sa Ten ara Tim r especiall r liaman and Area mba ho provided idance on s stem plannin co nterparts in the inin & ner ervices and the e ional Development lannin A encies ithin the fo r kab paten of mba and Dr radeep Tharakan enior ner pecialist limate han e of the ADB ho ided preparation of the report

i Government of Indonesia and ADB

December 2015

TAB E OF

ONTENTS

Foreword

2

i

Introd ction 1 1 Back ro nd of the mba Iconic Island Initiative 1 2 vervie of ADB pport 1 3 r ani ation of this eport

- 1 1 1 3 1 5

Bio ass ower re-Feasibility St dy

2-

ind Far

icro- ydro Screening St dy

re-Feasibility St dy

- -

In estor For ic -o

or Electri ication

- or ing

ro p

7

Bio ass Assess ent or Bali and ap a

8

Inp ts to t e eospatial Decision S pport Syste enter o E cellence

- 7- o t e 8-

ii Government of Indonesia and ADB

December 2015

1.

INTRODUCTION BA rogra

ROUND OF T E SU BA I ONI

IS AND INITIATI E

Rationale

astern Indonesia is characteri ed b lo electrification ratios At the start of 2015 the electrification ratio for the province of sa Ten ara Tim r as onl 5 compared to a national avera e of 3 1 This poor access to electricit has profo nd conse ences on the socio economic development of the re ion lectricit is essential for prod ctive activities and the hi her standards of livin the brin ntil electricit s ppl becomes more idespread eastern Indonesia s economic and social development ill la the rest of the nation The traditional method of providin electricit s ppl to these comm nities diesel eneration is costl Tho h diesel costs have fallen sharpl over the past ear s avera e prod ction cost biaya pokok produksi B in TT for 2015 as p 3 2 1 k h compared to an avera e tariff ield of p 1 02 k h based on na dited estimates has previo sl embarked on a pro ram of small coal plant development and is c rrentl considerin a small scale G for eastern Indonesia o ever it remains to be seen hether the lo istical challen es of operatin small scale G and coal plants over a dispersed eo raphical re ion can be addressed ort natel tho h eastern Indonesia is blessed ith relativel hi h levels of insolation as ell as ind eothermal biomass and h dro reso rces oreover technolo ical advances and price red ctions for solar photovoltaic panels h brid s stem controllers stora e and end se technolo ies etc have provided ne options for electrification of remote comm nities A ainst this backdrop the D tch non overnmental or ani ation G ivos approached national and local overnment a encies ith a vision for the island of mba in the province of sa Ten ara Tim r ivos proposed mba as an iconic island to serve as an e ample of ho ener access can be scaled p thro h reliance on rene able ener so rces The principal ob ectives of the Iconic Island pro ram ere to achieve the follo in b 2025 5 electrification ratio and 100 of ener s ppl provided b ne and rene able reso rces These tar ets have since been pdated b Decree of the inister of ner and ineral eso rces o 3051 30 2015 on Desi nation of mba as an Iconic Island for ene able hich tar ets 5 of mba s ener s ppl to be from rene able so rces b 2020 In addition to providin the people of mba ith clean and s stainable niversal access the II initiative is intended to provide a model for rene able ener based access that can be replicated else here in Indonesia

Directorate General of lectricit Ketenagalistrikan 1

Book of lectricit

tatistics o 2

2015 Buku Statistik

11 Government of Indonesia and ADB

December 2015

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1. Introduction. . .. 2

istory and Instit tional Str ct re o t e Initiati e

Thro h the efforts of ivos the Iconic Island initiative as formall la nched at the end of 2010 at the Indonesia etherlands oint ner orkin Gro p The inistr of ner and ineral eso rces and ivos then or ani ed a series of stakeholder meetin s ith local and re ional overnments private sector and civil societ to en a e these stakeholders in the initiative and to link all e istin rene able ener pro ects nder a b these stakeholders e ho sehold solar panel pro rams b emda mba and In ebr ar 2011 a memorand m of nderstandin as si ned b the Governor of TT the B patis of the fo r mba kabupaten and ivos to ork to ether on the reali ation of the Iconic Island ob ective n the basis of this these local overnments and other stakeholders no ointl plan and coordinate their pro rams and pro ects took the lead in developin a comprehensive pro ram road map and desi ned a taskforce str ct re ivos has cond cted several st dies on the feasibilit of movin to 100 rene able ener s ppl to mba incl din st dies on off rid and rid electricit s ppl and biof el prod ction At a national seminar or ani ed b and ivos in ebr ar 2013 ass med f ll responsibilit for mba Iconic Island ob ectives and the implementation of the oad ap The initiative has evolved into a m lti stakeholder ndertakin led b the Directorate General of e and ene able ner and ner onservation ithin the inistr of ner and ineral eso rces in partnership ith ivos the provincial overnment of sa Ten ara Tim r the fo r districts of mba2 collectivel referred to henceforth as emda mba from Pemerintah Daerah Sumba) the tate lectricit ompan the Indonesian national tilit other overnment ministries and non overnment or ani ations the private sector and development partners incl din the Asian Development Bank the Government of or a A ence ran aise de D veloppement A D and Danida The illenni m hallen e Acco nt Indonesia is also f ndin activities that s pport the Iconic Island vision The pro ram and involvement of stakeholders is formali ed thro h a decree iss ed ann all b the Directorate General of e and ene able ner and ner onservation and more recentl b the inister of ner and ineral eso rces This decree desi nates the composition and roles of the members of the II task force The most recent decree has been iss ed as Decree of the inister of ner and ineral eso rces o 55 3 D 2015 dated 2 A st 2015 takeholders participate thro h three orkin ro ps i olic ii ppl and tili ation of ner and iii ndin and oordination The stakeholders meet t ice ever ear to plan and coordinate activities and revie pro ress d rin the previo s period Activities cond cted nder the initiative incl de capacit b ildin technical assistance investment plannin pro ect implementation and monitorin and eval ation rther information on the initiative incl din access to past reports and doc mentation on past and on oin pro ects ma be fo nd at s mbaiconicisland or

The fo r kabupaten are ast mba Sumba Timur entral mba Sumba Tengah est mba Sumba Barat and o th est mba Sumba Barat Daya The total land area of mba is sli htl over 11 000 km2 and the pop lation is appro imatel 00 000 The lar est to n is ain ap ith a pop lation of appro imatel 50 000 2


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1. Introduction. . .. 2

O ER IE

OF ADB SU

ORT

The Asian Development Bank e pressed its illin ness to s pport the II initiative and prepared a technical assistance TA pro ram to f rther develop the road map and bankable pro ects In a 2013 ADB or ani ed an Inception orkshop to kick off this TA At this orkshop the ADB also anno nced additional f ndin from the Government of or a to be channelled thro h the ADB TA pro ram for the Iconic Island The ADB TA ended on 31 December 2015 Activities cond cted d rin the 2 5 ears of the TA follo ed the tasks o tlined at the Inception orkshop hibit 1 1 identifies the reports iss ed over the co rse of the TA that cover the activit flo presented at the Inception orkshop These reports can be do nloaded from s mbaiconicisland or In addition a ebGI as created sho in c rrent ener reso rces and infrastr ct re on mba as ell as options for f t re development This ebGI can be accessed at http castlerockasia com s mba sii html

E

ibit

: Report

o erage o

ro ect Acti ities

START

Inception Report Task 1.1 Review past studies & legislation

Task 2.1 Set up GIS & other data Task 2.2 Assess demand & WTP

Task 1.2 Confirm objectives & governance

Task 1.3 Define critical success factors Task 1.4 Define service standards

Checkpoint: Kick‐off workshop

Task 2.5 Confirm PLN network plan Task 2.6 Assess grid vs. off grid supply

Mid‐Term Report Task 2.7 Determine least‐ cost grid mix

Task 2.8 Assess network feasibility

Task 2.9 Determine least‐ cost off‐grid supply

Task 2.10 Assess models & determine approach for Sumba

Checkpoint: Access Scale‐up Workshop

Task 3.2 Prepare Investment Prospectus

Checkpoint: Investment Prospectus Workshop

Task 2.3 Assess resources

Task 2.4 Procure monitors & analyze data (if necessary)

Deliverable B Phase 1: Consensus Phase 2: Analysis & Design Phase 3: Implementation

Final Report

Task 3.1 Conduct pre‐ feasbility stufies

Road Map Review Report

Task 3.2 Support tendering or development

Final Workshop: Lessons Learned

Deliverable A

rther details on the content of each deliverable prod ced over the life of the TA and the ali nment ith the TA tp ts defined in the Terms of eferences is sho n in hibit 12


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1. Introduction. . ..

E

ibit

TA O tp ts

2: Align ent o Deli erables wit t e Ter s o Re erence Deli erable

Deliverable B

1 reparation of a detailed electricit access plan for mba id Term eport

id Term eport

2 Identification and preliminar preparation of investment pro ects to be developed b &I s

3 Implementation of on oin and planned ener access pro rams financed b the overnment stren thened

II

oad evie

inal

ap

eport

Deliverable A incorporatin Deliverable D of the ori inal T

II oad evie

inal

ap

eport

ontents eso rce s rve s of vario s rene ables applicable for mba incl din ener demand anal sis and illin ness to pa reparation of T for i constr ction of a temporar river a in station & compilation of a flo d ration c rve ii a preliminar assessment of stora e h dro potential iii installation and operation of a met mast for ind data ac isition An electricit master plan and associated modellin for mba incl din i east cost electrification anal sis identification of rid vs off rid areas ii Grid load forecast based on above iii east cost eneration e pansion plan takin into acco nt the rid load forecast above as ell as the Deliverable B reso rce assessment iv Transmission load flo anal sis v Determination of II capital investment re irements reparation of a eb based Geo raphical Information stem eb GI to s pport plannin and the presentation of res lts for stakeholders Desi n of a mini rid pilot pro ram reparation and doc mentation of a spreadsheet model Recana Umum Perencanaan Energi Sumba to determine II investment needs b ear b technolo pro ect and b so rce of f nds nder vario s scenarios and implications for pdatin the II oad ap Identification and screenin of candidate off rid micro h dro sites leadin to preliminar field s rve of p to 20 s ch sites ind reso rce assessment & preliminar pro ect financial eval ation dra in on one ear of data provided b the ADB f nded met mast re feasibilit st d for rid connected biomass po er pro ects reparation and deliver of an Investor or m describin II investment needs and potential pro ects eport on the polic and financin environment for e pandin ener access in Indonesia and a incl din a revie of lobal best practices and implications for Indonesia evie and eval ation of the overnment s on oin ener access pro rams and ill strative b siness models for scalin p ener access thro h p blic p blic private and private sector led initiatives e o tp t based aid schemes concessions I schemes etc II onitorin & val ation & frame ork incl din the follo in doc mentation i eport on development of an & rame ork ii & o frame in n lish & Indonesian iii T for & activities in 201 ith reportin forms iv T for & activities in 2015 ith timeline v inal & presentation Assistance to the Government of Indonesia to formall establish an electrification orkin ro p to plan and implement the recommendations of Deliverable A Doc mentation of pport to enter of cellence GI preparation and biomass assessment of Bali and ap a


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1. Introduction. . .. OR ANI ATION OF T IS RE ORT This report presents the o tp ts listed in

hibit 1 2 for the inal

eport

pecificall

hapters 2 3 and present the res lts of a rid connected biomass po er plant pre feasibilit st d a pre feasibilit st d for a rid connected ind farm at ambaprain and a screenin st d for off rid microh dro electric plants respectivel These pro ects ere presented at an Investor or m cond cted on 15 December 2015 at the ermita e otel akarta The event as attended b more than 120 private investors state o ned enterprises and overnment co nterparts from both central and re ional overnments hapter 5 contains the presentations from the event hapter contains the presentations made at the first inter ministerial meetin held on 1 arch 2015 at the Do ble Tree otel akarta for national electrification scale p based on the findin s of the mba st d hapters and present the findin s of recent ork carried o t to s pport s enter of cellence partic larl the creation of a decision s pport s stem based on a eo raphical information s stem GI hapter presents a report on biomass reso rces in Bali and ap a and hapter presents the res lts of s pport for national electrification plannin


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2.

BIOMASS POWER PRE-FEASIBILITY STUDY


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PRE FEASIBILITY STUDY BIOMASS POWER PLANT IN SUMBA

Prepared for: Castlerock Consulting

Prepared by: Rohmadi Ridlo Oct 30, 2015

Page 7 of 396

Table of Contents EXECUTIVE SUMMARY .................................................................................................................................. 4 1. INTRODUCTION ..................................................................................................................................... 8 1.1.

Objective ....................................................................................................................................... 9

1.2.

Background .................................................................................................................................... 9

2. BIOMASS POWER PROJECT ................................................................................................................ 10 2.1.

Project Characteristics ................................................................................................................ 10

2.2.

Consistency with the government plan, RUPTL, and Electricity Supply and Demand ............. 11

2.3.

Expected project Impact and fuel sustainability ........................................................................ 12

3. PROJECT FUNDAMENTALS.................................................................................................................. 14 3.1. Type of biomass available in area considered (Sumba Tengah, Sumba Timur and Sumba Barat) 14 3.2.

Biomass production in Sumba Island ......................................................................................... 15

3.3.

Sumba Tengah, Sumba Timur and Sumba Barat ........................................................................ 19

4. SITE SELECTION ................................................................................................................................... 22 4.1

Site Selection for Energy Plantation ........................................................................................... 22

4.2

Project Site Of Biomass Power Plant .......................................................................................... 28

5. BIOMASS SUPPLY ................................................................................................................................ 29 5.1.

Estimation of Lamtoro Gung for power generation .................................................................. 29

5.2.

Potential wood production from proposed candidates of biomass energy plantation ........... 30

5.3.

Biomass supply chain .................................................................................................................. 31

5.4.

Projected biomass purchasing and cost ..................................................................................... 34

5.5.

Options for biomass fuel supply agreement .............................................................................. 36

5.6.

Biomass pre‐treatments /processing options ............................................................................ 37

5.7.

Supplementary biomass ............................................................................................................. 38

5.8.

Biomass risks mitigation ............................................................................................................. 38

6. TECHNOLOGY OPTIONS ...................................................................................................................... 41 6.1.

Biomass characteristics (Lamtoro Gung) .................................................................................... 41

6.2.

Combustion Technology ............................................................................................................. 42

6.3.

Gasification Technology .............................................................................................................. 46

6.4.

Cogeneration ............................................................................................................................... 50

6.5.

Pyrolysis ....................................................................................................................................... 51

6.6.

Selection of Power Generation Technology and options of technology provider ................... 52

6.7.

Gasification Plant Configuration ................................................................................................. 55

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6.8. Identified a potential local company or community which can operate and maintain the plant in the long‐term ............................................................................................................................ 57 7. FINANCIAL ANALYSIS .......................................................................................................................... 58 7.1

Required Funds ........................................................................................................................... 58

7.2

Financial Evaluation .................................................................................................................... 61

8. CONCLUSION ....................................................................................................................................... 64 8.1 Study findings and conclusion ........................................................................................................... 64 8.2. Pre‐Feasibility Study Discussion ....................................................................................................... 65 APPENDIXES I ................................................................................................. Error! Bookmark not defined. Emission Reduction from Biomass Power Project in Sumba Timur Regency (site 1) ............................. 66 Emission Reduction from Biomass Power Project in Sumba Tengah Regency ....................................... 81 APPENDIX II ................................................................................................................................................. 93 Financial Internal Rate of Return (FIRR) Calculation ............................................................................... 93 APPENDIX III Productivity of Leucaena Leucocephala ................................................................................ 95

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EXECUTIVE SUMMARY The pre FS was done on September 2014‐March 2015. The objectives of the pre FS is to make a first evaluation with respect to economically viable, sustainable and recommendable to build a biomass power plant in Sumba Island with biomass supplied from a plantation forest. The pre FS study included an assessment of: • Market considerations for the product and the biomass feedstock • The available supply of biomass feedstock • Organizational structure for development and operation of a biomass plant • Plant size, location, and technology to be used • Environmental and economic considerations • Projected financial outcomes Being designed as an Iconic Island for utilizing renewable energy for electricity generation, Sumba Island posesses several renewable energy resources potential such as hydro, biomass, wind and solar. The finding from site survey showed that the island has a total potential electricity generation from rice husk biomass of about 4 GWh/y. However, its availability has made it unattractive for power plant feedstock due to the seasonal variation and climate of the Island as well as constraint for rice husk collection. Moreover, rice Husk potential throughout Sumba Island is only about 0.5 MW and this will not supply electricity to PLN. Other residues from cassava, coconut, candle‐nut and corn‐cob are constrained by its availability and collection method, thereby they are not considered as potential fuel for electricity generation. The production of biomass in fast growing, short rotation tree plantations, is considered an option to meet the targets of the Sumba iconic island. To release the pressure on dependence on fossil fuel, the only way to increase biomass production on the long‐term is through the establishment of fast growing tree plantations. The study has revealed that the Island has a potential to generate electricity from biomass supplied from forest energy plantation of Leucaena Leucocephala (Lamtoro Gung) for totalling up to 889 GWh/y utilizing its wood chips from Sumba Timur regency, Sumba Tengah regency and Sumba Barat regency. The utilization of such biomass resource would contribute to the program of Sumba as the Iconic Island, where power generation shall be developed from renewable energy. Developing energy plantation in Sumba Tengah alone would supply enough electricity (10 MW) in Sumba Island through PLN grid (considering current demand in Sumba Island 10 MW peak load).

Page 10 of 396

Meanwhile, from estimation in this study Sumba Timur regency and Sumba Tengah regency could supply 90 MW and 7 MW electricity to PLN grid respectively. It is recommended to further consider gasification technology for power generation from Lamtoro Gung biomass utilizing gas engine for generating electricity from syngas. The study presents information on estimation of biomass fuel availability and costs, power generation capacity based on gasification technology. Table 1: Capital Cost Summary – Biomass Gasification for Grid Electricity Generation Basic Price in USD No

Plant Item/Description

Quantity Site 1

Detail Design & Engineering Charges Biomass Sizing & Conveying 2 System, Biomass Drying 3 Skip‐Charger Biomass Gasifier along with basic accessories and auxiliaries with 4 Dry Gas Filtration System Dry Gas Filtration System Flare system 1

5 Gasifier Cooling Tower 6

Condensate Neutralization System

7 52 TR Chiller 8

Producer Gas Engine & Other Related Accessories

9 Radiator for Engine Cooling

Sub Total 10 Packing & Transportation Charges Packing Charges @ 5% of order value FOB Basis (Containers for stuffing needs to be provided by client at their cost) Transportation cost (ocean freight, trucking to export harbour of Surabaya export documents, ISPM#15 certificate, certificate of origin, bill of loading, document courier fee. Add to each shipment

Lump Sum Lump Sum 2 Nos.

2 Sets.

Lump Sum Lump Sum Lump Sum 5 Nos. Lump Sum

111,607 15,000

Site 2

Site 3

Site 4

52,195

52,195

52,195

52,195

125,000

125,000

125,000

125,000

43,510

43,510

43,510

43,510

1,042,460

1,042,460 1,042,460 1,042,460

26,320

26,320

26,320

26,320

48,430

48,430

48,430

48,430

95,940

95,940

95,940

95,940

732,475 (5 x 146,495)

732,475 (5 x 146,495)

732,475 (5 x 146,495)

732,475 (5 x 146,495)

65,800

65,800

65,800

65,800

2,232,130 215,407 215,407

2,232,130 215,407

2,232,130

2,232,130

215,407

88,800

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a fumigation fee of $60 and insurance of 2.5% of shipping value, transportation Surabaya to location, Sumba) 12 Startup Power For The System Installation and Civil & foundation 13 work 14 Grid Interconnection 15 Building Total Contingency (4%) Total Plant Cost

40,000

40,000

40,000

40,000

166,667

166,667

166,667

166,667

450,000 360,000 150,000 1,500,000 100,000 100,000 100,000 100,000 4,254,204 3,204,204 3,114,204 2,904,204 170,168 128,168 124,568 116,168 4,424,372 3,332,372 3,238,772 3,020,372

Table 2. Results of pre‐feasibility study of the biomass project project. Site 1 Site 2 Site 3 Site 4 Peak Capacity (kW)‐gross 1200 1200 1200 1200 Peak Capacity (kW)‐net 1056 1056 1056 1056 Continuous duty‐gross (kW) 1020 1020 1020 1020 Continuous duty‐net (kW) 898 898 898 898 Gasifier Type Down Draft Down Draft Down Draft Down Draft Electricity to the grid (kWh) 8,363,520 8,363,520 8,363,520 8,363,520 Electricity produce (gross)‐kWh 9,504,000 9,504,000 9,504,000 9,504,000 Biomass consumption (t/y)‐ 20%MC 11,310 11,310 11,310 11,310 Biomass consumption (t/y)‐Dry Base 9,048 9,048 9,048 9,048 Biomass consumption (t/y) ‐ 40%MC 15,080 15,080 15,080 15,080 Parasitic load (kW) 144 144 144 144 Environment Baseline Diesel PP Diesel PP Diesel PP Diesel PP GHG reduction 2,480 2,755 2,761 2,767 (tCO2e/y) Energy 1,777,248 1,777,248 1,777,248 1,777,248 substitution effect (liter diesel oil/yr) Cost Initial performance investment 4,424,372 3,332,372 3,238,772 3,020,372 (US$) IRR (%) 9.33 14.73 15.35 16.94 Investment 14 11 11 10 payback period (Year) The financial summary shows that the project is financially feasible for a Biomass Gasification generating 1 MW electricity for grid to be built on one of the four identified potential project sites except Site 1, where the most important and sensitive factor is the electricity selling tariff that was

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assumed as US$14.2 cents/kWh (1840 rupiah/kWh) in the evaluation. Site 4 is the most favourable one in the financial sense as it has the shortest connection with the grid.The development will provide economic benefit to the local communities as well as people of the Sumba Island. The interest in converting biomass to electricity comes not only from its potential as a low‐cost, indigenous supply of power, but for its potential environmental and developmental benefits. For example, biomass may be a globally important mitigation option to reduce the rate of CO2 build‐up by sequestering carbon and by displacing fossil fuels. Renewably‐grown biomass contributes only a very small amount of carbon to the atmosphere. Locally, plantations can lessen soil erosion, provide a means to restore degraded lands, offset emissions and local impacts from fossil‐fired power generation (e.g., SO2 and NOx). In addition to the direct power and environmental benefits, biomass energy systems offer numerous other benefits. Some of these benefits include the employment of underutilized labour and the production of co‐ and by‐products (e.g., fuelwood). Issues Plantation establishment is a critical phase of a biomass energy project, since the timing of wood supply must be coordinated with the construction of a complex and expensive power plant. Mistakes or miscalculations at any one of many stages can result in expensive delays in power generation. Issues that must be addressed include: site preparation, seedling or cutting supply and quality, availability of required soil microorganisms, nursery operation, spacing of plantings, fertilization, watering, weed control, road construction, protection of nursery stock and plantings from insect pests, disease, animals, humans, fire, and other threats.

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1. INTRODUCTION Of different future alternative energy sources, biomass is a source that should be reckoned. Biomass is an organic matter sourced originally from plants, produced through photosynthesis, and is not converted into fossil (like coal). Biomass contains stored chemical energy to be converted into heat, electricity, and transportation fuel, or even as feedstock for biomass based products. One of many biomass benefits is that this energy source is renewable in characteristic. Biomass sources include woods, agricultural residues, dedicated crops, plantation wastes, and solid waste (such as municipal solid waste. Among advantages of the utilization of biomass as energy besides its renewable fuel source are helping to reduce fossil fuel dependency and reducing Greenhouse Gases emissions. The need to to replace fossil fuels with renewable biomass fuel (particularly fuel oil) in Indonesia is becoming important lately considering limited fossil fuel resources, increasing fossil fuel price, and especially on the country’s energy security concern and global warming issue. The government of Indonesia has commited to replace fossil fuel oil with renewable one, biofuel produced from biomass. This was mainly encouraged to reduce fossil fuel dependency, especially imported fuel. The development and utilization of biomass as energy source is in line with the implementation activity of the development program of Sumba Island as renewable energy Ico Based on identification carried out on this Island, biomass energy (from energy plantation) is one of proposed potential renewable energy sources to contribute to the program. By 2025, biomass energy is targeted to contribute to a capacity of 10 MW in electricity generation. In order to achieve this target, a secure and sustainable biomass supply of required feedstock must be developed and established. Bearing in mind to the low biomass potential from agricultural and plantation wastes in the Island, only biomass from energy plantation could provide enough biomass for energy generation to contribute to the fulfillment of energy demand in Sumba Island. The development of a plantation devoted to an energy generation would offer enough biomass and at the same time securing sufficient feedstock for supplying to biomass power generation in Sumba. One of steps of the utilization of biomass energy for electricity generation is performing a Pre‐Feasibility Study.

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This Pre‐feasibility study is prepared for the Government of Indonesia and the Asian Development Bank (ADB) under ADB Technical Assistance (TA) No. 8287‐INO: Scaling‐Up Renewable Energy Access in Eastern Indonesia in evaluating possibility and prospectus site for developing a biomass power plant in Sumba Island. The development of the plant will support the increase in electrification ratio and renewable electricity generation on the Island of Sumba. 1.1. Objective The key objective of this Pre‐feasibility study is to make a first evaluation with respect to economically viable, sustainable and recommendable to build a biomass power plant in Sumba Island with biomass supplied from a plantation forest. At the end of this preparation of this study, options for developing of such biomass power plant shall be presented as inputs to stakeholders in determining energy generation from renewable energy in this Island. 1.2. Background Sumba Island has been selected as an Iconic Island where renewable sources are to be developed and used for fulfilling energy demand in the Island, thereby substitutes fossil fuel dependency. Until 2014 the electrification ratio is only 30% in the Island where about 10.168 MW was mostly provided by diesel generators. Through the development, the share of renewable energy for electricity generation could gradually increase and finally substitute the use of fossil fuel. Among renewable sources existed in the Island, biomass from energy plantation is potentially developed for fuel as the source of biomass plant is easly found and grow in the Island, considering the climate of the area and its soil type. The option for energy plantation is considered desirable since the biomass used for power generation does not jeopardise local food security and provides benefits for local population, particularly to economic development. A continue supply of biomass for power plant is required for maintaining a continue electricity generation. This means that biomass supply security must be considered prior to developing a biomass power plant.

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2. BIOMASS POWER PROJECT 2.1. Project Characteristics Early study of Sumba Island has showed that this Island has relatively significant biomass potential from food crops residues. However, its availability is scattered in many areas making it impractical and inefficient (financially not feasible) for using as fuel. Other potential biomass sources for fuel from this area is biomass from forest plantation that is especially grown for being used for energy generation or commonly used term as “energy plantation”. Easy grown plant type with high productivity is required for an energy plantation development. Leucana Leucochephala (Lamtoro Gung) has been identified from the study (initial site survey) to grow in many areas in this Island which is covered majority with arid land. Therefore, this plant is selected and a recommended biomass type for an energy plantation. The plant has a productivity of 30 tons/ha/year and a typical calorific value of its wood of 4,597 kcal/kg. Competition use of biomass from Lamtoro Gung is for cooking fuel by local people. However, since the biomass for the power generation will be sourced from an energy plantation that is to be managed by a third party, such competition could be minimized. Moreover, it would reduce biomass price fluctuation as the biomass will be obtained from a pre‐determined agreement with the third party as the biomass producer. Other issue to be considered is the location of biomass source from biomass power plant project site. A reasonable distance of biomass source is required for an acceptable transport price and a feasible project. Biomass for energy generation has been widely developed around the world with capacity project range varies from lower than 100 kW to over 100 MW. A grid connected biomass power projects are generally above 5 MW, while off grid projects are typically 300 ‐ 400 kW.1 Hundreds of biomass gasification power plants have been installed in India in recent years, for both mini‐grid rural electrification and for supply to the main grid. Most are small, ranging from 100 kW to 1 MW, and use a wide variety of feedstocks, including agricultural waste, human and animal waste, and Juliflora, a common legume woody weed. Woody biomass has been developed for power generation for more than 100 MW using either combustion or gasification technologies. Capacity factors assumed to be in the range of 74.7% to 84.1% with an average adopted value of 80%. The selection for a grid or non‐grid connection depends basically on local electricity supply and demand. A biomass off‐grid project is financially feasible if its electricity generation cost is lower

1

http://siteresources.worldbank.org/INTRENENERGYTK/Resources/REToolkit_Technologies.pdf

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than existed fossil generation cost. Meanwhile, a grid‐connected biomass power plant will be financially feasible if it could get benefit from grid’s tariff. 2.2. Consistency with the government plan, RUPTL, and Electricity Supply and Demand A program for Sumba Island as an Iconic Island with renewable energy was initiated since 2010 by the Ministerial of Energy and Mineral Resources (MEMR) together with Bappenas (Badan Perencanaan Nasional/National Development Planning Agency) and HIVOS (Humanistisch Instituut voor Ontwikkelingssamenwerking)2. The selection of the Island as the iconic one was based on an early assessment conducted by HIVOS which indicated that the Island had abundant new and renewable energy potential. The goal of the program is to achieve 100% renewable energy development and 95% electrification ratio in Sumba Island by 2025. Local government regulation of Sumba Timur Regency No 12 of 20103 on the Spatial Planning of Sumba Timur Regecy year 2008‐2028 contains spatial planning structure of Sumba Timur regency which includes the development of energy sources and transmissions systems. Moreover, the development plan of energy network system according to this regulation has included the development of new and renewable energy by the regency government which comprises such as PLTMH, PLTU, PLTA, PLTM, PLTB, PLTS or even hybrid systems in accordance with local available renewable energy resources. This regulation has also set about spatial planning strategy on increasing capacity and electricity service through development of renewable energy (PLTA and PLTM), performing assessment and development of interconnection systems of inter‐regional (regencies) in Sumba Island.[page 18] Through the Local Government Regulation of Sumba Tengah No. 1 of 2011 regarding the Spatial Planning of Sumba Tengah Regency year 2009‐20294, the government has set the policy and development strategy of Spatial Planning of Sumba Tengah Regency. The development strategy on infrastructure network system includes among other optimizing energy/electricity infrastructure service level and extension of electricity transmission up to remote villages by conducting assessment and developing electricity hybrid system. Other strategy is by increasing electricity capacity and service through an interconnection system with other regencies in Sumba Island.

2

International Humanist Institute for Cooperation with Developing Countries www.jdih.setjen.kemendagri.go.id/.../KAB_SUMBA%20TIMUR_12_2010 4 http://kupang.bpk.go.id/wp‐content/uploads/2010/09/OKE.‐PERDA‐NO‐1‐TAHUN‐2011.pdf 3

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Under this strategy, development of renewable energy, particularly PLTMH, has been put into consideration to utilize local water energy potential. Although the development of biomass as one of renewable energy source has not been specifically mentioned in both local government regulations, the development of biomass power plant included in the Iconic Island program would certainly in consistence with the development of renewable energy of Sumba Timur and Sumba Tengah governments. Meanwhile, PT PLN (persero) has intended to realize Sumba Island in Nusa Tenggara Timur as the only region in Indonesia which is diesel oil free for generating electricity in 2015. The company shall use potential natural resources such as water, solar, wind and biomassa. According to MEMR, the government has been continuing to develop distributed electricity generation in 2014 like distributed solar power plants, wind power plant, hydro power plants, 1 MW biomass power plant in Sumba Barat Daya and distributed Biogas.5 Current electricity demand in Sumba is majority supplied from renewable energy (55%). The peak load from the Island is approximately 10.3 MW. Renewable power plants supplying the electricity in the Island are PLTMH Lokomboro 2,3 MW, PLTMH Laputi 32 kW, PLTS Bilachenge 480 kWp, PLTMH Kamanggih 40 kW and PLTMH Lapopu 1,6 MW totalling to 4,452 MW.6 Biomass power plant development of 1 MW capacity in Sumba has been put in RUPTL 2013‐2022, with expected commercial operation date in 2018. The operation of this plant will contribute to the achievement program of Sumba as Iconic Island. 2.3. Expected project Impact and fuel sustainability In an effort to help stakeholders in the decision‐making process, this section (sub‐section) explores the advantages and disadvantages of producing and utilizing woody biomass as feedstock for power generation. The followings are expected positive impacts and possibly negative impacts on local community, economy and environment:

5

http://maxfmwaingapu.com/2014/03/sumba‐ikon‐energi‐terbarukan‐pembangunan‐pembangkit‐energi‐terbarukan‐ terus‐digenjot/ 6 http://www.geoenergi.co/read/solar/1306/55‐listrik‐pulau‐sumba‐dari‐energi‐baru‐dan‐terbarukan/#.VCq1T8WJSSo

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‐

Providing electricity generation from renewable energy would improve local economy and community wealth. Local community would benefit from increasing the reliability or availability of electricity.

‐

Biomass utilization would create and retent local jobs in rural economies It is estimated that direct employment for a biomass power plant is five to six person per MW installed capacity. 7 , 8 Meanwhile, fuel processing (biomass pre‐treatment) would provide employment of roughly about 18 people (cutting/felling, skidding, and chipping, vehicle driver).9

‐

Biomass power development would attract investments towards rural areas, generating new business opportunities for small‐and medium‐sized enterprises in biomass production, preparation, transportation, thereby generating income

‐

Mitigation of carbon in electricity generation due to avoidance use of fossil fuel. Moreover, biomass contains minimal sulphur, thereby avoiding SO2 emissions which could cause acid rain.

‐

Introducing biomass for energy plantation would help avoiding of land degradation such as erosion and becoming desert (desertification)

Negative impacts to anticipate: ‐

Increase of vehicle traffic which could cause noise, dust and air pollution for local community

‐

Local air pollution due to biomass power plant (exhaust gas/stack)

‐

Local water use and influence to water resource which could compete with local community use

‐

Ash (waste removal)

7

http://www.reenergyholdings.com/reenergy‐to‐resume‐operations‐at‐biomass‐to‐energy‐facility‐in‐ashland‐me/ http://www.pacificbiomass.org/documents/Oregon3EasternCountiesBiomassAssessment.pdf 9 To estimate fuel procurement employment, we assumed that a six‐person crew could produce approximately six full chip vans per day. This includes felling, skidding, chipping and three daily round trips per driver. Assuming a chip van will hold 23 GT of biomass, a 5‐MW power plant that consumes 123,415 GT/year of fuel would need three crews operating to provide its fuel. Therefore, a 5‐MW plant would employ 18 people in the fuel procurement sector 8

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3. PROJECT FUNDAMENTALS 3.1. Type of biomass available in area considered (Sumba Tengah, Sumba Timur and Sumba Barat) Once a site is chosen, the next key to the success of the energy plantation is the selection of genetically superior tree species, varieties or clones suitable for the climate, soils, and desired products of the energy plantation plantation. Most species achieve their best growth under a fairly narrow range of climate and soil conditions, and failure to match species to site has been the cause of the failure of many plantation projects. Even within a species that is suited to a particular site, there can be great variation in the growth and wood characteristics from different seed sources or regions within the species range. The largest, cheapest, and fastest gains in most tree improvement programs can be made by assuring the use of the proper species and seed sources within species. Key to producing low‐cost biomass is the land base and the quality of sites, which determine to a significant extent the degree of site preparation necessary; the choice of species, spacings and cutting cycles; required cultural management and soil amendments (fertilization, weed control, animal control, and pest management); and fuel transport and logistics. The analysis in the preceding report prepared by Castlerock Consulting for the Government of Indonesia and the Asian Development Bank (ADB) under ADB Technical Assistance (TA) No. 8287‐ INO: Scaling‐Up Renewable Energy Access in Eastern Indonesia study indicates that power generation from forest energy plantation with Lamtoro Gung wood appears promising for Sumba Island above agricultural wastes (rice husk, maize, cobs, coconut shells, candle nut shells and bagasse). Its woody character has several advantages over agricultural wastes particularly in harvesting and storage. Such wastes would generally require short time frame for harvesting and pre‐treatment before storage could be done for providing year‐round biomass supply. Lamtoro Gung (leucaena leucocephala/Horse tamarind or leed tree) is a type of shrub plant from the fabaceae. It is a tropical species which grows well in areas with annual rainfall ranging of 650 – 3000 mm and best in warm temperatures areas (25‐30°C day temperatures) and at altitude of below 500 m. This species tolerates to dry climates (300 mm) and to long drought periods of up to 6‐7 months.10

10

http://www.feedipedia.org/node/282

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The average productivity of the plant can reach as high as 36 tons/ha/year, although 15 to 30 tons/ha/year is more typical. 11 Appendix III summarizes several sources on Lamtoro Gung productivity. The first harvest of the plant occurs after 12 to 18 months of transplanting. The wood is obtained from an energy plantation, so the percentage of the wood availability is therefore assumed to be approximately 70% of the theoretical potential. This wood is relatively dense for a quick growing plant (various sources cite density of 500‐640 kg/m3) and the water content of wet wood is between 30 to 50%, depending on its age. Lamtoro Gung wood is estimated to have a calorific value of 19,250 kJ/kg (equivalent to 4,597 kcal/kg). In the combustion process, energy content, moisture content and chemical composition are the most important biomass characteristics affecting combustion processes. This plant is preferred for wood fuel, and would be the primary candidate for any biomass fuel plantation in Sumba. The species does best on calcareous soils12, such as those found on Sumba Island. 3.2. Biomass production in Sumba Island A grid‐connected Lamtoro Gung wood fuelled power plant design would need to consider wood sources, wood availability, location of power plant, and technical characteristics of the plant utilizing adopted biomass as fuel. Lamtoro Gung is already grown as a plantation forest species in Indonesia , as it was in Sikka, Nusa Tenggara Timur province. Thus the knowledge base for establishing plantations in Indonesia is readily available in addition to the promising results of previous studies on the island.13

11

Lamtoro Gung typically yields 20 to 60 m3/ha/yr (~12 to 36 t/ha/yr assuming 0.6 t/m3); see for example http://www.tropicalforages.info/key/Forages/Media/Html/Leucaena_leucocephala.htm, http://www.worldagroforestrycentre.org/treedb2/AFTPDFS/Leucaena_leucocephala.pdf, http://www.fs.fed.us/global/iitf/pubs/gtr_so088_1992.pdf, http://www.tropicalgrasslands.asn.au/Tropical%20Grasslands%20Journal%20archive/PDFs/Vol_23 _1989/Vol_23_01_89_pp28_34.pdf, http://www.worldagroforestry.org/units/library/books/PDFs/07_Agroforestry_a_decade_of_develop ment.pdf#page=298, http://www.fao.org/ag/agp/AGPC/doc/gbase/data/pf000158.htm. Other sources indicate productivity of about 30 t/ha/yr, e.g. http://wgbis.ces.iisc.ernet.in/energy/HC270799/RWEDP/acrobat/fd45.pdf. http://www.chemlin.de/publications/documents/leucaena.pdf : (Leucaena is a fodder legume. Yields up to 30‐40 m3/ha/year. It shows yield 40‐50 m3 of wood/hectare. Needs rainfall 1,100 – 1,200 mm. It needs minimum 600‐700 mm rainfall. It grows best in rainfall 1,000‐3,000 mm. Leucaena grows well in alkaline soil. It grows well in soil having pH 6.0‐7.7. 12 http://www.timoragri.fhost.com.au/ta100/ta117.pdf: calcareous, with a soil pH between 8 and 9, with some soils being sodic 13 http://www.timoragri.fhost.com.au/ta100/ta117.pdf

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Sumba Island has a climate semi‐arid climate. This information has been obtained from a report provided by the Indonesian Central Bureau. Sumba Timur regency Sumba Timur regency has typically a semi‐arid climate. The average temperature in this regency in 2012 reached 27.2°C, with the lowest 24.9°C in August and the highest 29.5°C in November. The highest average precipitation was in March, while from June through October there was no rainfall at all.14 Nothern part had the lowest range of precipitation (800‐1,000 mm p.a), while the eastern part and western part of the middle area of Sumba Timur regency had an average precipitation of 1,000‐1,500 mm p.a and 1,500‐2,000 mm p.a. in the western part of the regency.15 The regency has a total area of 700,050 ha of which 44% (307,700 ha) has a slope of 0‐8%. Sumba Tengah regency This regency is also known to have a semi arid climate. Dry season occurs from the month June through September, while rainy season occurs normally from December through March. Transition periods occur in months April‐May and October‐November. Thus, 8 months in a year is relatively dry in this regency.16 An analysis based on a 30 years climate data series (1983‐2012) on temperature and rainfall showed that the mean monthly temperature in Nusa Tenggara Timur and the monthly rainfall tend to increase in the range of 0.2°C – 0.4°C and 25‐10 mm respectively.17 In addition, rainy season tends to shift later (1 – 3 months) than the normal case and occurs in a shorter period. Umbu Ratu Nggay Sub‐district is located at an altitude of about 500 m asl.18

Sumba Barat Like other regencies in Sumba Island, Sumba Barat Regency has also two seasons, rainy season (from December to March) and dry season (June to September, with the transition period on April‐May and October‐November). The rest of 8 months is dry. 14 15

http://sumbatimurkab.bps.go.id/index.php?hal=tabel&id=10 http://www.sumbatimurkab.go.id/iklim.html

16

http://ntt.litbang.pertanian.go.id/phocadownload/Kab_Dalam%20Angka%202009/Kabupaten%20Sumba%20Tengah%20D alam%20Angka%202009.pdf 17 http://bkpm‐nttprov.web.id/data‐wilayah/profil‐provinsi‐nusa‐tenggara‐timur/ 18 http://geospasial.bnpb.go.id/wp‐content/uploads/2010/09/indeks_peta/250K/ID‐Q14‐250K.pdf

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19

Altitude of Sumba Barat Regency by District 201220 District Altitude (m) Lamboya 0‐700 Wanokaka 0‐450 Laboya Barat 0‐700 Loli 200‐600 Kota Waikabubak 200‐600 Tana Righu 0‐550 From the climate characteristic in all regencies described above, it was concluded that Lamtoro Gung could basically grow throughout the Island. The plant was found to grow in these area, as observed from the site survey. Lamtoro Gung growing in Sumba is currently used for fuel or fodder by local community. In order to secure a supply of the wood, Lamtoro Gung plantation should be considered rather than collecting it from local areas that grow wildly or are owned by farmers. Based on the site survey and discussions with the local government of Sumba (Pemda) and Forestry Service, Sumba Tengah, Sumba timur, and Sumba Barat were found to be potential areas for Lamtoro Gung energy plantation. It was confirmed that there are available land areas in Sumba Timur, Sumba Tengah and Sumba Barat regencies for energy plantation. Two locations were identified in Sumba Timur 36,000 ha and 19,200 ha, one location in Sumba Tengah (6,350 ha), and one location in Sumba Barat (5,000 ha). The locations are shown in the map below, with description of the locations.

19

http://www.setyanovanto.info/sumba‐barat?page=polling&lang=id: Jika dilihat dari ketinggian, wilayah Kabupaten Sumba Barat diklasifikasikan kedalam 4 daerah ketinggian dengan rincian : ketinggian dari 0‐25 m meliputi 4,24% luas wilayah, dari 25‐100m meliputi 21,46% luas wilayah, dari 100‐500 m meliputi 61,31% luas wilayah, dan ketinggian di atas 500 m meliputi 12,99% luas wilayah. Dari aspek klimatologi, Kabupaten Sumba Barat dipengaruhi oleh iklim muson dengan rata‐rata musim hujan dari 1.000‐2500 mm, dengan jumlah hari hujan dari 100 hingga 150 hari. Curah hujan ini sudah dipengaruhi oleh kondisi hidrologi di Kabupaten Sumba Barat. 20 http://sumbabaratkab.bps.go.id/index.php/keadaan‐geografi/21‐tinggi‐rata‐rata‐wilayah‐kabupaten‐sumba‐barat‐ menurut‐kecamatan‐tahun‐2012

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INDONESIA

Sumba Island

3 2 4

1

Location

Desa

Kecamatan

Kabupaten

Forest

Savannah

Farmland/ Plantation

Sumba Timur (Candidate 1) Sumba Timur (Candidate 2)

Meu Rumba

Kahaungu Eti

Sumba Timur 37%

60%

3%

Rakawatu

Lewa

Sumba Timur 9%

90%

1%

Sumba Tengah (Candidate 3)

Soru

Umbu Ratu Nggay

Sumba Tengah

8%

90%

2%

Sumba Barat (Candidate 4)

Bodo Hula Lamboya Dete

Lamboya

Sumba Barat

35%

60%

5%

Figure 3.1. Location and description of candidates for forest energy plantations in Sumba

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3.3. Sumba Tengah, Sumba Timur and Sumba Barat 3.3.1. Electricity supply and demand PLN’s Rencana Usaha PenyediaanTenaga Listrik (RUPTL) or Power Supply Business Plan for the period 2015 to 2024 states that in 2012, combined peak load on PLN’s isolated systems on Sumba amounted to 0.9 MW, while peak load on the Waikabubak system was 5.1 MW and on the Waingapu system 5.2 MW. The Waikabubak system is supplied by generation mix consisting of diesel, hydro, and solar power plants with a total installed capacity of 9.6 MW.21 PLN has planned to increase an effective capacity from 16.0 to 21.7 MW over the period of 2014 – 2020, as stated in RUPTL 2015‐2024. According to this RUPTL, there would remain some 6.7 MW diesel capacity in operation, 3.0 MW of biomass capacity, 0.5 MW of hybrid, and the remaining 11.5 MW as small hydro. Until 2014 (October), there has been no biomass power plant developed in the Island as earlier planned in RUPTL 2012‐2021.

Current (2013/2014) peak demand in Sumba Island is reported to be 10.3 MW. Ready to develop renewable energy in Sumba Island includes hydro potential 12.4 MW, biomass power plant and wind potential. The development of 1 MW biomass power plant in Waingapu seems to be changed to a later time in RUPTL 2012‐2023, which states that the plant is allocated to be commercial by 2016. However, this development is likely to experience barrier so that it could not be realized as expected. Existing transmission line in Sumba Island is system Waingapu, system Waikabubak‐Waitabula, and system isolated supplied by a 20 kV feeder from 19.1 MW of generation mix power plant.

21

RUPTL 2015‐2024

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PLN’s existing 20 kV network

PLN’s planned 20 kV network Figure 3.2. PLN’s existing and planned 20 kV network for Sumba PLN has started a program for the interconnection of the East and West systems via connection through the northern and central routes. For development of a biomass power plant, it must be made clear on sub‐station to which electricity generated from biomass power plant is supplied / exported.

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3.3.2. Market options Biomass power plant to be developed could provide electricity to local community or be sent to PLN’s grid when local demand is already fulfilled. Market options for by‐products Excess Heat: Any excess heat from the power plant could be utilized for biomass drying during pre‐ processing. Hot air generated in gas cooler during cooling of gas can be used for drying of biomass. Fly Ash Ash generated from biomass power plant could be used for fertilizer. However, this would need further consideration to determine its potential market. The ash and waste products from burning or gasification will, in most cases, be sufficiently benign to return to the soil.

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4. SITE SELECTION 4.1 Site Selection for Energy Plantation Site selection must consider and balance a wide range of biological, economic, and societal factors. The biomass decision tree shown in Fig. 4.1 summarizes the information required and decisions that need to be made to determine whether a biomass plantation may be feasible. Site selection and planning at the national, regional, and local level requires geographically located information on soil and geology, natural vegetation, current land uses, topography, watershed boundaries, stream/river systems, roads, local political jurisdictions, land ownership and tenure information, location of cultural and historical resources, location of nature preserves and rare habitats and species. It is also very valuable to have site‐specific research data on the yields that can be expected from the preferred species. Based on the discussion with local governments (Pemda) during the site survey in 2013‐2014 in Sumba Island as reported in ADB Technical Assistance (TA) No. 8287‐INO: Scaling‐Up Renewable Energy Access in Eastern Indonesia ‐ Deliverable B: Energy Resources for Grid Supply & Electricity Demand Analysis for Sumba 3 regions were identified to have potential for the development of energy plantation; Sumba Timur Regency, Sumba Tengah regency and Sumba Barat regency. The sites for energy plantation in these regions are owned by local governments. The sites were suggested by forestry service of Sumba Timur and Sumba Tengah and considered as potential and appropriate sites for Lamtoro Gung plantation as this sites are mainly savannah areas (>60% of proposed sites area). The plantation program could help improve soil properties. Table 4.1. Proposed sites for Lamtoro Gung energy plantation in Sumba Island Regency/ Candidate site Sumba Timur (Candidate 1) Sumba Timur (Candidate 2) Sumba Tengah (Candidate 3) Sumba barat (Candidate 4)

Village

Sub‐district

Forest

Savannah


Potential area (ha)

Meu Rimba

Kahaungu Eti

37% (Protection forest)

60%

3%

36,695

Rakawatu

Lewa

9% (Production forest)

90%

1%

19,748

Soru

Umbu Ratu Nggay

8% (Production forest)

90%

2%

6,350

Bodohula Lamboya Dete

35%

60%

5%

Lamboya

4,720

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Figure 4.1. Biomass project decision tree

Figure 4.2. Map indicating candidate locations for Lamtoro Gung energy plantation Candidate site 1: Sumba Timur regency An area of 36,000 ha suggested for the energy plantation is located in Meu Rimba Village, Kahaungu Eti Sub‐district. Only small part of the area is a farm area (3%), about 37% protection forest. Lamtoro

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Gung is expected to grow well considering the climate of this area where reasonable precipitation is available for growing this kind of plant and is located between 200‐500 m asl.22 Table 4.2. Number of rainfall and number of rainy days by Months in Kahaungu Eti Sub‐district (2010) Month 2010 2012 Rainy Days Rainfall (mm) Rainy Days Rainfall (mm) (days) (days) January 13 220 No data No data February 7 130 No data No data March 13 220 No data No data April ‐ ‐ No data No data May ‐ ‐ No data No data June ‐ ‐ No data No data July ‐ ‐ No data No data August ‐ ‐ No data No data September ‐ ‐ No data No data October ‐ ‐ No data No data November ‐ ‐ No data No data December ‐ No data No data Total 33 570 No data No data Source: Kahaungu Eti in Figures 2013‐BPS Sumba Timur Candidate site 2: Sumba Timur regency The proposed site is located in Rakawatu Village, Lewa Sub‐district totalling an area of 19,000 ha. Most of this is savannah area (90%) though about 1% is a farm area and the remaining is production forest. The climate of this area would still be suitable for Lamtoro Gung energy plantation as it is located in northern part of Sumba Timur having generally a range annual precipitation of 800‐1000 mm and an altitude of less than 500 m asl.23

22

http://geospasial.bnpb.go.id/wp‐content/uploads/2010/09/indeks_peta/250K/ID‐Q14‐250K.pdf http://geospasial.bnpb.go.id/wp‐content/uploads/2010/09/indeks_peta/250K/ID‐Q14‐250K.pdf (altitude 500 m asl) 23

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Table 4.3. Number of rainfall and number of rainy days by Months in Lewa Sub‐district (2011 and 2012) Month 2011 2012 Rainy Days Rainfall (mm) Rainy Days Rainfall (mm) (days) (days) January ‐ ‐ 18 2727 February 11 1825 ‐ ‐ March 15 3456 ‐ ‐ April ‐ ‐ 6 990 May ‐ ‐ ‐ ‐ June ‐ ‐ ‐ ‐ July ‐ ‐ ‐ ‐ August ‐ ‐ ‐ ‐ September ‐ ‐ ‐ ‐ October 2 221 ‐ ‐ November ‐ ‐ ‐ ‐ December 15 No data ‐ ‐ Total 43 5502 24 3717 Source: Lewa in Figures 2013‐BPS Sumba Timur, Dinas Pertanian Tanaman Pangan dan Hortikultura, Kabupaten Sumba Timur Candidate site 3: Sumba Tengah regency The 3rd site proposed for the energy plantation is in Soru village, Umbu Ratu Nggay Sub‐district. As in other proposed sites, Lamtoro Gung is expected to grow well in this area where dry season could reach up to 8 months. Out of 6,350 ha, majority of the proposed area at this site is savannah (90%) while farm land constitutes of only 2%. The proposed site also covers protection forest which could be used for energy plantation. The sites is located at altitude of approximately 500 m asl. No data of number of rainfall and number of rainy days in Umbu ratu Nggay Sub‐district (also in Sumba Tengah regency), because instrument is not yet available. Sumba Tengah Regency has only two seasons, dry season and rainy season. On June to September the wind flow which contains little moisture, caused the dry season. On the contrary, on December to March the wind flow contains a great deal of moisture, caused the rainy season. This condition changes and turn for a half of year, after passing, the transitional period on April‐May and October‐November. Nevertheless, since Sumba Tengah as not so far from Australia, the great deal of moisture of wind flow comes from Asia and Pasific Ocean, has reduce after reaching Sumba Tengah area. And it makes Sumba Tengah has the dry area which is relatively wet in 4 months (January until April and December) and the rest of 8 months is dry.

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Candidate site 4 : Sumba Barat regency The site covers an area of 4,720 ha and is in Lamboya Sub‐district. This area is under the management of a private company, PT Usaha Tani Lestari. Plantation of Lamtoro Gung in this area is expected to result good quantity of wood for developing a biomass power plant in this Island. As noted in the table above, potential areas for the plantations are located in protected forest and production forest. However, the Indonesian forestry laws and regulations allow the use of Protected Forests (Hutan Lindung) and Production Forests (Hutan Produksi) for uses like forest energy plantations. Nature Reserves (Cagar Alam) and Core Zones of National Parks (Zona inti Taman Nasional) are the ones that are prohibited for any utilization.24,25 The process of using Protected and Production forests for these purposes is through application to the Ministry of Forestry. An area of 500 ha of Candidate 1 was converted to community forest based on Decision of the Ministry of Forestry (Surat Kuasa) 110/Menhut‐II/2009. An additional conversion of 2,754 ha from the protected forest at this Candidate location to community forest is being proposed by the Forestry Office of Sumba Timur to the Ministry of Forestry. Candidate 4 is managed by PT Usaha Tani Lestari which has obtained business License on Industrial Forest Plantation (hutan tanaman industri /HTI) from The Ministry of Forestry based on SK.216/Menhut‐11/2013, 25 March 2013 for an area of 41,515 ha consisting of 4,720 ha in Sumba Island (Sumba Barat Regency) and of 36,795 Ha in Flores Island (Kupang Regency). The purpose of the HTI is to plant/grow woody plant for wood work, energy and to provide incentive from GHGs emissions reduction based on REDD program (Reducing Emissions from Deforestation and Forest Degradation). An area of 4,720 is planned for planting of plant types such as eucalyptus, turi, gamal, lamtoro (short term plant), and also jati (long term plant). Law 41/1999 on Forestry contains the following provisions. Minister of Forestry Regulation P.38/Menhut‐II/2012

24

provides further details: Article 24: Forest area utilization can be made to all forest areas except natural conservation forest as well as core zone and forest zone in national park. Article 26: (1) Utilization of protected forest in form of area utilization, environmental service utilization and collection of non‐timber forest produce. Article 38: (1) Use of forest area use in the interest of development beyond forestry activities can only be made in production forest area and protected forest area 25 Protected Forests and Production Forests can be used for industrial or commercial timber plantations, community forest plantations or ecosystem services and non‐forestry activities such as renewable energy, right‐of‐way for electricity grid lines, etc.

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Table 4.4. Number of rainfall and number of rainy days by Months in Lamboya Sub‐district (2012 and 2013) Month 2012 2013 Rainy Days Rainfall (mm) Rainy Days Rainfall (mm) (days) (days) January 23 494 20 422 February 14 367 19 301 March 18 833 16 165 April 11 193 7 246 May 8 91 10 116 June ‐ ‐ 6 108 July 5 19 3 30 August ‐ ‐ ‐ ‐ September 2 1 3 89 October 7 62 4 152 November 10 63 15 151 December 24 278 12 656 Total 122 2401 124 2436 Source: Lamboya in Figures 2013 and Sumba Barat in Figures 2014‐BPS Sumba Barat

PT Usaha Tani Lestari as the IUPHHK (Permit for Timber Forest Product Utilization) holder must arrange Timber Forest Product Utilization Plan (RKUPHHK /Rencana Karya Usaha Pemanfaatan Hasil Hutan Kayu). RKUPHHK is prepared as a working plan for all working area of IUPHHK for a period of 10 years, which must consider long term management plan KPH and should include among other forest sustainability aspect, business sustainability, environmental balance and social economy development of local community.26 Current status of the program in accordance with license stages is development of RKU‐UPHHK (Rencana Karya Sepuluh Tahunan‐ Usaha Pemanfaatan Hasil Hutan kayu) which expired on July 2014, and next is to prepare Annual Plan ‐ Timber Forest Product Utilization (RKT‐UPHHK /Rencana Karya Tahunan) and planting is targeted in January 2015. In area of 4,720 ha in Sub‐district Lamboya was later included as one of candidate sites for energy plantation in this report.

26

Based on Minute of Meeting with PT Usaha Tani Lestari: PT Usaha Tani Lestari as the IUPHHK holder must arrange Timber Forest Product Utilization Plan (RKUPHHK /Rencana Karya Usaha Pemanfaatan Hasil Hutan Kayu) one year at the latest after receiving Timber Forest Product Utilization License (IUPHHK /Izin Usaha Pemanfaatan Hasil Hutan Kayu).

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4.2 Project Site Of Biomass Power Plant The purpose of the proposed project is to generate electricity using biomass as fuel. Project site selection is vital in order to make capital investment as effective as possible and to obtain maximum results. Following are major criteria for region suitability for electrification using the biomass power system: a. Strong Government priorities for regional and community development b. Strong support of local Government, PT PLN for the project c. Local transmission line infrastructure (location relative to the existing grid) d. Adequate land and suitable sites for power system The candidate sites for energy plantation for supporting biomass power plant are given in section 4. An on‐site survey was conducted based on the above criteria in conjunction with officials from relevant local government, as a result of which four candidate sites were chosen. Table 4.5. Candidate site of biomass power plant Candidate site of biomass Power plant size Geographical coordinates power plant (MW) gross Kapohakpenang (Candidate 1) 1.2 Sumba Timur:S 09056.039’ E 120024.383’ Rakawatu (Candidate 2) 1.2 Sumba Timur: S 09035.348’ E 119055.839 Pahedutilli (Candidate 3) 1.2 Sumba Tengah:S 09032.563’ E 119050.393 Lamboya (Candidate 4) 1.2 Sumba Barat: S 09°56.260’ E120°23.473’

Distance to PLN grid (km) 50 15 12 5

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5. BIOMASS SUPPLY 5.1. Estimation of Lamtoro Gung for power generation The amount of Lamtoro Gung wood generated annually was calculated based on the estimated annual average area harvested and assumed yield values of the plantation as noted previously and as described in Appendix A (30 tons/ha/year). Technical availability (accessibility to biomass resource to use it as feedstock for energy generation) was assumed to be 70%. Table 5.1 Presents estimation on quantity of Lamtoro Gung wood and land required for electricity generation from 1 MW up to 10 MW. Table 5.1.Estimated Land Required for Electricity Generation Capacity of 1 MW No

Remarks

Amount required

1

Wood Chip required from Lamtoro Gung tree (MC:20%)

28.8 tons/day (24 hours)

2



3

Wood Chip required from Lamtoro Gung tree (MC: 40%)

1,152 tons/month

4

Wood Chip required from Lamtoro Gung tree (MC:40% and 330d/y)

12,672 tons /year

5

Planting area for Lamtoro Gung tree (70% availability)

603.5 ha

6

Annual harvesting product (MC:40%)

30 tons/year/ha

7

An area of 1000 ha (70% availability) could produce wood log with diameter of 5 cm

21,000 tons/year

A 1 MW biomass power plant shall require lamtoro gung wood chips of around 28,8 ton/day (20% wet basis). With an annual productivity of 30 tons/ha/year, technical availability (accessibility to biomass resource to use it as feedstock for energy generation) was assumed to be 70%, an approximately 603.5 ha plantation area is required. Larger power plant capacity will require more plantation area. Unlike dedicated energy crops, the advantage of woody biomass for power generation fuel is that it does not have critical harvest time.

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5.2. Potential wood production from proposed candidates of biomass energy plantation The candidate sites for the energy plantation with estimated annual technical potential of wood production are listed in the following table following the communication with local stakeholders (Dinas Kehutanan Sumba Timur, Dinas Kehutanan Sumba Barat and Dinas Kehutanan Sumba Tengah and PT Usaha Tani Lestari). Table 5.2. Estimation of technical potential of Lamtoro Gung wood production at candidate sites for energy plantation Regency/ Location

Village

Sub‐district

Sumba Timur (Candidate 1) Sumba Timur (Candidate 2) Sumba Tengah (Candidate 3) Sumba Barat (Candidate 4)

Meu 27 Rimba

Kahaungu Eti

Rakawatu

Lewa

Soru

Umbu Nggay


Lamboya

Potential area (ha)

Wood productivity (tons/year)

Technical potential (tons/year)

36,965

1,108,950

776,265

19,748

592,440

414,708

6,350

190,500

133,350

4,720

141,600

99,120

2,033,490

1,423,443

Ratu

TOTAL

* Assumptions: Biomass potential from Lamtoro Gung ,wood yield 30 tons/ha/year and technical availability of biomass 70%, with average calorific value 19.25 kJ/kg ** The Forest Service of Sumba Timur Regency *** The Forestry and Plantation Agency of Sumba Tengah Conclusion from the candidate sites: Forest energy plantation : •

Under forest plantation plan (Lamtoro Gung ) in Sumba Timur, Sumba Tengah and Sumba Barat, estimated power generation is 889 GWh/y

•

Sumba Timur could produce 1,190,973 tons wood chips (could generate at least 90 MW power, 1.2 t biomass (MC:20%)/MWh)

•

Sumba Tengah could produce 133,350 tons wood chips (could generate at least 10 MW power, 1.2 t biomass (MC:20%)/MWh)

•

Sumba Barat could produce 99,120 tons wood chips (could generate at least 7 MW power, 1.2 t biomass (MC:20%)/MWh)

27

Kawasan hutan Kapohak – Penang , merupakan blok‐blok hutan yang ada di wilayah desa, (Meurumba, Kambatabundung, Mauramba). Desa‐desa tersebut saat ini berada dalam wilayah kecamatan Kahaungu Eti sebagai Kecamatan baru yang mekar dari Kecamatan Paberiwai. Kawasan tersebut merupakan bagian dari Das Kambaniru dan Das Melolo. Hutan Kapohak‐Penangg, termasuk dalam Register Tanah Kehutanan (RTK) Thn 1978 no 183. Penetapan kawasan hutan Kapohak – penang dengan fungsi Lindung seluas 3500 Ha dan Fungsi produksi tetap 625 ha, SK Menteri Kehutanan No. 631/Kpts/Um/10/1974. Hutan Produksi tetap seluas 625 ha ini, berlokasi diantara Desa Kambatabundung, Desa Meurumba, dan Desa Mauramba, Kecamatan Kahangu Eti.

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•

Developing energy plantation in Sumba Tengah alone as planned would supply enough electricity (10 MW) in Sumba Island through PLN grid (current demand in Sumba Island 10 MW peak load)

5.3. Biomass supply chain This section will provide feedstock supply process to biomass power plant which will include the following: 1. Feedstock supply 2. Management practices to produce forest biomass 3. Harvesting system 4. Processing/ transportation/ separations systems 5. Processing/ storage Biomass supply chain considered in this report includes harvesting, transportation, storage, handling and fuel preparation for power plant. As noted earlier in section 5.1, 28.8 ton/day lamtoro gung wood chips must be provided for the proposed 1 MW biomass power plant. The provision of this fuel must be well planed and timely executed for a continued operation of the power plant. Biomass fuel is to be sourced from Lamtoro Gung plantations which are assumed to be managed by an authorized party appointed by government. The party shall facilitate and participate and coordinate in biomass supply chain. It is also assumed that the party will also be responsible in biomass preparation (wood harvesting and pre‐treatment). PT Usaha Tani Lestari has indicated willingness to establish and coordinate the woody biomass supply chain. Lamtoro Gung is ready for harvesting after 12‐18 months (consider as dedicated short rotation woody crops (SRWCs). Assuming that an adequate spacing of the trees of 2 m for healthy and good quality of wood/lumber from an area of 600 ha lamtoro gung plantation 38.4 ton of wood will be harvested. The residues/wastes from trees cutting are left on the field. About 8 ton/day residues is estimated to be generated from daily harvest. Lamtoro are pruned during harvesting season and the prunings (branch) are used as a mulch and N source.

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Wood harvesting The harvested log woods are processed into wood chips with size range of 15‐75 mm to suit to feedstock size for gasification after transported to biomass power plant site. 28 The size of the plant per MW has a direct impact on the number of workers required in wood supply chain, though workers for power plant do not vary linearly with MW generation. It is estimated 10 workers are needed for 1 MW plant, with 300 workers for fuel supply. Felling could be done with chainsaws. The trees are cut to length or left whole and are forwarded with grapple loaders for moving to a landing area from which are loaded onto trucks for transporting to a pre‐treatment facility. In case that excess of labor in the surrounding plantation area exists with low wage rates and costly fuel, felling and forwarding could be performed manually. To be conservative, it is assumed, based on several harvest rates from reference, that a harvest rate of 0.4 dry tonnes/day Lamtoro Gung wood could be achieved. But, this value could be different from the real plantation later on at the candidate sites due to local site conditions such as plantation density, tree size, forwarding distances, climate, season, topography.29 Pre‐treatment For a combustion technology the quality of wood chips requires less …than for a gasification technology. Moisture content and size up to 40% and 50% are tolerated in boiler. In the gasification technology, wood fuel requires specific moisture content and size (and sometimes also preferred feedstock e.g. with low ash) depending on the type of gasifier. Therefore, additional drying, milling, chipping and screening are used as pretreatments. As later on in the next chapter discussed, the specification of wood fuel for the gasification technology (using downdraft type gasifier) are wood chips with moisture content about 20% and size 15‐75 mm. The pretreatments of Lamtoro Gung wood to achieve the specification are drying, chipping and screening. The pretreatment would occur prior to use at the power plant facility. 28

http://webcache.googleusercontent.com/search?q=cache:Tra3YowpHuIJ:https://inlportal.inl.gov/portal/server.pt/docu ment/30968/tm2008‐008‐ 0_supply_system_costs_of_slash,_forest_thinnings,_and_commercial_energy_wood_crops_pdf+&cd=2&hl=en&ct=clnk&gl =id Wood chips are prone to self-heating and dry matter loss when moisture content is greater than about 20% (wet basis) (Springer 1979). To mitigate this potential problem, a just-in-time delivery system is used so that chips are seldom stored longer than 15 days and the pile height is held under 30 ft (Springer 1979; McDonald and Twaddle 2000) 29

https://bioenergy.ornl.gov/reports/fuelwood/chap3.html

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Normally, fresh harvested wood contains about 40‐50% moisture (wet basis). Moisture content higher than 50% could cause significant decrease of boiler efficiency in combustion technology.30 With regard to the climate of Sumba Island it would be possible to reduce moisture content through natural air dry about 15%, but this would require a time period of 30 – 60 days.31 For a conversion system requires small sizes of wood as feedstock, the harvested wood can be chipped soon after harvesting. In case that a conversion system requires dry feedstock, moisture content below 50%, then green chips would have to be stored. Instead, felled trees can be stored in whole form for storage and drying, thereby reduces decomposition losses. Generally, it is known that drier wood is more difficult to chip and to ensure uniform size. At harvest time, the moisture content of Lamtoro gung wood is estimated in the range 30‐50%, and thus would require drying to suit to fuel characteristic either for boiler or gasification. Moreover, high moisture content would reduce transportation efficiency and storage time (durability). The moisture should be reduce to 20%. When air‐dry to 30% moisture content is possible, it would reduce or even eliminate the heat required for drying and thus save energy. Transportation Transportation costs are the costs for transporting biomass from the forest landing to the power generation plant. Transportation costs are calculated based on distance traveled and diesel fuel cost of Rp 6000/litre. The total number of trips required to transport woody biomass is estimated from the total amount of woody biomass available in candidate sites, biomass density, and the freight of truck arrangement. Items considered in the calculation of transportation cost of biomass to power plant include: unit cost of transportation (Rp/km), number of trucks and capacity of trucks, fuel consumption (litre/100km), total distance to transport wood fuel to power generation plant, fuel consumption/cost. 30

https://bioenergy.ornl.gov/reports/fuelwood/chap3.html

31

http://www.advancedbiomass.com/2011/11/biomass-storage-pile-basics/

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Fuel handling and Storage Consideration of biomass outdoor storage for up to 15 days32 would be important as a biomass power plant is to be run continuously all year around. This could anticipate seasonal variation in Sumba Island where dry season occur normally for 8 months (from April to November). Wood chips biomass could be stored outdoor (in open area) in piles. After field drying, outdoor stored wood would be expected to only slightly increase in moisture content from precipitation.33 The followings are to be considered in designing fuel storage facilities, which include: storage area which is close to the selected conversion system (boiler or gasifier), characteristics of wood fuel to be stored, additional feedstock preparation requirements, back‐up storage capacity, seasonal weather variation, and operational requirements of the selected conversion technology. A fuel storage system could be an open or a covered system, but an open system would be cheaper. A fuel feeding system would transfer wood from storage facility to a selected conversion system. Fuel can be stored in silos, hoppers, containers. 5.4. Projected biomass purchasing and cost Woody biomass from Lamtoro Gung plantations is assumed to be purchased from a third party that is appointed by local government which is also responsible for the management of the plantations and harvesting. Stumpage, forest operational costs and biomass transportation costs are the costs that determined delivered cost. It is estimated that the industrial plantation forest development cost pert ha would be Rp 15,356,350/Ha.

32

http://webcache.googleusercontent.com/search?q=cache:Tra3YowpHuIJ:https://inlportal.inl.gov/portal/server.pt/docume nt/30968/tm2008‐008‐0_supply_system_costs_of_slash,_forest_thin nings,_and_commercial_energy_wood_crops_pdf+&cd=2&hl=en&ct=clnk&gl=id Wood chips are prone to self-heating and dry matter loss when moisture content is greater than about 20% (wet basis) (Springer 1979). To mitigate this potential problem, a just-in-time delivery system is used so that chips are seldom stored longer than 15 days and the pile height is held under 30 ft (Springer 1979; McDonald and Twaddle 2000)

33

www.fs.fed.us/rm/pubs_other/rmrs_2014_keefe_r001.pd

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Table 5.3. Cost estimation of industrial plantation forest development per ha of PT Usaha Tani Lestari (for first year) No Activity Unit Cost/Unit I. Non loan‐Cost component /Komponen Biaya Bukan A. Planning 1 Preparation of FS and EIA Ha 32,500 2 Preparation RKUPHHK Ha 25,000 3 Preparation RKTUPHHK Ha 12,500 4 IMB (building permit) cost Ha 14,000 5 Boundaries (Tata Batas) Ha 40,000 6 Layout area Ha 196,000 Total A 320,000 B. Development of facilities and infrastructure 1 Making Building, Procurement and Construction Equipment Road Ha 2,450,000 2 Maintenance of Infrastructure Ha 32,750 Total B 2,482,750 C. Administration and general 1 Education and Training Ha 49,000 2 Research and development Ha 98,000 3 General costs Ha 980,000 4 Appraisal Ha 71,000 Total C 1,198,000 Total I 4,000,750 II. Cost component of revolving loan fund as working capital A. Planting 1 Nursery and Seedling Ha 2,420,000 2 Land preparation Ha 3,214,000 3 Cultivation Ha 684,000 Total A 6,318,000 B. Maintenance 1 Maintenance Year I Ha 1,082,000 2 Maintenance Year II Ha 852,000 3 Maintenance Year III Ha 748,000 4 Further Maintenance I Ha 425,000 5 Further Maintenance II Ha 213,000 Total B 3,320,000 C. Protection and Forest safeguard 1 Pest and Disease control Ha 260,000 2 Fire control Ha 110,000 3 Security Forests Ha 122,000 Total C 492,000

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D. E. 1 2 E 1 2

Food crop cost (in a agroforestry pattern) Ha 1,000,000 Total D 1,000,000 Obligation to the country (fee, land value tax) contribution IUPHHK Ha 2,600 Property taxes Ha 3,000 Total E 5,600 Total II 11,135,600 III. Cost component which can be borrowed or not as revolving fund Liability To the Environment Physical Chemistry Biology Ha 98,000 Social Environment Ha 122,000 Total E 220,000 Total III 220,000 Total (I+II+III) 15,356,350

Source: PT Usaha Tani Lestari

5.5. Options for biomass fuel supply agreement

Two options are considered for wood supply from a supplier: ‐

Wood delivered to storage facility in the form of wood log In this case, the power plant investment should include fuel pretreatments facility (drying, chipping, and screening). Logs delivered should be of uniform size and shape.

‐

Wood delivered to storage facility in the form of wood chip The wood chip would be delivered from a selected supplier to deliver wood chip either by the tons, volume or energy content, depending on what is stated in an agreement of fuel supply

The supplier must provide wood chips according to the specification required for the selected technology. Consistency in size and moisture content as well as a continue amount of supply is priority. Therefore, fuel quality control is highly necessary for smooth operation of the power plant. A quality assurance from the supplier should be put in the agreement to reduce troubles in operating the power plant.

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5.6. Biomass pre‐treatments /processing options Biomass process would improve the characteristics of biomass as a fuel. The processes mainly involve the reduction of moisture content and improving characteristics of biomass. The energy content of biomass is utilized through one of following three processes: physical, biological and thermochemical, of which biological and thermochemical are outside the scope of this pre‐ feasibility. Physical processes It is aimed at modification of the biomass feedstock to improve its fuel characteristics. Some methods are given below: i.

Particle size reduction: Biomass size modification through chipping and fabrication into pellets facilitates easy storage and transportation. This also helps in achieving fuel characteristics required for combustion or gasification technology.

ii.

Separation (Screening): Separation process would be required to screen particle size of beyond the standard for the technology adopted.

iii.

Drying: Drying process would include vaporisation of all or part of the water in the feedstock. Solar drying is one of the cheapest methods. Reduction of water content shall reduce energy consumption.

iv.

Compaction/pelletizing: Biomass compaction in the form of pellets would results in uniform combustion. Binding agents such as thermoplastic resins can be used for manufacturing pellets.

Feed Handling and Preparation: The biomass feedstock is dried from its as‐received moisture level to less than 50% to minimize water content to acceptable level for feedstock of the selected conversion technology, namely gasification technology as later on discussed in the following chapter 6. It is then

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ground to 15‐75 mm particle size to yield sufficiently small particles, ensuring rapid reaction in the gasification reactor. 5.7. Supplementary biomass There is no supplementary biomass is considered for the proposed biomass power plant. The biomass used as fuel is only from Lamtoro Gung wood. 5.8. Biomass risks mitigation Table 5.4. Biomass risks mitigation to be considered Risks Seasonal variation – Feedstock security of supply climate Weather and seasonal variations could lead to variation of feedstock supply quantity, different quality and price.

Mitigation It is anticipated through providing a large biomass buffer stocks. Consideration of biomass outdoor storage for up to 15 days34 would be important as a biomass power plant is to be run continuously all year around. This could anticipate seasonal variation in Sumba Island where dry season occur normally for 8 months. Wood can be harvested and stockpiled outdoors to warrant a continue fuel supply during monsoon or when harvesting activity is impossible. Disease Woody biomass production is Energy plantation that is largely prone to plant disease which may depending on the production of lower its production. woody material must be well managed and maintained. Periodical checking of trees health would be unavoidable. Fuel supply contract Risk of contract violation by biomass ‐ All main supplies are contracted suppliers with insurance

34

http://webcache.googleusercontent.com/search?q=cache:Tra3YowpHuIJ:https://inlportal.inl.gov/portal/server.pt/docume nt/30968/tm2008‐008‐0_supply_system_costs_of_slash,_forest_thin nings,_and_commercial_energy_wood_crops_pdf+&cd=2&hl=en&ct=clnk&gl=id Wood chips are prone to self-heating and dry matter loss when moisture content is greater than about 20% (wet basis) (Springer 1979). To mitigate this potential problem, a just-in-time delivery system is used so that chips are seldom stored longer than 15 days and the pile height is held under 30 ft (Springer 1979; McDonald and Twaddle 2000) http://www.advancedbiomass.com/2011/11/biomass‐storage‐pile‐basics/: biomass‐fired power plants will stockpile a minimum of 20‐30 days worth of fuel, but many will store 60‐days worth or more

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Land availability

Competitive users

Transportation distance

Lack of transparency of land acquisition or permit on land utilization

Illegal logging of Lamtoro Gung wood could influence biomass feedstock quantity for the proposed power plant project. Woody biomass from Lamtoro Gung tree designed as the feedstock for the proposed project is generally used by local community in Sumba island as cooking fuel. – Long distance from plantation to power plant location, where road transportation is necessary, is vulnerable to fuel price variation.

Fire risk

Woody biomass is also susceptible to fire risk, particularly during dry season.

Public acceptance

The public needs to be informed and confident that bioenergy is environmentally and socially beneficial and does not result in significant negative environmental and social trade‐offs. However, the industry is confident such challenges can be met as similar

‐ When possible, a backup source for biomass supply is recommended ‐ Preparing a reasonably large storage for biomass as feedstock Seek advice from local governments regarding a list of property available for the energy plantation and the site for biomass power plant Socialization of the energy plantation project to local communities surrounding the plantations is necessary. This is to provide them with the concept of the energy plantation for electricity generation that could benefit people of Sumba Island and in local economy development. Estimation of economical feasibility should include sensitivity on among other fuel price escalation and inflation. This is to foresee the project feasibility during the project lifetime. Lamtoro Gung energy plantation must be well protected from any intruder or unauthenticated to minimize irresponsible actions. Also, biomass facilities require fire protection measure. In the development planning, facility for fighting forestry fire hazard should be considered as well. Stakeholders and local people need to be informed and convinced that the project would bring environmentally and socially benefit and would not result in negative impacts.

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challenges have been addressed in other sectors and appropriate technologies and practices are being developed and deployed.

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6. TECHNOLOGY OPTIONS Various biomass conversion technologies could transform biomass into heat, electricity and biofuels. Generally the conversion technologies are developed through the following conversion routes: thermochemical, physical, biochemical and chemical. Combustion, pyrolysis and gasification are the three main thermo chemical processes which alter biomass physically and chemically through heating. These processes depend on temperature, existence of oxygen and residence time. In case that biomass is desired as fuel for electricity generation other than heat, two possible candidates as summarised as: ‐ Direct combustion in conventional boiler/steam turbine/condenser technology ‐ Gasification with selection of gas turbine or internal combustion engine Other two biomass conversion process technology considered are pyrolsis and cogeneration (allowing simultaneous generation of heat and power (CHP) which increases global efficiency). CFP uses a condensing‐extraction (or back‐pressure) turbine. 6.1. Biomass characteristics (Lamtoro Gung) A selected woody plant species for bio‐energy plantation must have high wood calorific value, ability to produce wood of high density and capability for growing rapidly on a broad range of sites. These are required particularly related to the combustion and gasification (thermochemical) processes. Lamtoro Gung is a fast‐growing tree species which its wood density varies from 500‐640 kg/m3 (as cited from many references). Biomass fuels such as this species have lower density than fossil fuels such as coal, oil and gasoline. As a result, at an equivalent energy biomass fuel would require larger volume to transport than the fossil fuels. Therefore, it is generally recommended to have an energy plantation close to the power plant utilizing biomass as fuel from the plantation as this would minimize the transportation cost. It is estimated that wood production and delivery cost in Sumba are Rp 239,523/ton and Rp 25,000/ton respectively. The products are sold at at price of Rp 450,000/ton. For the purpose of thie report is is assumed that the price of biomass is 40 USD per ton on air dry base (not wet, not dry weight). The price excludes chipping cost after harvesting wood.

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Moisture content of wet lamtoro gung wood varies according to its age, ranging between 30 to 50%.35 Its content will affect to the quality of biomass fuel for combustion and gasification processes. Lamtoro Gung wood is estimated to have a calorific value of 19,250 kJ/kg (equivalent to 4,597 kcal/kg). Wood usually contains very small inorganic matters such as alkali and other compounds such as S, P, Cl, N, Al, heavy metals. After a total combustion of wood, the remaining inorganic matters are called ash. Lamtoro Gung wood contains 69.8‐73.9% holecellulose, 8.9 20.1%, pentosans; 21.8‐26.0% lignin; 13.0‐16.4% caustic soda soluble, and 0.7‐0.9% ash.36,37,2138 The chemical components of Lamtoro Gung is in the range of that of soft wood (volatiles 0.5 wt%, ash 0.5 wt%, lignin 25‐35 wt%, cellulose 40‐45 wt%, hemicelluloses 25‐28 wt%). 6.2. Combustion Technology Among thermo chemical conversion technologies of biomass, direct combustion of biomass in a boiler is the most common technology applied so far for generating electricity and heat generation. With this technology, combustion of biomass produces a hot flue gas which could be used for heating or producing steam for processing purpose or electricity generation. Combustion systems are commercially available technology ranging in sizes from 2 kW to 500 MW. The most influencing biomass characteristics in the combustion process are moisture content, chemical composition and energy content. Biomass fuel for combustion fuel is recommended to have moisture content of lower than 50% and higher than this would require pre‐drying.39 More energy would be required to evaporate water for biomass with higher moisture content, which in turn lowers combustion efficiency. 35

http://proseanet.org/prosea/e‐prosea_detail.php?frt=&id=3025 http://www.fao.org/docrep/006/AD583E/ad583e00.pdf: The natural water content in green wood is always high; even hardwood species contain as much as 50‐60% water. When trees are cut, the water content in wood starts decreasing rapidly and reduces to 30‐40% within a short time even in damp climates. And 3‐6 months after the harvest it may go down to only 10‐20%, on an air‐dried basis. 36 idl-bnc.idrc.ca/dspace/bitstream/10625/7620/1/IDL-7620.pd 37

http://wgbis.ces.iisc.ernet.in/energy/paper/TR109/tr109_intr.htm

The chemical structure and composition of wood determines its combustion efficiency, as combustion is a series of chemical reactions. Generally softwoods have 40‐45% cellulose, 24‐37% hemicellulose and 25‐30% lignin. The hardwoods contain approximately 40‐50% cellulose and 22‐40% hemicellulose. 38 39

http://www.pacificbiomass.org/documents/Oregon3EasternCountiesBiomassAssessment.pdf http://data.obitet.net/makale/makale/internalcombustionengines/097.pdf

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Type of combustion technologies Combustion technologies are distinguished in fixed‐bed combustion, fluidized bed combustion (bubbling and circulating) and dust combustion. These combustion technologies will produce boiler efficiencies ranging from 65 to 75% with net plant efficiencies from 20 to 25%.40 Fixed‐bed combustion systems include grate furnaces and underfeed stokers. The most commonly used types of boilers for biomass combustion are stoker boilers and fluidized bed boilers. Both can be fueled entirely by biomass fuel or cofired with a mix of biomass and coal. Fixed‐bed combustion Boiler (Stoker) Grate furnaces This type furnace is suitable for high moisture content biomass fuels, varying particle sizes (limited to the amount of fine particles in the fuel mixture), and high ash content.41 The capacity applied is up to around 20 MWth. The grate are available: stationary or travelling grate. Moving grate boilers (stepped grate or inclined grate boilers), are designed to burn wood chip with moisture content between 30%‐50%, but also dry wood chip.42 The followings are specific technologies which include stoker boilers, fluidized bed boilers, and cofiring43 Stoker Boiler Stoker boilers, the simplest boiler type having relatively small grate, employ direct fire combustion of solid fuels with excess air. Hot flue gases produced generates steam in the heat exchange section of the boiler. The steam could be used directly for heating purposes or passed through a steam turbine generator for producing electricity. Stoker boiler is suitable for burning wood pellet or chips with up to 30% moisture content. There are two general types of stoker boiler system; underfeed and overfeed. Underfeed stokers supply both fuel and air from under the grate, while overfeed stokers supply fuel from above the

40

https://bioenergy.ornl.gov/reports/fuelwood/chap3.html http://energoeffekt.gov.by/bioenergy/htdocs/en/practa.pdf 42 http://www.biomassenergycentre.org.uk/pls/portal/docs/PAGE/BEC_TECHNICAL/BEST%20PRACTICE/37821_F OR_BIOMASS_2_LR.PDF 43 http://www.epa.gov/chp/documents/biomass_chp_catalog_part5.pdf 41

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grate and air from below. Underfed stoker boilers could burn wood pellets and wood chips up to 30% MC. It is a cheap safe technology for small‐ and medium‐scale systems up to about 6 MWth and suitable for biomass fuels with low ash content such as wood chips, sawdust, pellets and small particle sizes (up to 50 mm), with a maximum allowable moisture content 40%. With underfeed combustor, a boiler efficiencies of 80‐85% could be achieved. Underfeed system with single screw combustors is available for capacities up to 2 MWth, while multiple screw combustors up to 6 MWth. Two types of overfeed stokers exists—mass feed and spreader. In the mass feed stoker, fuel is continuously fed onto one end of the grate surface. Spreader stokers are the most commonly used stokers because of their versatility. It is commonly employed for wood‐fired boilers with a steam generation rate larger than 100,000 lb/h. Though spreader stokers are the most common stokers among larger wood‐fired boilers, overfeed and underfeed type stokers boiler are also applied for smaller units44 Dust combustion In this system combustion takes place while the fuel is in suspension and gas burnout is achieved after secondary air addition. Small size fuel of less than 2 mm and low moisture (<15%) is blown into the boiler and combusted by supporting it in air rather than on fixed grates. Variations of these technologies are available. Examples are combustion systems with spreader stokers and cyclone burners. Fluidized Bed Boilers Biomass is burnt in a mixed suspension of gas and solid bed material (usually silica sand and dolomite) in fluidized bed. Air for combustion enters from below. These plants usually operate at full load. The plants are of special interest for large scale applications (normally larger than 30 MWth). Fluidized bed boilers are categorized as either atmospheric or pressurized units. Atmospheric fluidized bed boilers are further divided into bubbling‐bed and circulating‐bed units; the fundamental difference between bubbling‐bed and circulating‐bed boilers is the fluidization velocity (higher for circulating). Fluidized bed boilers are categorized as either atmospheric or pressurized units. Atmospheric fluidized bed boilers are distinguished further into bubbling fluidised beds (BFB) and circulating fluidised beds (CFB) have to be distinguished. A proper biomass pre‐treatment system for particle 44

http://www.epa.gov/ttnchie1/ap42/ch01/final/c01s06.pdf

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size reduction (usually below 40 mm for CFB units and 80 mm for BFB units) and separation of metals is required. The disadvantage of FB combustion plants is the high dust loads entrained with the flue gas, requiring dust precipitators and boiler cleaning systems. BFB is normally applied for plants with boiler capacity of larger than 20 MWth, while CFB combustion is of interest for plants larger than 30 MWth. A CFB system is achieved with fluidizing velocity to 5 to 10 m/s and using smaller sand particles diameter (0.2‐0.4 mm). The circulating bed is most suitable for fuels of higher heating values. The disadvantages of CFB furnaces are their larger size (thus higher price) and higher loss of bed. Small biomass particle size required (between 0.1 and 40 mm in diameter), results in higher investments in fuel pre‐treatment. The own consumption of electricity is about 1 % point higher from CFB boilers than from grate fired boilers (2‐3 % for grate fired boilers and 3‐4 % for BFB/CFB boilers according to Evald and Witt (2006)) Burning solid fuels in a pressurized fluidized bed boiler produces a high‐pressure stream of combustion gases. After the combustion gases pass through a hot gas cleanup system, they are fed into a gas turbine to make electricity, and the heat in the hot exhaust gas stream can be recovered to boil water for a steam turbine. Therefore, a pressurized fluidized bed boiler is more efficient, but also more complicated and expensive. Capital costs of pressurized fluidized bed combustion technology are higher than atmospheric fluidized beds For smaller plants, fixed bed systems are usually more cost‐effective. Ash is a by‐product of wood combustion, the quantity produced varying from 0.5% to 2% or more of the dry weight of wood chip or wood pellet burned. Cofiring: In a cofiring combustion system, a portion of biomass (up to 20%) substitutes coal in an existing boiler. Since no major modifications are required in existing plant, it is an economic option for introducing new biomass power generation. Bomass can substitute for up to 20 percent of the coal used in the boiler. Cofiring is typically applied when either the supply of biomass is intermittent or biomass has high moisture content. Cofiring of coal with biomass occur at large

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plants, but at small plants more biomass is used for cofiring with natural gas. Homogenization of fuel with different moisture contents at the fuel yard is a necessity. Potassium ash content which is relatively high in fresh wood, green particles, and fast‐growing biomass, could cause the ash to melt at low temperatures leading to fouling and slagging. Moreover, biomass fuels could contain chlorine and alkalis which may induce corrosion. Net bio‐energy conversion efficiencies for biomass combustion power plants range from 20% to 40%. The efficiency of combustion technology can be increased by applying the so‐called cogeneration technology in which simultaneous generation of heat and power (CHP) occurs. 6.3. Gasification Technology Gasification is a process of converting biomass to combustible producer gas (syngas), which is then converted to power in an internal combustion engine. Syngas produced has low heating value of around 4‐6 MJ/Nm3 if air is used as oxydizing agent. Syngas after cleaning process (and filtered) can be burnt directly or used as a fuel for gas engines and turbines for power generation. Gas cleaning generally consists of a series of filters. Syngas used for driving IC engine could be run in 100% gasification and in dual mode (with 20% diesel oil addition into the combustion chamber). In smaller systems, the syngas can be fired in reciprocating engines, microturbines, Stirling engines, or fuel cells. Important biomass properties affecting gasification process are: ₋

Moisture content Gasification process requires relative dry biomass feedstocks for producing a higher quality gas (higher heating value, higher efficiency and lower tar levels). The process requires the water content of biomass to be low (<20 %) for proper operation. Woody biomass like Lamtoro Gung (with water content 30%‐50%) would certainly require pre‐drying. The option is to perform drying using waste heat from the gas engine and is integrated with the gasification plant for maintaining a relatively constant moisture content of the biomass.

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₋

Ash content and ash composition Ash formed after completion of a combustion process contains inorganic and mineral of biomass. The chemical composition of ash in biomass affects the melting behaviour of the ash. Ash melting can cause slagging and channel formation in gasification reactors. Woody biomass could produce ash of up to 0.1%.45

₋

Volatile matter content Volatile matter content influences tar production levels in various types of gasifier design (updraft gasifier, fluid bed gasifier, or downdraft gasifier). Biomass contains volatile matters in the range of 50% to 80%.46

₋

Element composition Biomass elemental composition will influence the heating value of the gas and to emission levels. The biomass bulk density and morphology together with the heating value will determine the energy density of the gasifier feedstock, i.e. the potential energy available per unit volume of the feedstock.

₋

Density and morphology Low density of biomass in fixed bed gasifier reactors could cause a high voidage which in turn resulting in channeling, bridging, incomplete conversion and decreasing gasifier capacity. Fluid bed gasifiers have more flexibility to biomass density but feeding remain problematic.

Gasification has greater efficiency in power production than that using direct combustion. Other advantage of gasification is that its ability to receive low ash melting point feedstock, unlike direct combustion technology (melted ash fouls boiler). The main drawback in gasification is related to the presence of tars in the syngas, which is corrosive and makes the fuel gas inappropriate for use in internal combustion engines. However, nowadays, cleaning systems have been in constant development. McKendry, P.; Energy production from biomass (part 2): conversion technologies; Bioresource Technology, 83 (2002) 47‐

45

54 (http://www.diva‐portal.org/smash/get/diva2:547536/FULLTEXT01.pdf) 46 http://www.iafbc.ca/funding_available/programs/livestock/documents/LWTI‐1_FR_App3.pdf

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Syngas from wood biomass to be utilized for power generation is difficult to clean up. In many cases, syngas cooling prior to combustion is required to remove tars and other contaminants, thereby losing the sensible heat. When necessary, pre‐drying of wood is performed prior to gasification for sustaining combustion. Three gasification technologies exist; fixed bed gasification, fluidized bed gasification, and entrained flow gasification. Fixed Bed Gasifiers Fixed bed gasifiers are generally equipped with a fixed grate inside a refractory‐lined shaft. Biomass feedstock is typically placed on top of the pile of fuel, char, and ash inside the gasifier. The distinction of fixed bed gasifier types is based on the direction of air (or oxygen) flow in the gasifier. A downdraft gasifier involves air flows down through the bed and leaves as biogas under the grate. Air flows up through the grate and biogas is collected above the bed in updraft gasifier. Meanwhile, air flows across the bed, exiting as biogas in a crossflow gasifier. This gasifiers are commonly applied for small‐ to medium‐scale application (< 5 MW). Updraft gasifier produces syngas with higher tar than downdraft gasifier, but high gas outlet temperature of downdraft gasifier forms a drawback. Fixed bed gasifiers are considered suitable for small‐scale distributed power generation equipment. However, its economic viability depends on variable economics of biomass collection and feeding and particularly site‐specific. Fixed bed gasifiers are fed with large fuel particles so that no complex fuel preparation is necessary. However, it is limited to its ability to handle fine particles. Updrat gasifier produces syngas with high tar content, which requires comprehensive gas cleaning, particularly for using in internal combustion engines which requires gas cooling. Syngas produced from updraft gasifier could alternatively be used for direct heating application where gas cooling is not necessary.47

47

https://www.princeton.edu/pei/energy/publications/texts/Small_scale_‐gasification.pdf

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Fluidized Bed Gasifiers In this type gasifier, the gasification medium (steam, air or oxygen) are mixed with biomass material in a hot bed material (such as sand). There are two designs of fluidized bed gasifier; circulating and bubling fluidized beds. The benefits of fluidized bed gasifiers are their high productivity (per area of bed) and flexibility. They also able to accomodate a wider range of biomass feedstocks with moisture contents average of up to 30%. However, a defined fuel particle size range are required for this type of gasifier. The technology is recommended for a large scale plant due to its complex process. Entrained flow gasification This type of gasifier requires fuel in the form of a fine owder (typically 0.5 mm). The fuel is entrained co‐currently by a carrier gas (oxidant), and is gasified. Entrained flow gasifier is operated at high temperature (1200 – 1600 °C). Due to its high operating temperature, it results in CO and H2 rich gas and relatively clean gas compared to fixed bed and fluidized bed gasifiers. The following technologies are available with specific respect to their ability to run on biomass or biogas. Gas (combustion) turbines: Gas turbine technology is available for large system. Modifications are required to existing natural gas turbine for applying gas turbine for a low‐Btu gas produced from gasification. Gas Engines – Syngas produced from biomass gasifiers has been commercially used as fuel for spark ignition gas engine. Spark ignition engines could be operated on 100% syngas. However, the dust content in the gas should be as low as possible. Syngas can also be used in compression ignition (diesel) engines. Diesel engine has higher efficiency, greater durability and reliability, simpler maintenance than spark ignition engine. Utilization of syngas in diesel engine could substitute diesel oil used. Commercial diesel engines require only minor modifications to suit for syngas application.

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48

Figure 6.1. Gasifier size by type 6.4. Cogeneration Cogeneration is a technology that applies simultaneous generation of heat and power (Combined Heat and Power/CHP). The overall efficiency of a cogeneration system is higher than a separate production of heat and electricity. The plant efficiency improves from 25‐35 % when only electric power is produced to an overall efficiency of 70‐90 %.49 Through a CHP system biomass fuels could be used most efficiently and beneficially. A CHP system offers a waste‐heat recovery for heating, cooling, or process applications. The system consist of a number of individual components: heat engine (such as combustion or gas turbines, steam turbines, reciprocating engines, micro‐turbines, and fuel cells), electricity generator, heat recovery, and electrical interconnection. CHP system based on biomass combustion has been developed with a capacity of higher than 2,000 kWel with steam turbine proved to be economic and feasible, while in capacity range of between 200 – 2,000 kWel Organic Rankine Cycle has been proved to be mature in technology, though steam engine and steam turbine are also suitable technologies. For a CHP plant up to 100 kWel, stirling engine process is an appropriate choice so far.50 48 https://www.irena.org/DocumentDownloads/Publications/RE_Technologies_Cost_Analysis‐ BIOMASS.pdf) 49 50

http://lnu.diva‐portal.org/smash/get/diva2:445550/FULLTEXT01

http://www.elmiraohio.com/Organic%20Rankine%20Cycle%20Docs/Obernberger‐2008‐INFUB‐keynote‐bm‐combustion‐ gasification.pdf

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The main biomass CHP system generally consists of biomass receiving and preparation unit, conversion technology unit (biomass combustion or biomass gasification), and power and heat production unit (conversion of syngas or biogas or steam into electricity and process steam and hot water). CHP system based on biomass downdraft gasifier would require limited size variation (20‐100 mm)and dry biomass (moisture content <20%).51 CHP systems are applied in agriculture‐based industries such as sugar mill and palm oil mill, where heat produced from the CHP systems are captive used in the mills. There is no industries in the area considered in this report, as such a CHP system is not recommended to be developed. 6.5. Pyrolysis Pyrolysis involves thermal decomposition of carbonaceous material in the absence of oxygen to produce solid (char or carbon), gases (CO2, H20, CO, C2H2, C2H4, C2H6, C6H6,etc.), and a liquid product of oxygenated hydrocarbons (bio‐oil). Generally, this occurs at around 300‐650⁰C.52 The pyrolysis oil can then be used as a fuel to generate electricity. Pyrolysis also occurs both in combustion and gasification at earlier stages. In a Slow Pyrolysis, the primary product through carbonization is Char, while in a Rapid/Fast Pyrolysis the primary product is Bio‐oil and Gas. Pyrolysis in a Medium uses usually water (producing bio‐oil with reduced oxygen content) or Hydrogen (for increasing light hydrocarbons). Char yield decreases when higher temperature and smaller particles are applied in the process. Biomass composition will have influence on the pyrolisis products. Pyrolisis of wood produces more volatiles and less char.53 Rapid heating to a moderate temperature (400‐600⁰C) will produce higher volatiles and increased oil production.54 Bio‐oil is unstable product which limits long‐term storage. It is not miscible with any conventional hydrocarbon‐based fuel. Bio‐oil can be stabilized for long‐term storage and converted to a conventional hydrocarbon fuel through oxygen removal via hydrotreating.

51

http://www.elmiraohio.com/Organic%20Rankine%20Cycle%20Docs/Obernberger‐2008‐INFUB‐keynote‐bm‐combustion‐ gasification.pdf

52

http://poisson.me.dal.ca/site2/courses/mech4840/Pyrolysis%20&%20Torrefaction%20of%20Biomass.pdf http://www.diva‐portal.org/smash/get/diva2:8949/FULLTEXT01.pdf 54 http://poisson.me.dal.ca/site2/courses/mech4840/Pyrolysis%20&%20Torrefaction%20of%20Biomass.pdf 53

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Bio‐oil obtained from fast pyrolysis of biomass (substitute fuel oil) can be used to generate electricity and heat in power generation systems. Diesel engines and turbines are considered potentially important markets for bio‐oil rather small generation capacities, co‐firing in power stations is limited to large plants. 6.6. Selection of Power Generation Technology and options of technology provider The selection of power generation technology depends on the following items as given in the following table, based on annual availability of selected biomass fuel of Lamtoro Gung wood. The selection of power generation technology depends on the following items as given in the following table, based on annual availability of selected biomass fuel of Lamtoro Gung wood. Table 6.1. Selection of power generation technology Items Plant capacity

Gasification Minimum 10 kW

Combustion Economical combustion – steam power generation process > 3 MWe55

15‐35% Potential for more efficient conversion process when generating power. biofuel‐to‐electricity efficiency reaches 30‐40 % and overall performance efficiency in the range of 90 %56 Utility ‐water Elimination of water use, if power generation without steam turbine Engine Gas engine Electrical Efficiency

Status technology

mature

mature

Remarks Direct combustion technology is simpler, lower cost, more flexible in fuel moisture and size, and more mature (proven) than gasification. However, direct combustion has higher emissions and a less efficient conversion process than gasification; and requires water for steam turbine power generation. Combustion is usually carried out in a boiler to generate steam for electricity generation by steam turbine. the electrical efficiency is greater than by steam turbine.

Biomass power plant to be developed is located in Sumba Island with dry climate area low cost, and reliability; it also works well even at low loads

55 http://cgpl.iisc.ernet.in/site/FAQ/MostFrequentlyDiscussedIssues/CombustionvsGasification/tabid/163/Default.aspx: It is conventionally understood that combustion – steam power generation process is economical for large power levels, typically in excess of 3 MWe. The cost per MWe installed is about 1 million USD. The actual performance shows a fuel-to-electricity efficiency of ~ 30 %. Even 200 MWe steam power generation systems deliver fuelelectricity efficiency of 35 % (using coal with higher calorific value). 56

http://lnu.diva‐portal.org/smash/get/diva2:445550/FULLTEXT01

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The net electrical efficiency of gasification plant with gas engine system is the highest (10‐28%) than the plant with gas turbine, steam turbine, or externally fired gas turbine systems. Moreover, a gas engine system is relatively inexpensive and reliable as well as durable. Despite of these, the system requires short maintenance interval resulting in low availability. Efficiency of a CHP system is site‐specific. The followings are commonly installed CHP prime movers with standard ranges of achievable efficiency; Steam Turbine: 80 percent, Diesel Engine: 70‐80 percent, Natural Gas Engine: 70‐80 percent and Gas Turbine: 70‐75 percent.57 Based on the references and as given in the table above it is determined that gasification technology is better suited for this project for the following reasons: ‐

Status of the technology: Gasification technology for woody biomass power plant is to a large extent has been commercialized in the past decade. Although the technology results in tars, this issue is considered solvable with gas cleaning technology developed so far.

‐

Plant capacity

‐

Minimal water use

Size of biomass power plant The size of the plant is dimensioned with regard to potential available Lamtoro Gung wood chips in respective candidate sites and reasonable plant size. As early mentioned in section 4, technical potential available of lamtoro gung wood from all candidate sites are 776,265 tons/year (Kapohakpenang, Candidate 1), 414,708 tons/year (Rakawatu, Candidate 2), 133,350 tons/year (Pahedutillu, Candidate 3), 99,120 tons/year (Lamboya, Candidate 4) respectively. Based on the selected technology for the biomass power plant to be developed, estimation on power plant size for all candidates is given in the table below. 57

http://www.epa.gov/chp/basic/efficiency.html

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Table 6.2. Potential size of biomass power plant Candidate site Power plant Remarks size* (MW) Kapohakpenang (Candidate 1) 61.26 Technical availability was assumed to be 70%. Rakawatu (Candidate 2) 32.73 Technical availability was assumed to be 70%. Pahedutilli (Candidate 3) 10.52 Technical availability was assumed to be 70%. Lamboya (Candidate 4) 7.82 Technical availability was assumed to be 70%. *Based on technical potential of lamtoro gung wood and the selected technology is gasification Notwithstanding the potential of the wood available in all candidate sites capable for producing more than 2 MW, it is suggested to develop biomass power plants of 1 MW. The reason for this is that over 10 years the projected demand in the Island is only around 10 MW. Moreover, existence of abundant biomass resource from the energy plantations would potentially secure biomass feedstock for the plant even during long dry season. Other consideration to the suggestion of 1 MW development is the capability of PLN transmission line to which the electricity of the plant is connected. Power plant location Considering the land area for energy plantation, the reasonable distance from the plantation to the power plant is maximum 20 km. This is mainly related to the transportation cost of the harvested wood from the plantation sites to the plant. Grid connection The electricity generated from the plant is to be connected to PLN’s grid as local demand is lower than the generation. The connection from all sites is assumed as provided in the following table. Table 6.3. Candidate site of biomass power project Candidate site Possible connection to PLN’s grid Candidate site 1 Connected at 20 kV Candidate site 2 Connected at 20 kV Candidate site 3 Connected at 20 kV Candidate site 4 Connected at 20 kV Power plant operation

Remarks Distance: 50 km Distane: 15 km Distance: 12 km Distance: 5 km

The plant (biomass gasification plant) will be operated as base load taking advantage from lower fuel cost than fossil fuel based power plant. A load factor of 80% for a gasification power plant is

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commonly applicable. But, to be conservative a load factor of only about 77% for the biomass power plant in all candidate sites is assumed due to being the first (no experience for operating such a plant) in the Island. 6.7. Gasification Plant Configuration Feedstock Preparation Feedstock preparation is one of the most vital stages in ensuring production of desired quantity and quality of gas. Relatively dry and properly sized biomass is necessary for Gasification to be efficient. The moisture contents in all these feeds should be limited to 20% or lesser. The ideal diameter of feedstock is around 150‐75 mm. If the diameter is around 90 mm then they will need to be sliced at 25‐30 mm. Minimum dimensions of 15 mm, maximum dimensions of 75 mm. Fines below 3 mm should be sieved and removed. There should be no foreign matter like dust, dirt, fines, fibers, stones, debris, soil, oil, metal, plastic, glass etc. in the biomass. Gasification The gasifier is essentially a chemical reactor where various complex physical and chemical processes take place. Four distinct processes take place in a gasifier, namely drying of fuel, pyrolysis, combustion and reduction. Biomass is fed into gasifier at specified intervals. The equipment is designed in such a way that it takes in air in controlled quantities, resulting in partial oxidation of biomass into Producer gas. One kg of biomass gets converted into 2.5 to 3.0 Nm3 of gas with a calorific value of 1000‐1300 Kcal per Nm3, which would have the following composition: CO ‐ 21 ± 3% H2 ‐ 16 ± 4% CO2 ‐ 11 ± 3% CH4 ‐ 1 – 2.5% O2 ‐ 0.2 to 0.9% N2 – Rest Gas Cooling and Cleaning System The gas coming out of the gasifier is at a temperature of 450 degrees centigrade or greater. The hot gas, generally contains almost no tar and some amount of fine particles of ash and soot. Depending on the application, the temperature of the gas may need to be brought down to around ambient temperature. At the same time, the ash and the tar (if this is generated at all) need to be handled. The system used for cooling and cleaning the gas coming out from gasifiers is explained below:

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₋

Tar Cracking in the Gasifier

Gasifiers have been specially designed with proper throat size and throat nozzle geometry to ensure almost complete tar cracking in the gasifier itself. Thus, the hot gas leaving the gasifier is generally tar‐free over the operating range of the gasifier. ₋

Dry Gas cleaning system

The dry gas cleaning system essentially cools the gas using a heat exchanger. Then the gas is passed through a fabric filter. The fabric filter removes the particulates and the tars from the gas. The gas is then further cooled. After this the gas passes through a saw dust filter and a pleated cartridge filter. The gas is then very clean and ready for use in an Engine Genset. Advantages of dry gas cleaning system: o

No direct contact of water with gas for cooling

o

Hot air generated in gas cooler during cooling of gas can be used for drying of biomass

o

Both particulates and tar are removed in fabric filter are in dry form and hence their handling becomes easier

o

Reduction in size of fine filters

o

Less space required for installation

o

Low captive power required compared to wet filtration

₋

Fine Filtering System

These are saw dust filters that remove the particulates and the tars. Two or more of these filters are used in series. The gas after these filters is almost as clean as ambient air. The saw dust used in these filters is of a certain quality and is to be changed periodically. The used saw dust can be re‐used in the gasifier. ₋

Check Filter

A pleated cartridge filter is used to ensure that coagulated particulates are arrested at this point. The gas coming out of the check filter would generally have total tar and particulate level of less than 5 mg per Nm3 of gas. This level of cleanliness also allows gasifiers to be easily connected to turbo charged and/or after‐cooled engines.

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Kind of Construction The gasifier shed will be of Reinforced Cement Concrete (RCC) construction with structural steel truss and Galvanized Corrugated (GC) roof sheeting. The engine room will need to be enclosed with acoustics as required as per local regulations.

Figure 6.1. System Schematic and Technical Specifications for the Gasifier 6.8. Identified a potential local company or community which can operate and maintain the plant in the long‐term For the energy plantation in Sumba, PT Usaha Tani Lestari already prepares for the plantation implementation. Based on the communication during the site survey to PT Usaha Tani Lestari, the company has been requested by Forestry Ministry to support 1 MW Biomass power planned by EBTKE‐ESDM. However, there has been no discussion with EBTKE regarding to this biomass power program in Sumba. It is assumed that PT Usaha Tani Lestari shall manage Lamtoro Gung plantation and supply wood chip to the proposed power plant and together operate and maintain the plant in the long‐term.

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7. FINANCIAL ANALYSIS 7.1 Required Funds 7.1.1. Basic Condition Calculation 7.1.1.1. Currency The cost for year 2015, one of the conditions for financial analysis, was estimated based on the cost data in 2014. The basic curency used in the calculation is US dollar. Indonesia Rp is US $1=Rp 13,000. 7.1.1.2 Sales Plan Total sales amounts of power per annum Total Sales amounts per annum (kWh) = (Net output‐Auxiliary consumption) X 24hours X 365 days X Availability = (1200‐144)kW x 24 X 365 X 0.9 = 8,363,520 kWh/year Candidate site Candidate site 1 Candidate site 2 Candidate site 3 Candidate site 4

Gross Production 9,504,000 9,504,000 9,504,000 9,504,000

Sales Plan (kWh) 8,363,520 8,363,520 8,363,520 8,363,520

7.1.1.3 Required number of employees Types of jobs and personnel required to operate and manage the gasification plant are shown below. Since the plant is to be operated 24 hours a day. The personnel deployment in three shifts is adopted in plan, with a crew of one shift, out of three, set aside for reserve. Table 7.1. Manpower requirement Type of Man power

Qualifications required

Total number

Work responsibility

Plant In charge

An experienced Technical or Commercial person

1

To overall monitor the working of the plant and who can drive the performance of the plant.

Accounts / Administration personnel

Should possess Strong Accounting and Adminstration background and experience

1

For monitoring of incoming biomass, record keeping, accounting, billing of power evacuated etc.

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Plant Supervisors (Diploma level)

Labours

Mechanical Engineer

1 per shift

To monitor the plant performance and get things done as needed. Biomass preprocessing, conveying, gasifier and its accessories, charcoal / char disposal systematically etc

Electrical Engineer

1 per shift

To monitor the performance of the engines, evacuation systems etc.

Skilled labours

2‐4 per shift

1 for biomass pre‐processing and conveying and the 2nd person for Gasifier and Engine maintenance.

Unskilled labours

2‐4 per shift

Helping the above skilled labours and Supervisor for biomass pre‐processing, conveying / feeding, char removal and disposal and then as needed for Gasifier & Engine maintenance.

Total of US$ 117,333 will be appropriated every year for labour cost as follows: 1 Plant In charge, 1 person @ Rp 7.5 million x 16 month 2 Plant Supervisors, 1 per shift mechanical & 1 per shift electrical Administration personnel, 1 person, @Rp 7 million x16 3 month/year 4 Labours (skilled) 3 person per shift 5 Labours (unskilled) 3 person per shift Total

10,000 32,000 9,333 36,000 30,000 117,333

7.1.2. Total Required Funds Expenses for each project candidate are calculated based on offer data. The detailed costs for project implementation will consider engineering capability, shipment and current fabrication of Indonesian industries. In order to reduce the investment cost an inclusion of local content has been considered in the calculation. The cost estimation of power plant facilities for all four conditions as set above is shown in Table 7.2. The total required funds are as follows:

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Table 7.2 Project Cost Structure 1 MWe Biomass Power Plant

No

Plant Item/Description

1 Detail Design & Engineering Charges Biomass Sizing & Conveying System, Biomass Drying 3 Skip‐Charger Biomass Gasifier along with basic accessories and auxiliaries with Dry 4 Gas Filtration System Dry Gas Filtration System Flare system 2

5 Gasifier Cooling Tower 6 Condensate Neutralization System 7 52 TR Chiller

Quantit y Lump Sum Lump Sum 2 Nos.

2 Sets.

Lump Sum Lump Sum Lump Sum

Basic Price in USD Site 2

Site 1 52,195

Site 3

52,195

Site 4

52,195

52,195

125,000 125,000 125,000

125,000

43,510

43,510

43,510

43,510

1,042,460

1,042,4 60

1,042,4 60

1,042,46 0

26,320

26,320

26,320

26,320

48,430

48,430

48,430

48,430

95,940

95,940

95,940

95,940

732,475

Producer Gas Engine & Other Related 8 Accessories

5 Nos.

9 Radiator for Engine Cooling

Lump Sum

Sub Total

10 Packing & Transportation Charges Packing Charges 111,607 @ 5% of order value FOB Basis (Containers for stuffing needs to be provided by client at their 15,000 cost) Transportation cost (ocean freight, trucking to export harbour of Surabaya export documents, ISPM#15 certificate, certificate of origin, bill of loading, document courier fee. Add to 88,800 each shipment a fumigation fee of $60 and insurance of 2.5% of shipping value, transportation Surabaya to location, Sumba) 12 Startup Power For The System Installation and Civil & foundation 13 work 14 Grid Interconnection

732,475 732,475 732,475 (5 x (5 x (5 x (5 x 146,495 146,495 146,495) 146,495) ) ) 65,800

65,800

65,800

65,800

2,232,1 30

2,232,1 30

2,232,13 0

215,407

215,407

215,407

40,000

40,000

40,000

166,667 166,667 166,667

166,667

1,500,000 450,000 360,000

150,000

2,232,130

215,407

40,000

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15 Building

Total

Contingency (4%)

Total Plant Cost

100,000 100,000 100,000 100,000 3,204,2 3,114,2 2,904,20 4,254,204 04 04 4 170,168 128,168 124,568 116,168 3,332,3 3,238,7 3,020,37 4,424,372 72 72 2

7.2

Financial Evaluation

7.2.1. Assumptions for Financial Evaluation The project is expected to take 11 months for construction. The duration for operation is assumed to be 20 years. The financial analysis is conducted in real term without the general price inflation included. The electricity feed‐in tariff is Rp1840/kWh that was specified in the Ministerial regulation No.27/2014 on small and medium scale power generation from biomass and biogas. Indonesian current electricity tariff for medium voltage is IDR 1150 / kWh x F (=IDR 1840/kWh) or US$0.142/kWh. Biomass price for the financial analysis is 40 US$/ton (moisture content max 20%). The major technical and financial assumptions are listed in Table 7.3. Table 7.3 Assumptions for Financial Evaluation Expected Rate of Return on Investment (discount factor) Inflation (long term) Loan Tenor (years, excluding grace period)) Years of depreciation and amortization Investment Life Time (years) Portion of long-term debt/bank loans Equity Capacity 1200 kW Auxiliary power Annual gross Output (See technical explanation) Annual net Output (See technical explanation) Operation (24 h/d) Operation day (330 d/y) Operational hour/year Unit Price of Sales (US$/kWh, refer to indication) Insurance Water requirement /year (m3/y) Water price (Rp/m3) Borrowing Interest Rate p.a. Income tax rate Exchange Rate USD/Rp

16.00% 5% 8 20 20 70% 30% 1,200 144 9,504,000 8,363,520 24 330 7,920 0.142 0.50% 18,532.800 2,500.000 8.00% 25.00% 13,000

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7.2.2 Results of Financial Evaluation A discounted cashflow analysis was carried out to the base cases of the four identified sites to calculate an internal rate of return on equity investments. The resulted IRR is then compared with the expected rate of return on equity investment to determine the project’s financial viability. The assumed nominal expected rate of return is 16%. After deducting the inflation factor the real expected rate of return for equity capital is 10.5%. The analytical results are shown on Table 7.4. It is obvious that except Site 1 the other three sites are financially acceptable in their base cases. Table 7.4 Financial Analysis Results Option

Site 1

Site 2

Site 3

Site 4

Threshhold

IRR (%)

9.33

14.73

15.35

16.94

10.50

14

11

11

10

n.a.

Payback Period (year)

The above discounted cash flow analysis uses pre‐determined assumptions without taking into account uncertainties that may deviate the project away from the expected result. To test the robustness of the results of the financial model in presence of uncertainty, sensitivity analysis is executed to Site 4, which has got the highest IRR, in order to envisage how the variability in the outputs can be apportioned to different sources of uncertainty in its key inputs, including power tariff, capital cost, variable operating expense, cost of capital, loan interest rate and capacity utilization. Only adverse changes are considered. Two sensitivity test indicators are applied, namely, the sensitivity indicator (SI) – the ratio of the % change in the NPV to the % change in a variable, and the switching value – % change required in a variable for the NPV to become zero. Table 7.5 ranks the key variables in sequence of their sensitivities to the NPV. The result indicates that the most sensitive factors or the most influential elements to the project’s financial viability are the electricity tariff and the net power output. The operating cost and the cost of equity capital rank the second and third. Interestingly the capital cost ranks the second from the bottom, indicating the capital cost does not play a critcial role. For the sake of comparison, the SI for the capital cost being standardized to be 1 is taken as a benchmark. The SI for the tariff and net output are standardized to be 7.23 and the SI for the operating cost and cost of equity are standardized as 4.22 and 1.69. It means that the sensitivities of the tariff and the net output are 7.23 times that of the capital cost. Even the sensivity of the

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operating cost is 4.22 times that of the capital cost. The cost of debt is the least sensitive factor to the project sustainability. The SV results illustrate that the limit for the tariff and net output to be lowered is 9.3%. Any reduction below that limit will cause the project infeasible. The project will become unsound when the opearating cost increases by 16% and the capital cost increases by 67% from the base case level. Table 7.5 Sensitivity Test on NPV of Site 4 Variables Change FNPV SI* SV**(%) Normalized SI Base case 531,643.00 Decline in electricity tariff -10% (42,354.00) 10.80 9.26 7.23 Decrease in net output -10% (42,354.00) 10.80 9.26 7.23 Increase in operating cost 10% 196,805.00 (6.30) (15.88) 4.22 Increase in cost of equity 10% 397,227.00 (2.53) (39.55) 1.69 Increase in capital cost 10% 452,258.00 (1.49) (66.97) 1.00 Increase in lending rate 10% 508,090.00 (0.44) (225.72) 0.30 * SI -- Sensitivity indicator. The ratio of the % change in the FNPV to the % change in a variable. ** SV -- Switching value. It shows % change required in a variable for the FNPV to become zero.

7.2.3 Conclusion on Financial Analysis Four potential project sites have been identified where the only difference is in the connection distances between the sites and the power grid. The capital costs among the four are, therefore, differentiated. The financial analysis concluded that Site 4 is the most feasible option which has the highest IRR. Site 1 has to be dropped down as its rate of return is below the threshhold. Equity investors can earn a return on investment higher than the general market return. The sensitivity analysis indicates that the electricity tariff and the net power output are the most critical factors to determine the project’s financial viability. While the production output is subject to the market demand and the power plant operation management, the tariff will be controlled by the government. To let the biomass power project play a demonstration part for renewable energy development in the country, the government shall be responsible for keeping the tariff in favour of the project.

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8. CONCLUSION 8.1 Study findings and conclusion The main findings concerning the biomass project project in Sumba are summarized below. Table 8.1‐1 Results of pre‐feasibility study of the biomass project project. Peak Capacity (kW)‐gross Peak Capacity (kW)‐net Continuous duty‐gross (kW) Continuous duty‐net (kW) Gasifier Type Electricity to the grid (kWh) Electricity produce (gross)‐kWh Biomass consumption (t/y)‐ 20%MC Biomass consumption (t/y)‐Dry Base Biomass consumption (t/y) ‐ 40%MC Parasitic load (kW) Environment Baseline GHG reduction (tCO2e/y) Energy substitution effect (liter diesel oil/yr) Cost Initial performance investment (US$) IRR (%) Investment payback period (Year)

Site 1

Site 2 Site 3 Site 4 1200 1200 1200 1200 1056 1056 1056 1056 1020 1020 1020 1020 898 898 898 898 Down Draft Down Draft Down Draft Down Draft 8,363,520 8,363,520 8,363,520 8,363,520 9,504,000 9,504,000 9,504,000 9,504,000 11,310

11,310

11,310

11,310

9,048

9,048

9,048

9,048

15,080 15,080 15,080 15,080 144 144 144 144 Diesel PP Diesel PP Diesel PP Diesel PP 2,480 2,755 2,761 2,767 1,777,248

1,777,248

1,777,248

1,777,248

4,424,372

3,332,372

3,238,772

3,020,372

9.33

14.73 11

15.35 11

16.94 10

14

The equity capital’s internal rate of return (IRR) of the biomass power project for each of the potential locations, except Site 1, was found to be above the threshhold discount rateover 20 years. The project is thought attractive to private investors given that the assumed power tariff of US$14.2 cents/kWh (1840 rupiah/kWh) shall be kept up and be changing along with the inflation. Concrete investigation of the project in the future will require the cooperation of the government of Sumba (Sumba Barat, Sumba Tengah, and Sumba Timur), which is responsible for the administration of forest energy plantation, and the PLN (Indonesia’s state‐owned electricity company), which aims to provide stable supplies of electricity.

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8.2. Pre‐Feasibility Study Discussion A full feasibility study was not undertaken for this site as the preliminary assessment of the utility market and potential resources demonstrated that a biomass power facility had reasonable financial viability. If the project merited further study, additional work would need to be performed to verify project parameters used in the technical and economic analyses. The key economic drivers for this type of project are the feedstock availability and cost, and the price for the sale of electric. Assessing the biomass resource in the Sumba area can be done on a preliminary basis utilizing calculation tools. In order to verify these assumptions, further scrutiny is required that typically consists of a combination of site visits and demo plant to potential suppliers of the biomass. Collaboration with government entities like the Indonesian Ministry of Forestry would be done also. The market for wood has not yet formed in Sumba and setting up the chain of supply is very important. The chain of supply includes the long‐term supplier, processing, and delivery and storage issues. If the biomass power project was likely or had more favorable conditions, the pre‐feasibility study could be used to engage in discussions with utilities. Long‐term agreements would be discussed and evaluated with utilities to ascertain their level of interest and willingness to engage in a PPA. If part of the biomass power plant revenue is from energy sales (for example: biomass briquette), a long‐ term contract should be negotiated on a preliminary basis with the energy customer as well. The long‐term stability of the customer will also be a factor for lenders when conducting financial modeling for the project. Additional work for a full study would also include a heat and mass balance to verify the actual energy production, internal energy usage, and biomass feedstock required. Once this is accomplished, the equipment sizing can be deduced and an equipment cost estimate can be generated. This cost would be combined with the costs for construction, utilities and facility operation and maintenance for inclusion into an economic pro forma that evaluates the viability of the project. Other issues are also investigated, including permitting requirements, potential financing options, and local issues such as job creation and community involvement during the project progression.

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ATTACHMENT I

Emission Reduction from Biomass Power Project in Sumba Timur Regency (site 1) 1 MW Biomass Gasification 1. Application of a baseline methodology Title and reference of the approved baseline and monitoring methodology applied to the project: Methodology AM0042: Grid‐connected electricity generation using biomass from newly developed dedicated plantations (version 02.1, sector scope:01 and 14, EB 55) The methodology also referes to: 1. Tool for demonstration and evaluation of additionality. Version 07.0.0, EB 70. 2. Tool to calculate the emission factor of an electric system. Version 04.0, EB 75. Reference UNFCCC Website: http://cdm.unfccc.int/methodologies/PAmethodologies/approved.html Methodological tool “Tool for the demonstration and assessment of additionality”, Version 07.0.0, EB 70. Methodological tool “Tool to calculate the emission factor for an electricity system” – Version 04.0 , EB 75 Applicability of the methodology to be confirmed: The land area where the dedicated plantation will be established is, prior to project implementation, severely degraded and in absence of the project activity would have not been used for any other agricultural or forestry activity. The land degradation can be demonstrated using one or more of the following indicators: (a) Vegetation degradation, e.g., crown cover of pre‐existing trees has decreased in the recent past for reasons other than sustainable harvesting activities; (b) Soil degradation, e.g., soil erosion has increased in the recent past; soil organic matter content has decreased in the recent past. (c) Anthropogenic influences, e.g., there is a recent history of loss of soil and vegetation due to anthropogenic actions; and demonstration that there exist anthropogenic actions/activities that prevent possible occurrence of natural regeneration. Important ₋ Prior to the implementation of the project, no power was generated at the project site (i.e. the project plant does not substitute or affect the operation conditions of any existing power generation at the project site); under which ₋ The dedicated plantation must be newly established as part of the project the for the purpose of supplying biomass exclusively to the project; methodology ₋ The biomass from the plantation is not chemically processed (e.g. no

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is applicable

Baseline Scenario

production of alcohols from biomass, etc.) prior to combustion in the project plant but it may be processed mechanically or be dried; ₋ Grazing or irrigation for the plantation is not allowed; ₋ The land area where the dedicated plantation will be established has not been used for any agricultural or forestry activity prior to the project implementation. Electricity produced by more‐GHG‐intensive power plants connected to the grid.

Carbon dioxide

Fossil fuel

Grid

Electricity

Electricity

Project Scenario

Electricity produced by a grid‐connected biomass power plant.

Carbon dioxide

Grid

Fossil fuel

Electricity

Plantation

Biomass

Electricity

Renewable

2. Project Boundary According to ACM0042 methodology, the geographic extension of the project must include the entire extension of the project activity, including the power generation plant and the geographic extension of the dedicated plantation. Besides, the project limit is extended to include the emissions from the transportation of biomass up to the generation plant. The project limit also includes the generation plant connected to the electric system to which the project activity is connected. Table 2 summarizes the gases and sources included in the border of the project and presents an explanation and justification where the gases and sources are not included.

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Table 2 – Summary of gases. Source

Gases

Included?

Justification / Explanation

CO2

Included

Main source of emission.

CH4

Excluded

Excluded for simplification. This is conservative

N2O

Excluded


Source

Gases

Included?

Justification / Explanation

Consumption of auxiliary fuel and electricity generation process;

CO2

Excluded

Not applicable

CH4

Excluded

Not applicable

N2O

Excluded

Not applicable

CO2

Excluded

CO2 emissions from biomass burning are assumed not lead to changes in carbon pools

CH4

Included


N2O

Excluded


CO2

Included


CH4

Excluded


N2O

Excluded


CO2

Excluded

Not applicable

CH4

Excluded

Not applicable

N2O

Excluded

Not applicable

Fuel consumption in agriculture CO2 operations; CH4

Included


Excluded


N2O

Excluded


Baseline

CO2 emissions from the operation of the grid;

Project Activity

Combustion of biomass for electricity;

Off‐site fossil fuel combustion for transportation of biomass to the Project plant;

Electricity consumption at the project site

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Fertilizer production;

3.

CO2

Included


CH4

Included


N2O

Included


Fertilizer application;

N2O

Included


Field burning of biomass;

CO2

Excluded

Not applicable

CH4

Excluded

Not applicable

N2O

Excluded

Not applicable

Data and Parameters

Installed capacity 1200 kW Efficiency of gasification system 85% (net) Net electrical output ‐ 1056 kWe Annual operation time 7920 hours/year Load factor ‐ 77 % Start‐up Parasitic load ‐ 12 % Electricity to grid ‐ 8,364 MWh/year Biomass feedstock: Lamtoro Gung wood Annual quantity – 15,080 tonnes 20 km Average distance to site Load per truck 5 tonnes wood 4. Baseline emissions Baseline emissions are CO2 emissions from the displacement of electricity generation in grid‐ connected fossil fuel fired power plants. Baseline emissions are calculated as follows:

BEy

EGPJ , y EFgrid , y

(1)

Where: BEy = Baseline emissions in year y (tCO2/yr) EGPJ,y = Net quantity of electricity generated in the project plant in the year y (MWh/yr) EFgrid,y = Grid emission factor in year y, monitored and calculated according to the latest approved version of the “Tool to calculate the emission factor for an electricity system” (tCO2/MWh)

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5.

Project Emission PEy =PEFC,on−site,y + PEEC,y + PETP, y + PEBF ,y + PEFC,PL, y + PEFP, y + PEFA, y + PEBB, y Where: PEy = Project emissions in year y (tCO2/yr) PEFC,on‐site,y = Project emissions in year y from co‐firing fossil fuels in the project plant and/or from other fossil fuel combustion that occurs at the site of the project plant and that is attributable to the project activity (tCO2/yr) PEEC,y = Project emissions from electricity consumption at the site of the project plant that is attributable to the project activity (e.g. for mechanical processing of the biomass) in year y (tCO2/yr) PETP,y = Project emissions related to transportation of the biomass from the dedicated project plantation and/or biomass residues to the power plant in year y (tCO2/yr) PEBF,y = Project emissions from combustion of the renewable biomass from the dedicated project plantation and biomass residues in the project plant in year y (tCO2e/yr) = Project emissions related to fossil fuel consumption at the plantation during agricultural PEFC,PL,y operations in year y (tCO2/yr) PEFP,y = Project emissions related to the production of synthetic fertilizer that is used at the dedicated plantation in year y (tCO2e/yr) = Project emissions related to the application of fertilizers at the plantation in year y PEFA,y (tCO2e/yr) PEBB,y = Project emissions arising from field burning of biomass at the plantation site (tCO2e/yr) a) CO2 emissions from fuel combustion (PEFC,on‐site,y) This emission source should include CO2 emissions from all fuel consumption that occurs at the site of the project plant and that is attributable to the project activity. This includes: • Fossil fuels consumed with the renewable biomass from the dedicated plantation in the generation plant; • Other biomasses consumed with the renewable biomass from the dedicated plantation in the generation plant; • Fuels consumed in the mechanical preparation of the biomass or biomass drying process. The CO2 emissions due to the burning of biomass, must not be included. The emissions is calculated as follows:

PEFC , on

FCon

site , y

site , i , y

NCVi EFCO 2, FF ,i

(1)

i

Where: PEFC,on‐site,y

= Project emissions in year y from co‐firing fossil fuels in the project plant and/or from other fossil fuel combustion that occurs at the site of the project plant and that is attributable to the project activity (tCO2/yr)

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FCon‐site,i,y

NCVi EFCO2,FF,i i

= Amount fuel type i that is (a) co‐fired in the project plant and/or is (b) combusted at the site of the project plant and attributable to the project activity, during the year y (mass or volume unit)58 = Net calorific value of fuel type i (GJ / mass or volume unit) = CO2 emission factor of fuel type i (tCO2/GJ) = Fossil fuels or biomass fuel types other than the biomass from the dedicated plantation or biomass residues

b) CO2 emissions from on‐site electricity consumption (PEEC,y) CO2 emissions from on‐site electricity consumption (PEEC,y) are calculated by multiplying the electricity consumption by an appropriate grid emission factor, as follows:

PEEC , y

ECPJ , y EFgrid , y

(2)

Where: PEEC,y

= Project emissions from electricity consumption at the site of the project plant that is attributable to the project activity (e.g. for mechanical processing of the biomass) in year y (tCO2/yr)

ECPJ,y

= On‐site electricity consumption attributable to the project activity during the year y (MWh)

EFgrid,y

= Grid emission factor in year y, monitored and calculated according to the latest approved version of “Tool to calculate the emission factor for an electricity system” (tCO2/MWh)

c) CO2 emissions from fossil fuel combustion due to transportation of biomass from the plantation site(s) to the site of the project plant (PETP,y) This emission source includes CO2 emissions from the transportation of biomass from the dedicated plantation site(s) and biomass residues from their source of generation to the project plant. Emissions may be calculated either based on information on the number of trips, the return trip distance and CO2 emission factors of the vehicles (Option 1) or based on data on the actual fuel consumption of vehicles (Option 2). Where the biomass is obtained from different sources with different distances and/or transported in different types of vehicles, emissions are calculated separately for the different distances and vehicles types.

58

Preferably use a mass unit for solid fuels and a volume unit for liquid and gaseous fuels.

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Option 1: Emissions are calculated on the basis of distance and the number of trips (or the average truck load):

PETP, y

N y AVDy EFkm,CO 2

(3)

or

BFPJ , j , y PETP , y

j

AVDy EFkm , CO 2, y

TLy

Where: PETP,y

(4)

= Project emissions related to transportation of the biomass from the dedicated project plantation and/or biomass residues from their source of generation to the power plant in year y (tCO2/yr) = Number of truck trips during the year y = Average return trip distance (from and to) between the source of the biomass and the site of the project plant during the year y (km), = Average CO2 emission factor for the trucks measured during the year y (tCO2/km) = Quantity of biomass type j fired in the project plant in the year y (tons of dry matter or liter)59 = Average truck load of the trucks used (tons or liter) = All types of renewable biomass from the dedicated project plantation and types of biomass residues that are fired in the project plant

Ny AVDy EFkm,CO2,y BFPJ,j,y TLy j Option 2:

Emissions are calculated based on the actual quantity of fossil fuels consumed for transportation.

PETP , y

FCTR , i , y NCVi EFCO 2, FF ,i

(5)

i

Where: PECO2,TR,y FCTR,i,y

= CO2 emissions from off‐site transportation of biomass residues to the project site (tCO2/yr) = Fuel consumption of fuel type i used in trucks for transportation of biomass during the year y (mass or volume unit)58 = Net calorific value of fuel type i (GJ / mass or volume unit) = CO2 emission factor for fossil fuel type i (tCO2/GJ)

NCVi EFCO2,FF,i d) CH4 emissions from combustion of biomass (PEBF,y) CH4 emissions are associated with the combustion of biomass fired in the project plant. This is calculated as follows:

PEBF , y

GWPCH 4

BFPJ , j , y NCV j EFCH 4, BF , j

(6)

j

59

Use tons of dry matter for solid biomass residues and liter for liquid biomass residues.

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Where: PEBF,y

= Project emissions from combustion of the renewable biomass from the dedicated project plantation and biomass residues in the project plant in year y (tCO2e/yr) = Global Warming Potential of methane valid for the commitment period (tCO2e/tCH4) = Quantity of biomass type j fired in the project plant in the year y (tons of dry matter or liter)59 = Net calorific value of biomass fuel type j (GJ/ton of dry matter or GJ/liter) = CH4 emission factor for the combustion of biomass type j in the project plant (tCH4/GJ) = All types of renewable biomass from the dedicated project plantation and types of biomass residues that are fired in the project plant

GWPCH4 BFPJ,j,y NCVj EFCH4,BF,j j

To determine the CH4 emission factor, IPCC default values are used, as provided in Table 2 of the methodology adopted, the default CH4 emission factor of 30 kg/TJ from Table 2 is used, for which the uncertainty is estimated to be 300%, and the conservativeness factor for the uncertainty is 1.37 (from Table 3 of the methodology adopted). Thus, in this case a CH4 emission factor of (30*1.37= ) 41.1 kg/TJ is used. e) CO2 emissions from fossil fuel consumption during agricultural operations (PEFC,PL,y) CO2 emissions associated with fossil fuel consumption at the plantation are calculated as follows:

PE FC,PL ,y

FCPL ,i ,y NCVi EFCO2 ,FF,i

(7)

i

Where: PEFC,PL,y

= Project emissions related to fossil fuel consumption at the plantation during agricultural operations in year y (tCO2/yr) = Amount of fuel type i that is combusted at the dedicated plantation during the year y (mass or volume unit)58 = Net calorific value of fuel type i (GJ / mass or volume unit) = CO2 emission factor of fuel type i (tCO2/GJ) = Fuel types used for combustion at the dedicated plantation

FCPL,i,y

NCVi EFCO2,FF,i i f) Emissions from the production of synthetic fertilizer that is used at the plantation (PEFP,y) The GHG emissions from the production of synthetic fertilizer are estimated for each synthetic fertilizer type f by multiplying an emission factor with the monitored quantity of fertilizer applied at the plantation during the year y, as follows:

PE FP , y

EFCO 2 e , FP , f FSF , f , y

(8)

f

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Where: PEFP,y

= Project emissions related to the production of synthetic fertilizer that is used at the dedicated plantation in year y (tCO2e/yr) = Emission factor for GHG emissions associated with the production of fertilizer type f (tCO2e/kg fertilizer) = Amount of synthetic fertilizer of type f applied in year y (kg fertilizer/yr) = Types of synthetic fertilizers applied at the dedicated plantation

EFCO2e,FP,f

FSF,f,y f g) N2O emissions from application of fertilizers at the plantation (PEFA,y) N2O emissions are associated with the application of both organic and synthetic fertilizers, and are emitted through direct soil emissions and indirect emissions from atmospheric deposition and leaching and run‐off. Emissions are calculated as follows.

PEFA, y

GWPN 2O

Where: PEFA,y GWPN2O PEN2O‐N,dir,y PEN2O‐N,ind,y

44 PEN 2O 28

N , dir , y

PEN 2O

N , ind , y

(9)

= Project emissions related to the application of fertilizers at the dedicated plantation in year y (tCO2e/yr) = Global Warming Potential of nitrous oxide valid for the commitment period (tCO2e/tN2O) = Direct N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Indirect N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr)

Direct soil N2O emissions

PEN 2O

N , dir , y

Where: PEN2O‐N,dir,y EFN2O‐N,dir FON,y FSN,y

EFN 2O

N , dir

FON , y

FSN , y

(10)

= Direct N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Emission factor for direct nitrous oxide emissions from N inputs (kg N2O‐N/kg N) = Amount of organic fertilizer nitrogen from animal manure, sewage, compost or other organic amendments applied at the dedicated plantation during the year y (t N/yr) = Amount of synthetic fertilizer nitrogen applied at the dedicated plantation during the year y (t N/yr)

Indirect N2O emissions Note: This source of emission is not to be accounted for in the case of a woody plantation.

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Indirect N2O emissions comprise N2O emissions due to atmospheric decomposition of N volatilized from the plantation and N2O emissions from leaching/run‐off:

PEN 2O

N , ind , y

PEN 2O

Where: PEN2O‐N,ind,y PEN2O‐N,ind,ATD,y PEN2O‐N,ind,L,y

N , ind , ATD, y

PEN 2O

N , ind , L , y

(11)

= Indirect N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Indirect N2O‐N emissions due to atmospheric deposition of volatilized N, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Indirect N2O‐N emissions due to leaching/run‐off, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr)

Indirect N2O emissions due to atmospheric decomposition are calculated as follows:

PEN 2O

N , ind , ATD, y

Where: PEN2O‐N,ind,ATD,y FSN,y FracGASF FON,y FracGASM EFN2O‐N,ATD

FSN , y FracGASF

FON , y FracGASM EFN 2O

N , ATD

(12)

= Indirect N2O‐N emissions due to atmospheric deposition of volatilized N, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Amount of synthetic fertilizer nitrogen applied at the dedicated plantation during the year y (t N/yr) = Fraction of synthetic fertilizer N that volatilizes as NH3 and NOX (kg N volatilized / kg N applied) = Amount of organic fertilizer nitrogen from animal manure, sewage, compost or other organic amendments applied at the dedicated plantation during the year y (t N/yr) = Fraction of organic N fertilizer that volatilizes as NH3 and NOX (kg N volatilized / kg N applied) = Emission factor for atmospheric deposition of N on soils and water surfaces (t N2O‐N / t N volatilized)

Indirect N2O emissions due to leaching and runoff are calculated as follows:

PEN 2O

N , ind , L , y

Where: PEN2O‐N,ind,L,y FSN,y FON,y FracLEACH

FSN , y

FON , y FracLEACH EFN 2O

N,L

(13)

= Indirect N2O‐N emissions due to leaching/run‐off, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Amount of synthetic fertilizer nitrogen applied at the dedicated plantation during the year y (t N/yr) = Amount of organic fertilizer nitrogen from animal manure, sewage, compost or other organic amendments applied at the dedicated plantation during the year y (t N/yr) = Fraction of synthetic and organic fertilizer N that is lost through leaching and runoff (kg N leached and runoff / kg N applied)

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EFN2O‐N,L

= Emission factor for N2O emissions from N leaching and runoff (t N2O‐N / t N leached and runoff)

h) CH4 and N2O emissions from the field burning of biomass Biomass may be burnt at the start of the project activity (for land clearance) or regularly during the crediting period (e.g. after harvest). In these cases, CH4 and N2O emissions are calculated for each time that field burning is occurring, as follows:

PE BB,y

A B M B Cf EFN2O,BB GWPN2O

Where: PEBB,y AB MB Cf

= = = =

EFCH4,BB GWPCH4

(14)

Project emissions arising from field burning of biomass at the plantation site (tCO2e/yr) Area burned (ha) Average mass of biomass available for burning on the area (t dry matter/ha) Combustion factor, accounting for the proportion of fuel that is actually burnt (dimensionless) N2O emission factor for field burning of biomass (tN2O/tonne of dry matter) Global Warming Potential of nitrous oxide valid for the commitment period (tCO2e/tN2O) CH4 emission factor for field burning of biomass (tCH4/tonne of dry matter) Global Warming Potential of methane valid for the commitment period (tCO2e/tCH4)

EFN2O,BB = GWPN2O = EFCH4,BB = = GWPCH4 6. Leakage According to AM0042 methodology, potential source of leakage emission for this project activity is the emissions related to the consumption of fossil fuel or other sources due to the devertion of biomass residues from other uses to the project plant, as a result of the project activity. As the project activity does not use any residual biomass, there is no leakage emission. 7. Emission reduction The emission reductions (ERy) are calculated as:

ERy

BEy

Where: ERy BEy PEy LEy

PEy

= = = =

LEy

(15)

Emission reductions in year y (tCO2/yr) Baseline emissions in year y (tCO2/yr) Project emissions in year y (tCO2/yr) Leakage emissions in year y (tCO2/yr)

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8. Ex‐ante calculation of emission reductions Net Electricity Generation Gross electricity generation capacity MW

1.2

Net electricity generation capacity

MW

1.056

Load factor

%

77

Working hours/day

hours/day

24

Parasitic load

MW

0.144

Net annual electricity generation

8,364 MWh/yr

(EGPJ,y)

Baseline Emissions Parameters

Unit

Value

BEy

(tCO2/yr)

6,691

EGPJ,y

MWh/yr

8,364

EFgrid,y

(tCO2/MWh)

0.8

Project emissions The total of emissions of the project: PEy =PEFC,on−site,y + PEEC,y + PETP, y + PEBF ,y + PEFC,PL, y + PEFP, y + PEFA, y + PEBB, y a) CO2 emissions from fuel combustion (PEFC,on‐site,y)

Density of diesel

0.845 kg/liter

Calorific value of diesel

NCV

0.043 TJ/ton

CO2 emission factor of diesel

EFCO2,FF,i

74.8 tCO2/TJ

Quantity of diesel oil consumption

FCon‐site,i,y

0

Diesel Fuel consumption for mechanical preparation or drying of the biomass

0

PEFC , on

FCon

site , y

site , i , y

NCVi EFCO 2, FF ,i

i

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b) CO2 emissions from on‐site electricity consumption (PEEC,y)

PEEC , y

ECPJ , y EFgrid , y

There is no consumption of electricity from the distribution grid. PEEC,y = 0 c) CO2 emissions from fossil fuel combustion due to transportation of biomass from the plantation site(s) to the site of the project plant (PETP,y) Option 2:

PETP , y

FCTR , i , y NCVi EFCO 2, FF ,i i

Diesel oil consumption for transportation

FCTR,i,y

15.29 t/y

Density of diesel oil

0.845 kg/liter

Net calorific value of diesel oil

NCV

0.043 TJ/ton


EFCO2,FF,i

74.8 tCO2/TJ

PECO2,TR,y

49.5 tCO2/yr

d) CH4 emissions from combustion of biomass (PEBF,y)

PEBF , y

GWPCH 4

BFPJ , j , y NCV j EFCH 4, BF , j j

Global warming potential

GWPCH4

21

Quantity of Lamtoro Gung wood gasified

BFPJ,j,y

15,080 t/y

Net calorific value of Lamtoro Gung wood

NCVj

0,01923 TJ/ton

CH4 emission factor for the combustion of Lamtoro EFCH4,BF, Gung wood Project emission from combustion of lamtoro Gung PEBF,y wood

0.0411 tCH4/TJ

250.3 tCO2e/yr

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e) CO2 emissions from fossil fuel consumption during agricultural operations (PEFC,PL,y)

PE FC,PL ,y

FCPL ,i ,y NCVi EFCO2 ,FF,i i

Project emissions related to diesel consumption used at PEFC,PL,y the dedicated plantation Annual diesel consumption in the dedicated plantatation FCPL,i,y

13.0 tCO2/yr

Net calorific value of diesel

NCVi

0.0433 TJ/ton


EFCO2,FF,i

74.8 tCO2/TJ

4 ton/yr

f) Emissions from the production of synthetic fertilizer that is used at the plantation (PEFP,y)

PE FP , y

EFCO 2 e , FP , f FSF , f , y f

Emission factor for GHG emissions associated EFCO2e,FP,f with the production of fertilizer Annual quantity of fertilizer used FSF,f,y

6.2 tCO2/yr 3,015 t fertilizer/yr

Project emission related to the production of PEFP,y 6.2 tCO2/yr synthetic fertilizer g) N2O emissions from application of fertilizers at the plantation (PEFA,y)

PEFA, y

GWPN 2O

44 PEN 2O 28

N , dir , y

PEN 2O

N , ind , y

Global Warming Potential of nitrous oxide valid for the commitment period Annual direct N2O‐N emissions as a result of nitrogen application at the dedicated plantation Annual indirect N2O‐N emissions as a result of nitrogen application at the dedicated plantation

GWPN2O

310 tCO2e/tN2O

PEN2O‐N,dir,y

6 tN2O‐N/yr

PEN2O‐N,ind,y

2 tN2O‐N/yr


PEN 2O

N , dir , y

EFN 2O

N , dir

FON , y

FSN , y

Direct N2O‐N emissions as a result of nitrogen application at PEN2O‐N,dir,y the dedicated plantation

6 tN2O‐N/yr

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Emission factor for direct nitrous oxide emissions from N EFN2O‐N,dir inputs Amount of organic fertilizer nitrogen from animal manure, FON,y sewage, compost or other organic amendments applied at the dedicated plantation during Amount of synthetic fertilizer nitrogen applied at the FSN,y dedicated plantation h) CH4 and N2O emissions from the field burning of biomass

PE BB,y


0.01 kg N2O‐N / kg N 0 tN/yr

603 tN/yr

EFCH4,BB GWPCH4

There is no field burning of biomass PEBB,y 0 Leakage As the project activity does not use any residual biomass, there is no leakage emission (LEy=0) Emission reductions

ERy Parameter

BEy

PEy

LEy Unit

Value

ERy

tCO2e/yr

4,211

BEy

tCO2e/yr

6,691

PEy

tCO2e/yr

4,211

LEy

tCO2e/yr

0

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Emission Reduction from Biomass Power Project in Sumba Tengah Regency 1 MW Biomass Gasification 9. Application of a baseline methodology Title and reference of the approved baseline and monitoring methodology applied to the project: Methodology AM0042: Grid‐connected electricity generation using biomass from newly developed dedicated plantations (version 02.1, sector scope:01 and 14, EB 55) The methodology also referes to: 1. Tool for demonstration and evaluation of additionality. Version 05.2, EB 39. 2. Tool to calculate the emission factor of an electric system. Version 01.0, EB35. Reference UNFCCC Website: http://cdm.unfccc.int/methodologies/PAmethodologies/approved.html Methodological tool “Tool for the demonstration and assessment of additionality”, Version 05.2, EB 39. Methodological tool “Tool to calculate the emission factor for an electricity system” – Version 01.1 , EB 35 Applicability of the methodology to be confirmed: The land area where the dedicated plantation will be established is, prior to project implementation, severely degraded and in absence of the project activity would have not been used for any otheragricultural or forestry activity. The land degradation can be demonstrated using one or more of the following indicators: (a) Vegetation degradation, e.g., crown cover of pre‐existing trees has decreased in the recent past for reasons other than sustainable harvesting activities; (b) Soil degradation, e.g., soil erosion has increased in the recent past; soil organic matter content has decreased in the recent past. (c) Anthropogenic influences, e.g., there is a recent history of loss of soil and vegetation due to anthropogenic actions; and demonstration that there exist anthropogenic actions/activities that prevent possible occurrence of natural regeneration. 10. Data and Parameters Installed capacity 1200 kW Efficiency of gasification system 85% (net) Net electrical output ‐ 1056 kWe Annual operation time 7920 hours/year Load factor ‐ 77 %

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Start‐up Parasitic load ‐ 12 % Electricity to grid ‐ 8,364 MWh/year Biomass feedstock: Lamtoro Gung wood Annual quantity – 15,080 tonnes Average distance to site 20 km Load per truck 5 tonnes wood 11. Baseline emissions Baseline emissions are CO2 emissions from the displacement of electricity generation in grid‐ connected fossil fuel fired power plants. Baseline emissions are calculated as follows:

BEy

EGPJ , y EFgrid , y

(1)

Where: BEy = Baseline emissions in year y (tCO2/yr) EGPJ,y = Net quantity of electricity generated in the project plant in the year y (MWh/yr) = Grid emission factor in year y, monitored and calculated according to the latest approved EFgrid,y version of the “Tool to calculate the emission factor for an electricity system” (tCO2/MWh) 12. Project Emission PEy =PEFC,on−site,y + PEEC,y + PETP, y + PEBF ,y + PEFC,PL, y + PEFP, y + PEFA, y + PEBB, y Where: PEy = Project emissions in year y (tCO2/yr) PEFC,on‐site,y = Project emissions in year y from co‐firing fossil fuels in the project plant and/or from other fossil fuel combustion that occurs at the site of the project plant and that is attributable to the project activity (tCO2/yr) PEEC,y = Project emissions from electricity consumption at the site of the project plant that is attributable to the project activity (e.g. for mechanical processing of the biomass) in year y (tCO2/yr) PETP,y = Project emissions related to transportation of the biomass from the dedicated project plantation and/or biomass residues to the power plant in year y (tCO2/yr) PEBF,y = Project emissions from combustion of the renewable biomass from the dedicated project plantation and biomass residues in the project plant in year y (tCO2e/yr) = Project emissions related to fossil fuel consumption at the plantation during agricultural PEFC,PL,y operations in year y (tCO2/yr) PEFP,y = Project emissions related to the production of synthetic fertilizer that is used at the dedicated plantation in year y (tCO2e/yr) PEFA,y = Project emissions related to the application of fertilizers at the plantation in year y (tCO2e/yr) = Project emissions arising from field burning of biomass at the plantation site (tCO2e/yr) PEBB,y

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a) CO2 emissions from fuel combustion (PEFC,on‐site,y) This emission source should include CO2 emissions from all fuel consumption that occurs at the site of the project plant and that is attributable to the project activity. This includes: • Fossil fuels consumed with the renewable biomass from the dedicated plantation in the generation plant; • Other biomasses consumed with the renewable biomass from the dedicated plantation in the generation plant; • Fuels consumed in the mechanical preparation of the biomass or biomass drying process. The CO2 emissions due to the burning of biomass, must not be included. The emissions is calculated as follows:

PEFC , on

FCon

site , y

site , i , y

NCVi EFCO 2, FF ,i

(17)

i

Where: PEFC,on‐site,y

FCon‐site,i,y

NCVi EFCO2,FF,i i

= Project emissions in year y from co‐firing fossil fuels in the project plant and/or from other fossil fuel combustion that occurs at the site of the project plant and that is attributable to the project activity (tCO2/yr) = Amount fuel type i that is (a) co‐fired in the project plant and/or is (b) combusted at the site of the project plant and attributable to the project activity, during the year y (mass or volume unit)60 = Net calorific value of fuel type i (GJ / mass or volume unit) = CO2 emission factor of fuel type i (tCO2/GJ) = Fossil fuels or biomass fuel types other than the biomass from the dedicated plantation or biomass residues

b) CO2 emissions from on‐site electricity consumption (PEEC,y) CO2 emissions from on‐site electricity consumption (PEEC,y) are calculated by multiplying the electricity consumption by an appropriate grid emission factor, as follows:

PEEC , y

ECPJ , y EFgrid , y

(18)

Where: PEEC,y

= Project emissions from electricity consumption at the site of the project plant that is attributable to the project activity (e.g. for mechanical processing of the biomass) in year y (tCO2/yr)

ECPJ,y

= On‐site electricity consumption attributable to the project activity during the year y (MWh)

60

Preferably use a mass unit for solid fuels and a volume unit for liquid and gaseous fuels.

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EFgrid,y

= Grid emission factor in year y, monitored and calculated according to the latest approved version of “Tool to calculate the emission factor for an electricity system” (tCO2/MWh)

c) CO2 emissions from fossil fuel combustion due to transportation of biomass from the plantation site(s) to the site of the project plant (PETP,y) This emission source includes CO2 emissions from the transportation of biomass from the dedicated plantation site(s) and biomass residues from their source of generation to the project plant. Emissions may be calculated either based on information on the number of trips, the return trip distance and CO2 emission factors of the vehicles (Option 1) or based on data on the actual fuel consumption of vehicles (Option 2). Where the biomass is obtained from different sources with different distances and/or transported in different types of vehicles, emissions are calculated separately for the different distances and vehicles types. Option 1: Emissions are calculated on the basis of distance and the number of trips (or the average truck load):

PETP, y

N y AVDy EFkm,CO 2

(19)

or

BFPJ , j , y PETP , y

j

TLy

Where: PETP,y

AVDy EFkm , CO 2, y

(20)

= Project emissions related to transportation of the biomass from the dedicated project plantation and/or biomass residues from their source of generation to the power plant in year y (tCO2/yr) = Number of truck trips during the year y = Average return trip distance (from and to) between the source of the biomass and the site of the project plant during the year y (km), = Average CO2 emission factor for the trucks measured during the year y (tCO2/km) = Quantity of biomass type j fired in the project plant in the year y (tons of dry matter or liter)61 = Average truck load of the trucks used (tons or liter) = All types of renewable biomass from the dedicated project plantation and types of biomass residues that are fired in the project plant

Ny AVDy EFkm,CO2,y BFPJ,j,y TLy j Option 2:

Emissions are calculated based on the actual quantity of fossil fuels consumed for transportation.

PETP , y

FCTR , i , y NCVi EFCO 2, FF ,i

(21)

i

61

Use tons of dry matter for solid biomass residues and liter for liquid biomass residues.

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Where: PECO2,TR,y FCTR,i,y

= CO2 emissions from off‐site transportation of biomass residues to the project site (tCO2/yr) = Fuel consumption of fuel type i used in trucks for transportation of biomass during the year y (mass or volume unit)58 = Net calorific value of fuel type i (GJ / mass or volume unit) = CO2 emission factor for fossil fuel type i (tCO2/GJ)

NCVi EFCO2,FF,i d) CH4 emissions from combustion of biomass (PEBF,y) CH4 emissions are associated with the combustion of biomass fired in the project plant. This is calculated as follows:

PEBF , y

GWPCH 4

BFPJ , j , y NCV j EFCH 4, BF , j

(22)

j

Where: PEBF,y GWPCH4 BFPJ,j,y NCVj EFCH4,BF,j j

= Project emissions from combustion of the renewable biomass from the dedicated project plantation and biomass residues in the project plant in year y (tCO2e/yr) = Global Warming Potential of methane valid for the commitment period (tCO2e/tCH4) = Quantity of biomass type j fired in the project plant in the year y (tons of dry matter or liter)59 = Net calorific value of biomass fuel type j (GJ/ton of dry matter or GJ/liter) = CH4 emission factor for the combustion of biomass type j in the project plant (tCH4/GJ) = All types of renewable biomass from the dedicated project plantation and types of biomass residues that are fired in the project plant

To determine the CH4 emission factor, IPCC default values are used, as provided in Table 2 of the methodology adopted, the default CH4 emission factor of 30 kg/TJ from Table 2 is used, for which the uncertainty is estimated to be 300%, and the conservativeness factor for the uncertainty is 1.37 (from Table 3 of the methodology adopted). Thus, in this case a CH4 emission factor of (30*1.37= ) 41.1 kg/TJ is used. e) CO2 emissions from fossil fuel consumption during agricultural operations (PEFC,PL,y) CO2 emissions associated with fossil fuel consumption at the plantation are calculated as follows:

PE FC,PL ,y

FCPL ,i ,y NCVi EFCO2 ,FF,i

(23)

i

Where: PEFC,PL,y FCPL,i,y NCVi EFCO2,FF,i i

= Project emissions related to fossil fuel consumption at the plantation during agricultural operations in year y (tCO2/yr) = Amount of fuel type i that is combusted at the dedicated plantation during the year y (mass or volume unit)58 = Net calorific value of fuel type i (GJ / mass or volume unit) = CO2 emission factor of fuel type i (tCO2/GJ) = Fuel types used for combustion at the dedicated plantation

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f) Emissions from the production of synthetic fertilizer that is used at the plantation (PEFP,y) The GHG emissions from the production of synthetic fertilizer are estimated for each synthetic fertilizer type f by multiplying an emission factor with the monitored quantity of fertilizer applied at the plantation during the year y, as follows:

PE FP , y

EFCO 2 e , FP , f FSF , f , y

(24)

f

Where: PEFP,y

= Project emissions related to the production of synthetic fertilizer that is used at the dedicated plantation in year y (tCO2e/yr) = Emission factor for GHG emissions associated with the production of fertilizer type f (tCO2e/kg fertilizer) = Amount of synthetic fertilizer of type f applied in year y (kg fertilizer/yr) = Types of synthetic fertilizers applied at the dedicated plantation

EFCO2e,FP,f

FSF,f,y f g) N2O emissions from application of fertilizers at the plantation (PEFA,y) N2O emissions are associated with the application of both organic and synthetic fertilizers, and are emitted through direct soil emissions and indirect emissions from atmospheric deposition and leaching and run‐off. Emissions are calculated as follows.

PEFA, y

GWPN 2O

Where: PEFA,y GWPN2O PEN2O‐N,dir,y PEN2O‐N,ind,y

44 PEN 2O 28

N , dir , y

PEN 2O

N , ind , y

(25)

= Project emissions related to the application of fertilizers at the dedicated plantation in year y (tCO2e/yr) = Global Warming Potential of nitrous oxide valid for the commitment period (tCO2e/tN2O) = Direct N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Indirect N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr)


PEN 2O

N , dir , y

Where: PEN2O‐N,dir,y

EFN 2O

N , dir

FON , y

FSN , y

(26)

= Direct N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr)

Page 92 of 396

EFN2O‐N,dir FON,y FSN,y

= Emission factor for direct nitrous oxide emissions from N inputs (kg N2O‐N/kg N) = Amount of organic fertilizer nitrogen from animal manure, sewage, compost or other organic amendments applied at the dedicated plantation during the year y (t N/yr) = Amount of synthetic fertilizer nitrogen applied at the dedicated plantation during the year y (t N/yr)

Indirect N2O emissions Note: This source of emission is not to be accounted for in the case of a woody plantation. Indirect N2O emissions comprise N2O emissions due to atmospheric decomposition of N volatilized from the plantation and N2O emissions from leaching/run‐off:

PEN 2O

N , ind , y

PEN 2O

Where: PEN2O‐N,ind,y PEN2O‐N,ind,ATD,y PEN2O‐N,ind,L,y

N , ind , ATD, y

PEN 2O

N , ind , L , y

(27)

= Indirect N2O‐N emissions as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Indirect N2O‐N emissions due to atmospheric deposition of volatilized N, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Indirect N2O‐N emissions due to leaching/run‐off, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr)

Indirect N2O emissions due to atmospheric decomposition are calculated as follows:

PEN 2O

N , ind , ATD, y

Where: PEN2O‐N,ind,ATD,y FSN,y FracGASF FON,y FracGASM EFN2O‐N,ATD

FSN , y FracGASF

FON , y FracGASM EFN 2O

N , ATD

(28)

= Indirect N2O‐N emissions due to atmospheric deposition of volatilized N, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr) = Amount of synthetic fertilizer nitrogen applied at the dedicated plantation during the year y (t N/yr) = Fraction of synthetic fertilizer N that volatilizes as NH3 and NOX (kg N volatilized / kg N applied) = Amount of organic fertilizer nitrogen from animal manure, sewage, compost or other organic amendments applied at the dedicated plantation during the year y (t N/yr) = Fraction of organic N fertilizer that volatilizes as NH3 and NOX (kg N volatilized / kg N applied) = Emission factor for atmospheric deposition of N on soils and water surfaces (t N2O‐N / t N volatilized)

Indirect N2O emissions due to leaching and runoff are calculated as follows:

PEN 2O

N , ind , L , y

Where: PEN2O‐N,ind,L,y

FSN , y

FON , y FracLEACH EFN 2O

N,L

(29)

= Indirect N2O‐N emissions due to leaching/run‐off, as a result of nitrogen application at the dedicated plantation during the year y (tN2O‐N/yr)

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FSN,y

= Amount of synthetic fertilizer nitrogen applied at the dedicated plantation during the year y (t N/yr) = Amount of organic fertilizer nitrogen from animal manure, sewage, compost or other organic amendments applied at the dedicated plantation during the year y (t N/yr) = Fraction of synthetic and organic fertilizer N that is lost through leaching and runoff (kg N leached and runoff / kg N applied) = Emission factor for N2O emissions from N leaching and runoff (t N2O‐N / t N leached and runoff)

FON,y FracLEACH EFN2O‐N,L

h) CH4 and N2O emissions from the field burning of biomass Biomass may be burnt at the start of the project activity (for land clearance) or regularly during the crediting period (e.g. after harvest). In these cases, CH4 and N2O emissions are calculated for each time that field burning is occurring, as follows:

PE BB,y


Where: PEBB,y AB MB Cf

= = = =

EFCH4,BB GWPCH4

(30)

Project emissions arising from field burning of biomass at the plantation site (tCO2e/yr) Area burned (ha) Average mass of biomass available for burning on the area (t dry matter/ha) Combustion factor, accounting for the proportion of fuel that is actually burnt (dimensionless) N2O emission factor for field burning of biomass (tN2O/tonne of dry matter) Global Warming Potential of nitrous oxide valid for the commitment period (tCO2e/tN2O) CH4 emission factor for field burning of biomass (tCH4/tonne of dry matter) Global Warming Potential of methane valid for the commitment period (tCO2e/tCH4)

EFN2O,BB = = GWPN2O EFCH4,BB = = GWPCH4 13. Leakage According to AM0042 methodology, potential source of leakage emission for this project activity is the emissions related to the consumption of fossil fuel or other sources due to the devertion of biomass residues from other uses to the project plant, as a result of the project activity. As the project activity does not use any residual biomass, there is no leakage emission. 14. Emission reduction The emission reductions (ERy) are calculated as:

ERy

BEy

Where: ERy BEy

PEy

LEy

(31)

= Emission reductions in year y (tCO2/yr) = Baseline emissions in year y (tCO2/yr)

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PEy LEy

= Project emissions in year y (tCO2/yr) = Leakage emissions in year y (tCO2/yr)

15. Ex‐ante calculation of emission reductions Net Electricity Generation Gross electricity generation capacity 1 MW

Net electricity generation capacity

MW

Load factor

%

Working hours/day

hours/day

Parasitic load

MW

Net annual electricity generation

.........MWh/year (EGPJ,y)

Net steam output

TJ/year

Baseline Emissions Parameters

Unit

Value

BEy

(tCO2/yr)

EGPJ,y

MWh/yr

EFgrid,y

(tCO2/MWh)

Project emissions The total of emissions of the project: PEy =PEFC,on−site,y + PEEC,y + PETP, y + PEBF ,y + PEFC,PL, y + PEFP, y + PEFA, y + PEBB, y a) CO2 emissions from fuel combustion (PEFC,on‐site,y)

Density of diesel

.......................

Calorific value of diesel

NCV

.......................


EFCO2,FF,i

.......................

Diesel Fuel consumption for mechanical preparation or drying of the biomass

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Quantity of diesel oil consumption

FCon‐site,i,y

.......................

.......................

PEFC , on

FCon

site , y

site , i , y

NCVi EFCO 2, FF ,i

i

b) CO2 emissions from on‐site electricity consumption (PEEC,y)

PEEC , y

ECPJ , y EFgrid , y

There is no consumption of electricity from the distribution grid. PEEC,y = 0 c) CO2 emissions from fossil fuel combustion due to transportation of biomass from the plantation site(s) to the site of the project plant (PETP,y) Option 2:

PETP , y

FCTR , i , y NCVi EFCO 2, FF ,i i

Diesel oil consumption for transportation

FCTR,i,y

................................

Density of diesel oil

Net calorific value of diesel oil

NCV


EFCO2,FF,i

PECO2,TR,y

d) CH4 emissions from combustion of biomass (PEBF,y)

PEBF , y

GWPCH 4

BFPJ , j , y NCV j EFCH 4, BF , j j

Global warming potential

GWPCH4

Quantity of Lamtoro Gung wood gasified

BFPJ,j,y

Net calorific value of Lamtoro Gung wood

NCVj

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CH4 emission factor for the combustion of Lamtoro EFCH4,BF, Gung wood Project emission from combustion of lamtoro Gung PEBF,y wood

e) CO2 emissions from fossil fuel consumption during agricultural operations (PEFC,PL,y)

PE FC,PL ,y

FCPL ,i ,y NCVi EFCO2 ,FF,i i

Project emissions related to diesel consumption used at PEFC,PL,y the dedicated plantation Annual diesel consumption in the dedicated plantatation FCPL,i,y

Net calorific value of diesel

NCVi


EFCO2,FF,i

f) Emissions from the production of synthetic fertilizer that is used at the plantation (PEFP,y)

PE FP , y

EFCO 2 e , FP , f FSF , f , y f

Emission factor for GHG emissions associated EFCO2e,FP,f with the production of fertilizer Annual quantity of fertilizer used FSF,f,y

Project emission related to the production of PEFP,y synthetic fertilizer

g) N2O emissions from application of fertilizers at the plantation (PEFA,y)

PEFA, y

GWPN 2O

44 PEN 2O 28

N , dir , y

PEN 2O

N , ind , y

Global Warming Potential of nitrous oxide valid for the GWPN2O commitment period Annual direct N2O‐N emissions as a result of nitrogen PEN2O‐N,dir,y application at the dedicated plantation

...... tCO2e/tN2O ....... tN2O‐N/yr

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Annual indirect N2O‐N emissions as a result of nitrogen PEN2O‐N,ind,y application at the dedicated plantation

0


PEN 2O

N , dir , y

EFN 2O

N , dir

FON , y

FSN , y

Direct N2O‐N emissions as a result of nitrogen application at the dedicated plantation Emission factor for direct nitrous oxide emissions from N inputs Amount of organic fertilizer nitrogen from animal manure, sewage, compost or other organic amendments applied at the dedicated plantation during Amount of synthetic fertilizer nitrogen applied at the dedicated plantation h) CH4 and N2O emissions from the field burning of biomass

PE BB,y


PEN2O‐N,dir,y

EFN2O‐N,dir

FON,y

FSN,y

EFCH4,BB GWPCH4

There is no field burning of biomass PEBB,y 0 Leakage As the project activity does not use any residual biomass, there is no leakage emission (LEy=0) Emission reductions

ERy Parameter

BEy

PEy

LEy Unit

Value

ERy

tCO2e/yr

BEy

tCO2e/yr

PEy

tCO2e/yr

LEy

tCO2e/yr

0

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ATTACHMENT II

Financial Internal Rate of Return (FIRR) Calculation Investment

2016 ‐2,654,623

2017 ‐1,769,749

‐2,654,623 ‐796,387

‐1,769,749 ‐530,925

Income Net Cash Flow (P) Net Cash Flow (E) Project IRR Equity IRR NPV rate NPV (project based) NPV (equity based) Payback period

1 2018

2 2019

3 2020

4 2021

5 2022

6 2023

7 2024

8 2025

9 2026

10 2027

11 2028

12 2029

13 2030

14 2031

15 2032

16 2033

17 2034

18 2035

19 2036

20 2037

0

174,920

167,756

160,490

153,121

98,773

311,503

303,816

296,020

288,113

233,219

271,961

263,712

255,347

246,862

191,382

229,529

220,677

211,699

202,593

146,484

174,920 174,920

167,756 167,756

160,490 160,490

153,121 153,121

98,773 98,773

311,503 311,503

303,816 303,816

296,020 296,020

288,113 288,113

233,219 233,219

271,961 271,961

263,712 263,712

255,347 255,347

246,862 246,862

191,382 191,382

229,529 229,529

220,677 220,677

211,699 211,699

202,593 202,593

146,484 146,484

0.01% 13.4% 4% ($1,079,257) $1,852,871 13 year

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ATTACHMENT IIII Productivity of Leucaena Leucocephala Table 1. Biomass component yield of leucaena planted over a 4‐year period (Sources: Songyos Chotchutima et.al., 2013) Thailand Cutting in

Rainfall (mm)

Fresh weight (t/ha)

Dry weight (t/ha)

Heating value (Kcal/kg)

1st year

1156

35.9‐53.2

17.3‐25.4

2nd year

1372

50.8‐66.5

24.7‐31.7

3rd year

1249

51.8‐71.3

25.5‐34.2

4630‐4720

4th year

1428

44‐62.8

19.3‐28.6

4370‐4410

Total (1st ‐ 4th year)

186.2‐253.8

87.2‐119.4

Table 2. Tree growth and wood traits of L. leucocephala at 6 and 12 mth after planting in Afar Region, Ethiopia (Sources: Ahmed Seid Ali et.al. 2013) Parameter 6 Month mean 12 Month mean Plant height (m)

2.03

5.22

Stem diameter (cm)

2.10

5.10

Number of trunk

11.10

12.76

Root length (m)

2.28

3.29

Stem biomass (kg.tree‐1)

1.69

2.68

Branch biomass (kg.tree‐1)

0.48

0.87

Leaf biomass (kg.tree‐1)

0.42

0.78

TAB (kg.tree‐1)

2.39

4.33

Stem biomass (t.ha‐1)

13.48

23.99

Branch biomass (t.ha‐1)

4.34

10.35

Leaf biomass (t.ha‐1)

3.78

6.66

TAB (t.ha‐1)

21.60

38.19

Calorific value (kJ.kg‐1)

‐

19.60

Calorific value (kcal/kg)

4684

Ash (%)

‐

1.93

Specific gravity

‐

0.52

Means followed by the same lowercase superscript letter within a row are not signifi cant (P < 0.05) at 6 and 12 mth after planting; TAB = Total above ground biomass; LL = L. leucocephala; Stem diameter = Stem diameter over bark measured at 1.3 m.

Samples of the stem, leaves and branches were taken, dried at 65 °C until constant mass and then the dry biomass of each portion was determined. The total dry biomass and biomass allocation to each component of each tree were calculated.

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Table 3. Mean Height, DBH and Wood Yield of Sample Trees of Leucaena leucocephala at age four years (Sources: Anthony Agustus Mainoo et.al. 1996) Ghana Variable/Component Species (Leucaena leucocephala) DBH (cm)

4.46

Heigh (m)

5.94

Dry Weight (t/Ha)

Stem

30.35

Branch

8.95

Total

39.30

Volume (m3/Ha)

Stem

42.42

Branch

13.11

Total

55.53

Calorific values of stem components (kcal/kg)

4703

Table 4. Leucaena growth rate during year 1 (Planting period 12 Months), Source: Sam Bona and Leuk Dana, 2005 Cambodia Variable/Component Species (Leucaena leucocephala) Fresh (t/Ha)

Oven Dried (t/ha)

Stem

6.8

3.8

Branch

10.3

5.1

Total

17.1

8.9

Foliage

6.1

2.0

Fruits

0.1

0.0

Total above ground biomass

23.3

10.9

Table 5. Biomass yielded and characteristics of fiber from Leucaena varieties during 2 years (Sources: F. Lopez et.al., 2008) Spain Varieties Year 1 Year 2 Year 1 sprouts WD

TD

WD

TD

WD

TD

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L. leucocephala (H)

9.4

12.8

17.1

23.4

28.4

38.8

L. leucocephala (I)

9.1

13.5

20.8

30.9

45.1

67.1

L. leucocephala (K360)

7.8

12.3

16.1

25.6

31.5

50.0

Note: Plants were obtained from seeds, for six varieties of Leucaena. L. leucocephala from Honduras (H), L. leucocephala from India (I), L. leucocephala var. K360 (K360), L. salvadorensis, L. collinsii and L. diversifolia were the varieties used in this experiment. In the case of L. leucocephala, it can be seen that a pruning every 2 years does not cause an important increase in the annual growth ratio, while if they are pruned when they are 1 year old, the grown sprout during that second year notably increases the production, reaching 50 t/ha/year.

References: 1. Songyos Chotchutima, Kunn Kangvansaichol, Sayan Tudsri, Prapa Sripichitt1, Journal of Sustainable Bioenergy Systems, 2013, 3, 48‐56 http://dx.doi.org/10.4236/jsbs.2013.31006 Published Online March 2013 (http://www.scirp.org/journal/jsbs), “Effect of Spacing on Growth, Biomass Yield and Quality of Leucaena (Leucaena leucocephala (Lam.) de Wit.) for Renewable Energy in Thailand” 2. Ahmed Seid Ali, Sayan Tudsri, Sarawut Rungmekarat2 and Kriengkri Kaewtrakulpong, Growth, Biomass Productivity and Energy Characteristics of Prosopis julifl ora (Sw.) DC. and Leucaena leucocephala (Lam.) De Wit in Afar Region, Ethiopia, Kasetsart J. (Nat. Sci.) 47 : 663 ‐ 674 (2013) 3. Anthony Agustus Mainoo & Francis Ulzen‐Appiah, “Growth, Wood Yield and Energy Characteristics of Leucaena Leucocephala, Gliricidia Sepium and Senna Siamea at age four years”, Ghana Journal of Forestry Vol. 3 1996 4. Sam Bona and Leuk Dana, “Farming Wood Fuel For Sustainable Energy In Rural Areas In Cambodia”, Workshop on Issues for the Sustainable Use of Biomass Resources for Energy, Colombo, Sri Lanka, 15‐19 August 2005 5. F. Lopez, M.M. Garcıa, R. Yanez, R. Tapias, M. Fernandez, M.J. Dıaz, “Leucaena species valoration for biomass and paper production in 1 and 2 year harvest”, Bioresource Technology 99 (2008) 4846–4853

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3.

WIND FARM PRE-FEASIBILITY STUDY


December 2015

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www.i-windenergy.com

Client: Asian Development Bank Title: Preliminary Wind Resource Assessment & Financial Assessment of Hambapraing, Sumba

Version 2.0 November 30, 2015

Prepared by: Pramod Jain, Ph.D. Innovative Wind Energy, Inc. 8578 Ethans Glen, Jacksonville, FL 32256 [email protected], +1-904-923-6489

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Version Version Number 1.0

Date of release October 19, 2015

Modifications in new release First release

2.0

November 28, 2015

Review of financial model by Xiaodong Review of entire report by Mike Crosetti

12/14/2015

Innovative Wind Energy, Inc.

Signature PJ

Page 2

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Table of Contents Executive Summary .................................................................................................................................. 6 1. Background ....................................................................................................................................... 7 Disclaimers ...................................................................................................................................... 7 2. Site Location ..................................................................................................................................... 9 3. Wind Data Sources ......................................................................................................................... 10 Data quality .................................................................................................................................... 10 Data Correction .............................................................................................................................. 10 Vertical Extrapolation .................................................................................................................... 11 Long-term data, MCP .................................................................................................................... 11 4. Wind Data Analysis and Wind Resource Map ............................................................................... 13 GIS map of the area ....................................................................................................................... 16 5. Layout of Turbines, Turbine Selection and Annual Energy Production ......................................... 17 6. Notes About Losses and Uncertainty .............................................................................................. 22 7. Financial Analysis ........................................................................................................................... 24 Analysis of Financial Results......................................................................................................... 25 8. Conclusions & Next Steps .............................................................................................................. 26 Appendix I: Financial Analysis Details Cash flow for the 10.2MW wind project ................................. 27

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LIST OF TABLES Table 1: Annual energy production and capacity factor for the 12x850kW wind farm .............................. 6 Table 2: Results of the financial analysis...................................................................................................... 6 Table 3: Source of wind data used for analysis. Anemometer heights, measurement interval, duration of mesurement and distance from proposed wind turbine sites are listed. .................................................. 10 Table 4: Average wind speed of various time series................................................................................... 11 Table 5: Long-term data series used for long-term correction of measured data. The last two columns contain the correlation with measured wind speed data from 1410 met-tower. ......................................... 12 Table 6: Siting and wind energy parameters for the twelve 850-KW WTG wind farm. Latitude/Longitude are in metric units in UTM84 coordinate system. The average wind speed is at hub height of 65m. Net AEP = Gross AEP – Wake loss. ........................................................................... 21 Table 7: Loss assumptions used in the project. In this preliminary analysis, losses add up to 10%......... 22 Table 8: Annual AEP estimates after losses and with uncertainty. The first column AEP is from Table 2. 10% losses were used in the calculation. ..................................................................................... 22 Table 9: Uncertainty assumptions used in the project. ............................................................................... 22 Table 10: AEP-P75, AEP-P90 and AEP-P95 are energy production levels for 75, 90 and 95% exceedance probabilities. ............................................................................................................................ 23 Table 11: Financial and operational assumptions about two scenarios. ..................................................... 24 Table 12: Performance metrics for the two scenarios. ................................................................................ 24

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LIST OF FIGURES Figure 1: North-central region of Sumba island. The ADB met-mast location is labeled. .......................... 9 Figure 2: Zoomed in view of the site. Locations of wind measurement and location of part 1 of wind farm are labeled as the “Met-masts” and “WTG” respectively. Also marked are the primary road in the area and the 20kV line, which runs along the road. ................................................................................ 9 Figure 3: Process of cleaning the raw wind data and filling holes.............................................................. 11 Figure 4: Plot of variation of MERRA long-term wind data ( ). The area shaded in yellow is the measurement period. ...................................................................... 12 Figure 5: Wind climate derived from the corrected data of met-tower 1410. ............................................. 13 Figure 6a,b,c,d: Plots a and b are monthly and hourly profiles of average wind speed at 65m above the ground level. April through Septemeber are high wind months. Plots c and d are average wind speed by hour for the peak wind month of August and low wind month of December........................................ 15 Figure 7: Elevation contour and roughness contours for Hambapraing...................................................... 16 Figure 8: Wind resource map of Hambapraing. Areas colored red have the highest, while areas in gray have the lowest wind power density. The location of met-mast 1410 and placement of twelve wind turbines is also illustrated................................................................................................................... 18 Figure 9a,b: Zoomed in view of wind resource map of Area 1 and Area 2 in Hambapraing along with layout of the 12 WTGs. ............................................................................................................................... 19 Figure 10: WTGs with wind rose attached for locations in Area 1 and Area 2; it illustrates that the frequency of wind from south-east is high and there should be minimal wake effect. The circle around the WTG has a diameter of 3 times the rotor diameter. The elevation contour lines (in meters) are also displayed. ....................................................................................................................................... 20 Figure 11: Power production curve (Power output P versus wind speed u) of the Vestas V52-850kW wind turbine for air density of 1.225 kg/m3. .............................................................................................. 21

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Executive Summary The Sumba Iconic Initiative (SII) aims to, by 2025, accomplish 95% electrification and a target of 100% renewable energy for electricity production1. As part of the Asian Development Bank (ADB) Technical Assistance (TA) No. 8287-INO: Scaling-Up Renewable Energy Access in Eastern Indonesia Castlerock prepared a least-cost electrification plan which identified 10MW of wind power2 as part of the future least-cost generation mix. In accordance with this plan, ADB financed installation and one year’s operation of a 60 meter met-mast to collect wind data at Hambapraing, Sumba. The met-mast was commissioned in October 2014. At the end of one year of data collection, this deliverable is a prefeasibility study of 10MW of wind power development in Sumba at Hambapraing. It consists of an initial wind resource assessment and a preliminary financial assessment of the 10MW wind project. This wind resource assessment is based on about 10 months of measured wind data over a period of 12 months using the 60m ADB met-mast, and statistical-fill in for the missing 2 months of data using data from the 33m HIVOS met-mast, which is sited approximately 5 km to the north of the ADB met-mast. The wind resource analysis is performed using WAsP. The wind turbine generator (WTG) chosen for this analysis is 850kW with 52m rotor diameter and 65m hub height, which is likely to meet the logistical constraints in Sumba. A preliminary siting of 12 WTGs in a 10.2MW wind farm is performed, it involves siting 8 WTGs near the ADB met-mast and siting the rest about 5 km south. These two areas in Hambapraing have the highest wind energy density and sufficient amount of land. The annual energy production (AEP), wake loss and capacity factor for the 12 WTG wind farm are presented below. WTG Count

Wind farm (MW)

Av. Elevation (m)

Av. Wind speed (m/s)

Gross AEP (GWh)

Net AEP (GWh)

Av. Wake loss (%)

10.2 453.7 7.39 31.67 31.16 1.6 12 Table 1: Annual energy production and capacity factor for the 12x850kW wind farm

Av. Capacity factor (%)

34.9

Preliminary estimates of losses and resource uncertainty were applied to the above computations to determine the exceedance probabilities (P50, P75 and P90). These values were used to perform a financial analysis of the wind project. The results of the financial analysis suggest that a 10.2MW wind project is financially viable, under conservative assumptions and a $0.28/kWh feed-in tariff as currently under discussion by the Ministry of Energy and Mineral Resources. It meets the expected return on equity and the debt service coverage ratio is close to an acceptable threshold.

AEP with 10% losses (GWh) Total Installed Cost (million $) Total Annual Revenue (million $) Project IRR, after-tax (%) Return on Equity, after tax (%) Debt service coverage ratio Simple payback period on equity (years) Table 2: Results of the financial analysis

Cost Scenario 1 P50 P75 28.047 25.775 $23.49 $23.49 $7.85 $7.22 17.2 15.7 24.1 20.6 1.49 1.37 5 7

P90 23.722 $23.49 $6.64 14.2 17.5 1.26 9

1

Ministerial Decree 3051 K/30/MEM/2015 on Designation of Sumba Island as a Renewable Energy Iconic Island stipulates that renewable energy will account for 95% of total energy supply on Sumba by 2020. Further analysis is underway to assess realistic timing to achieve targets of near-universal electricity access and full reliance on renewable energy. 2 The Least-Cost Plan may be downloaded from http://castlerockasia.com/sumba/sii.html 12/14/2015


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1. Background Innovative Wind Energy Inc. (IWE) has prepared this wind resource assessment report under contract to Castlerock Consulting as part of the Asian Development Bank (ADB) Technical Assistance (TA) No. 8287-INO: Scaling-Up Renewable Energy Access in Eastern Indonesia. The technical assistance program is part of the Sumba Iconic Island (SII) initiative, a multi-stakeholder undertaking led by the Directorate General of New & Renewable Energy and Energy Conservation within the Ministry of Energy and Mineral Resources, in partnership with Hivos, a Netherlands-based nongovernmental organization (NGO); the provincial government of Nusa Tenggara Timur; the four kabupaten of Sumba; Perusahaan Listrik Negara (PLN), the Indonesian national utility; other government ministries and NGOs; and development partners including ADB, the Government of Norway and Agence Francaise de Developpement (AFD). The SII initiative aims to accomplish the following by 20253: Increase the electrification ratio on the island of Sumba from a current level of some 30% of households to 95% (the “electrification ratio target”), and Increase the share of electricity produced from renewable resources on Sumba from some 15% to 100% (the “renewable contribution target”). The program aspires to these objectives not only for the benefit of Sumba, but to establish a model that may be replicated elsewhere in Indonesia. Within the TA-8287, this report is presented as part of the Final Report. Other principal deliverables produced under the assignment include: Inception Report (November 2013) Deliverable B: Energy Resources for Grid Supply & Electricity Demand Analysis for Sumba (September 2014) Met-mast bidding, procurement and installation (October 2014) Mid-Term Report: Least-Cost Electrification Plan for the Iconic Island (December 2014) Deliverable A: Achieving Universal Electricity Access in Indonesia (July 2015) The least-cost electrification plan determined a wind power penetration of 10MW as part of the 2025 generation mix in Sumba4. In order to better understand the wind resources in Sumba, a 60 meter metmast was installed in Hambapraing in October 2014. After the culmination of one year of wind measurement using this tower, a preliminary wind resource assessment and preliminary wind project financial assessment is being undertaken. The results of the assessments are reported in this document and will serve as the pre-feasibility report for wind project of size 10MW in the Hambapraing area of Sumba.

Disclaimers The analyses presented here and the data it is based on were done with utmost care. However, IWE will not be held responsible for any damages or liabilities resulting from the application or use of the

3

As noted above, the timing of these targets are being refined to provide realistic guidance. The least-cost analysis was based on a load forecast corresponding to a 95% electrification ratio in 2025. The maximum penetration of wind generation capacity was limited to 25% of peak demand in that analysis to reflect system operating constraints. Lower load growth or a failure to upgrade transmission infrastructure would likely result in a lower level of maximum penetration. The Least-Cost Plan may be downloaded from http://castlerockasia.com/sumba/sii.html. 4

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data/analyses. The views and recommendations outlined in this document represent the viewpoint solely of IWE. The following datasets form the basis of this report: onsite wind measurement data from ADB met-mast, one year of measurement data from the HIVOS met-mast and long-term data from 3Tier.The ADB metmast yielded 10 months of measured wind data over a period of 12 months, the met-mast was unavailable due to unscheduled maintenance for 2 months. A high quality wind resource assessment requires one year or more of contiguous dataset with higher than 95% of availability. HIVOS met-mast data was utilized to statistically fill-in for the 2 months of missing data. This wind resource assessment does not replace the need to complete a site-specific terrain study, environmental impact study and other engineering studies in order to determine the viability of the wind project. This report and the data contained herein remain ADB's sole property. ADB may release them to the general public at its sole discretion. Unless or until ADB releases this report to general public, the contents of the report may not be copied or disclosed to any person or entity except with ADB's prior written consent.

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2. Hambapraing Site Details Figures 1 and 2 below are aerial views of the Hambapraing area from Google Earth.

Figure 1: North-central region of Sumba island. The ADB met-mast location is labeled.

Road & 20kV line

Figure 2: Zoomed in view of the site. Locations of wind measurement and location of part 1 of wind farm are labeled as the “Met-masts” and “WTG” respectively. Also marked are the primary road in the area and the 20kV line, which runs along the road.

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3. Wind Data Sources Two sources of measured wind data were used for the analysis, see Table 3. The HIVOS met-mast or tower 1261 was installed in July 2012; this project was given access to data from October 2014. It is a 33 meter met-mast close to the shore, see Figure 2. Tower-1410 is the ADB met-mast installed in October 2014. It is a 60 meter tower located closer to the region where the 10.2MW wind farm is planned, hence it is the primary source of wind speed data used in this analysis. Tower-1410 was unavailable for two months due to unscheduled maintenance, so Tower-1261 data was used to fill up missing data in Tower1410 time series. Table 3: Source of wind data used for analysis. Anemometer heights, measurement interval, duration of mesurement and distance from proposed wind turbine sites are listed. Location Height in Measurement Distance* meters Interval, Duration from site (km) 32 10 minutes; 6.24 1 Tower 1261 (HIVOS met-mast) 23 12 months 10/2014 - 10/2015 57 10 minutes; 1.1 2 Tower 1410 (ADB met-mast) 47 12 months 10 days, 32 10/2014 – 10/2015 *Straight line distance, i.e. as the crow flies

Data quality The following data quality and availability issues were noted for Met-Tower 1410 (the ADB tower): 1. Anemometer at 47m was malfunctioning starting October 27, 2014. Loose connection was fixed on December 9, 2014. 2. Wind vane on Channel 7 at 53m started malfunctioning around January 16, 2015. Its reading would remain constant while the second wind vane at 43m tracked wind direction. 3. Wind speed on Channel 1 at 57m was slowing and possible malfunction was detected in February 2015 by comparing it to wind speed readings on Channel 3 for the anemometer at 47m. 4. On May 9, 2015 the met-tower (all instruments) stopped functioning because it fell to the ground during a lowering manueverto replace sensors. The fall occurred after the met-tower had been lowered by 80 degrees. More detailed information is available from Winrock, ADB’s contractor for the met-tower. 5. The met-tower was functioning again on July 10, 2015. Redundant anemometers (with orientation of 210 degrees) at 47m and 32m were removed, and channel for the remaining anemometer at 47m with orientation of 30 degrees was changed.

Data correction Given the issues listed above significant amount of data correction was performed to obtain one-year of wind measurement data that is usable for wind resource assessment. Figure 3 illustrates the process of data correction. The raw wind file was split into two because there was a change in channels. The two data streams are merged to create the corrected data stream with correct channels. The Filter block flags data based on variety of criteria; here wind speed data is flagged when value is 0.2 m/s or empty, which occured when the met-tower was not functioning. Measure Correlate Prediction (MCP) step takes as input wind speed data from met-tower 1261, performs correlation with wind speed data from met-tower 1410 to create a new time series of wind speed which is a statistical prediction of the combined wind speed. The Fill Data step then replaces the flagged wind data in 1410 time series with the MCP 12/14/2015


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prediction. At the end of this step, the wind speed time series has been fixed—the missing data from May 9 to July 10, 2015 are replaced with statistically adjusted data from the 1261 tower. The next set of blocks fix wind direction data. Fill Dirn block removes all the constant value (due to faulty wind vane) in 53m wind vane with values from the 43m wind vane. The Filter block flags all the wind direction when the met-tower was not functioning. The Fill Dirn2 block uses the direction data from 1261 tower and replaces the data flagged in the previous step.

Figure 3: Process of cleaning the raw wind data and filling holes.

Vertical extrapolation Shear was computed using wind speed data from 57m, 47m and 32m anemometers on 1410 met-mast. Shear parameters were estimated using the power law for each of the 12 direction sectors, each month and each hour. These parameters were applied to the 57m wind speed data in order to extrapolate to 65m, see Table 3. The average shear was computed to be 0.07068. Table 4: Average wind speed of various time series. Average Original time Time series after wind speed series with gaps data correction in m/s

Time series after extrapolation

Time series after long-term correction

65m AGL

6.71

7.005

57m AGL

6.007

6.648

6.648

6.941

47m AGL

5.996

6.633

6.633

6.925

32m AGL

5.824

6.44

6.44

6.723

Long-term correction of data using Measure Correlate Predict (MCP) Two long-term data series were obtained from 3Tier—MERRA (Modern Era Retrospective-Analysis for Research and Applications, http://gmao.gsfc.nasa.gov/research/merra/) and ERAI (European Centre for Medium-Range Weather Forecasts, http://www.ecmwf.int/en/research/climate-reanalysis/era-interim). The statistics for the two series are in Table 4. The hourly correlations between the measured and each of MERRA and ERAI is low, so the long-term dataset is not well suited for performing a long-term correction of the measured time series. However preliminary analysis of the both MERRA and ERAI dataset suggests that the measured time period has wind speed that are 4.4% lower that the long-term average. The last column in Table 4 contains the annual average wind speed with the 4.4% increase for long-term correction. Figure 4 is a plot of the annual variation of wind speed around the long-term mean. 12/14/2015


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Since the correlation between the measured and long-term data series is low, all the subsequent analysis will use the more conservative wind data time series without the 4.4% long-term correction. Table 5: Long-term data series used for long-term correction of measured data. The last two columns contain the correlation with measured wind speed data from 1410 met-tower.

Time period

MERRA data ERAI data

1981-01-01 to 2015-07-31 1981-01-01 to 2015-06-27

Average Wind Speed (m/s), 65m AGL 5.497

Correlation with measured data (hourly) 0.597

Correlation with measured data (daily) 0.842

5.535

0.395

0.739

Figure 4: Plot of variation of MERRA long-term wind data ( The area shaded in yellow is the measurement period.

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).

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4. Wind Data Analysis and Wind Resource Map This section presents analysis of wind data after the data correction task was performed. Figure 5 contains wind statistics. The overall wind speed average of the dataset is 6.71 m/s, while the average of the modeled dataset is 6.92 m/s. In the modeled dataset, the time series data is segmented into 12 direction sectors, and Weibull distribution parameters (A and k) and Weibull distribution’s mean wind speed are computed for each sector. These means are combined by adding sector mean multiplied by sector frequency to obtain the fitted mean wind speed. The Quality columns in Figure 5 are indications of the difference between source data mean and fitted mean of wind speed and power. Although the difference between mean wind speed of fitted versus source is higher than normal, the mean power difference is small (278 W/m2 versus 276 W/m2). The mean power difference is a better metric for measuring quality of fit and since it is small, the sectorwise Weibull parameters are used for all subsequent computations.

Figure 5: Wind climate derived from the corrected data of met-tower 1410.

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The rose plot indicates that the highest frequency of wind is from the 120-degree sector (East-SouthEast), and about 65% of the time wind direction is in the three sectors between 90 degs and 150 degs. It is worth noting that the highest energy is in sector 11 (300-degree), but the frequency is low (5.9%).

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Figure 6a,b,c,d: Plots a and b are monthly and hourly profiles of average wind speed at 65m above the ground level. April through Septemeber are high wind months. Plots c and d are average wind speed by hour for the peak wind month of August and low wind month of December.

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The seasonal and diurnal pattern of wind speed are presented in Figure 6. Months from May to September are high wind months. Notice that there is a substantial difference between the three diurnal plots b, c and d. The diurnal profile of the annual average (plot b) is similar to the diurnal profile for December. While the diurnal profile for the peak month of August has smaller inter-hour variation. In August the highest winds are between midnight and 6AM. In December the highest winds are between 11AM and 5PM.

GIS map of the area The elevation contour of the Hambapraing area was obtained from SRTM (Shuttle Radar Topography Mission, http://srtm.usgs.gov/), and roughness areas were marked visually based on large-scale vegetation changes. This is presented in Figure 7.

Figure 7: Elevation contour and roughness contours for Hambapraing.

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5. Layout of Turbines, Turbine Selection and Annual Energy Production (AEP) The digital map of Hambapraing was combined with the wind speed statistics by WAsP to create a wind resource map, see Figure 8. The highest energy density areas are in red. Turbine selection for this analysis is based primarily on infrastructure in the island and the associated cost of logistics to transport the turbine from the port to the location. A private investor has conducted preliminary analysis and determined that the Vestas V52-850kW wind turbine is likely the largest turbine that can be transported to Hambapraing at reasonable cost. This WTG has a rotor diameter of 52m and hub height of 65m. This WTG was therefore chosen for computation of AEP. In order to site a 10MW wind farm, eight V52-850kW WTGs were sited in the red area near the mettower (Area 1) and four WTGs were sited about 5 km south (Area 2), see Figures 8, 9 and 10. The total capacity of the wind farm is 10.2MW. The eight WTGs are located 160m apart along a straight line. The distance between the turbines is slightly more than 3D, where D is the rotor diameter ( ). A distance between turbines of 3D in a direction that is perpendicular to the primary wind direction is a good rule of thumb to minimize wake losses. The second set of 4 WTGs were manually sited in Area 2; locations that are in flat area with high wind energy density. The power production of the WTG is shown in Figure 10. Table 6 contains data about the twelve WTG wind farm—coordinates, elevation, wind speed at hub height, gross and net annual energy production (AEP), wake losses and net capacity factors. All the calculations were done using WAsP version 11.1.

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Area 1

Area 2

Figure 8: Wind resource map of Hambapraing. Areas colored red have the highest, while areas in gray have the lowest wind power density. The location of met-mast 1410 and placement of twelve wind turbines is also illustrated.

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Figure 9a,b: Zoomed in view of wind resource map of Area 1 and Area 2 in Hambapraing along with layout of the 12 WTGs. 12/14/2015


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Figure 10: WTGs with wind rose attached for locations in Area 1 and Area 2; it illustrates that the frequency of wind from south-east is high and there should be minimal wake effect. The circle around the WTG has a diameter of 3 times the rotor diameter. The elevation contour lines (in meters) are also displayed. 12/14/2015


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Figure 11: Power production curve (Power output P versus wind speed u) of the Vestas V52-850kW wind turbine for air density of 1.225 kg/m3. Table 6: Siting and wind energy parameters for the twelve 850-KW WTG wind farm. Latitude/Longitude are in metric units in UTM84 coordinate system. The average wind speed is at hub height of 65m. Net AEP = Gross AEP – Wake loss. WTG Latitude Longitude Elevation Wind Gross Net Wake Capacity (m) (m) (m) speed AEP AEP loss (%) factor (m/s) (GWh) (GWh) 189049.3 -1054305 464.8 7.31 2.578 2.521 2.22 0.339 1 188910.7 -1054385 470.4 7.33 2.596 2.527 2.66 0.339 2 188772.1 -1054464 471.5 7.33 2.595 2.53 2.52 0.340 3 188633.5 -1054544 474.4 7.38 2.637 2.572 2.44 0.345 4 188494.9 -1054624 469.6 7.33 2.603 2.544 2.26 0.342 5 188356.2 -1054704 465 7.29 2.577 2.523 2.09 0.339 6 188217.6 -1054784 461.2 7.26 2.551 2.505 1.77 0.336 7 188079 -1054864 460.4 7.26 2.551 2.537 0.53 0.341 8 191596.3 -1060845 428 7.55 2.754 2.726 0.99 0.366 9 191591.3 -1061019 426 7.53 2.738 2.714 0.87 0.364 10 191603 -1061215 427.6 7.52 2.739 2.737 0.08 0.368 11 191717.8 -1060700 425.1 7.55 2.755 2.727 1.04 0.366 12 Turbines 9 to 12 have higher energy production and lower wake losses compared to turbines 1 to 8. However, from a constructability standpoint, the locations of turbines 1 to 8 are more suitable because of low variation in elevation (flat area). The total net AEP in Table 6 accounts only for wake losses, the other losses are applied in the next section. The total net AEP is 31.163 GWh and the average capacity factor is 34.88%.

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6. Notes About Losses and Uncertainty The following losses were assumed in the current analysis. The scope of this project does not include assessing site specific losses, therefore generic estimates (Source: P. Jain, Wind Energy Engineering, McGraw-Hill, NY, 2010) are used. The net annual AEP after 10% losses is Table 7. Table 7: Loss assumptions used in the project. In this preliminary analysis, losses add up to 10%. Name Loss [%] 1. Wake effects, all WTGs 2. Availability Turbine availability Balance of plant (Substation) Grid availability 3. Turbine power curve performance 4. Electrical losses 5. Environmental & Others Total

Included 3 1 1 2 2 1 10%

Table 8: Annual AEP estimates after losses and with uncertainty. The first column AEP is from Table 2. 10% losses were used in the calculation. AEP Net AEP after Net Capacity (GWh) losses (GWh) factor 31.163

28.047

31.4%

The uncertainties listed in Table 5 were assumed in the current analysis. The highest uncertainty is wind speed measurement, because onsite wind speed data is not available. The net one-year uncertainty5 is 12% on AEP. Assessment of site-specific uncertainty is not within scope, therefore a generic estimate (same source as above) is used. Table 9: Uncertainty assumptions used in the project. Parameter Unit Std dev on Value [%] A. Wind Data - Wind measurement - Long term correction - Year-to-year variability B. Wind model C. Power curve uncertainty D. LOSS Total Uncertainty (%) 5

AEP-% AEP-% AEP-% AEP-% AEP-% AEP-% AEP-%

6 5 5 6 5 1 12

Same as standard deviation expressed as percentage of mean

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Based on the uncertainty assumptions, the AEP for exceedance probabilities of P75, P90 and P95 are computed in Table 10. AEP at P50 is the average energy production. AEP at P75 is the energy production in GWh that will be exceeded with a probability of 75%. Therefore, AEP-P95
25.775

P90

23.722

P95

22.510

Figure 12: Illustration of the exceedance probabilities. As as example, AEP at P90 is 23.72 GWh, which means that there is 90% confidence that the annual wind energy production will be 23.72 GWh or more.

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7. Financial Analysis A preliminary financial analysis of the 10.2MW wind project with twelve 850-kW wind turbines is presented here. The total installed cost analysis is not based on quotations from vendors, rather are primarily based on numbers provided by one private developer for refurbished turbines for installation of single turbine in Sumba. The data was provided in 2014 for installation in 2016. Two sets of cost numbers and assumptions were provided as shown in Table 11, hence Scenario 1 and Scenario 2 are analyzed below. It is assumed a windfarm of this size can be constructed within one year, hence there is no separate allowance taken for interest during construction. Table 11: Financial and operational assumptions about two scenarios. Scenario 1 Scenario 2 $2,303/kW $2,098/kW Total installed cost (TIC) $0.11/kWh $0.05/kWh Total O&M Costs 0% 5% Annual escalation of O&M 10.2MW 10.2MW Size of wind farm $0.280/kWh $0.280/kWh Sale price of energy 15-yr accelerated 15-yr accelerated Depreciation 25%, 13.8% 25%, 13.8% Tax rate, WACC* 15 years 15 years Life of project 70% debt/30% equity 70% debt/30% equity Financing Structure 8 years/12% 8 years/12% Debt duration/interest 18% 18% Required return on equity 5% 5% Investment tax deduction (ITD) 6 years 6 years ITC years Vestas V52-850kW Enercon 850kW Turbine *WACC: Nominal weighted average cost of capital. For purposes of comparison of the two scenarios, the amount of net AEP and uncertainty is assumed to the same. The financial metrics of the project as a result of the financial model are computed for exceedance probability P50, P75 and P90. The exceedance probability columns in Table 12 contain results that are likely to be realized with 50%, 75% and 90% probability. Table 12: Performance metrics for the two scenarios. Scenario 1 Annual Energy production (GWh) Total Installed Cost (million $) Total Annual Revenue (million $) Project IRR, after-tax (%) Return on Equity, after tax (%) Debt service coverage ratio Simple payback period on equity (years) Levelized Cost of Energy (current $/kWh) 12/14/2015

Scenario 2

P50 28.047 $23.49 $7.85 17.2 24.1 1.49

P75 25.775 $23.49 $7.22 15.7 20.6 1.37

P90 23.722 $23.49 $6.64 14.2 17.5 1.26

P50 28.047 $21.40 $7.85 24.7 44.7 2.12

P75 25.775 $21.40 $7.22 22.6 38.8 1.94

P90 23.722 $21.40 $6.64 20.7 33.7 1.79

5

7

9

3

3

3

$0.245

$0.257

$0.270

$0.187

$0.198

$0.210


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Analysis of Financial Results The tariff assumed for wind energy is 28 USc/kWh, which is the proposed feed-in tariff for wind projects in diesel-based 20kV grids such as Sumba. Investment tax deduction (ITD) of 5% for 6 years reduces the next taxable income of the project for 6 years by an amount equal to 5% of the total capital cost of the project. This deduction is an incentive taken in addition to depreciation. The primary differences between Scenarios 1 and 2 are that Scenario 2 is characterized by 15% lower capital cost and about 55% lower O&M cost. Both scenarios use refurbished wind turbines. In the judgment of the author, the O&M cost of Scenario 2 is below what can be reasonably expected. The reasons are: a) Indonesia is a new market for wind turbines so that there is little domestic technical support available, b) Sumba is a remote island with high logistics costs, and c) the size of wind farm is too small to provide any economies of scale. For these reasons, the cost of spares, support equipment (cranes) and personnel (expat) to support O&M operations will be higher. As a matter of reference O&M cost of wind farm with one or two wind turbines in a developed wind market is in the range of 4 to 5 USc per kWh; while the cost for 20MW wind farms is in the range of 2 USc per kWh. The life of the project is assumed to be 15 years because all turbines are assumed to be refurbished; the normal life of a wind project using new turbines is 20 to 25 years. Scenario 1 is therefore a more realistic case, hence it will be analyzed in more detail. Equity investors evaluate projects in terms of P75. A return of equity of 20.6% is higher than the required ROE of 18%. Lenders evaluate projects in terms of P90, that is, lenders determine amount of loan based on Debt Service Coverage Ratio (DSCR) for the P90 case. The minimum acceptable value of DSCR is typically in the range of 1.25 or 1.3. This scenario has DSCR of 1.26, which is very close the DSCR threshold and within allowed margin. The levelized cost of energy is comfortably below USc 28/kWh. Thus, the wind project is feasible even under the conservative scenario of high O&M cost.

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8. Conclusions & Next Steps Wind resource assessment was conducted for a wind project in Hambapraing based on wind data from two met-masts—60m ADB met-mast and 33m HIVOS met-mast with one year of measurement. Statistical methods were used to interpolate in cases of missing data. Spatial extrapolation was performed by WAsP software and a wind resource map was created. Twelve 850kW wind turbines were microsited in areas with the highest wind power density to create a 10.2MW wind farm. The average annual energy production was computed. Site or project specific losses and uncertainty were not assessed, rather typical values were used. The financial analysis of the project suggests a viable wind project even with conservative estimates of key parameters like O&M cost, annual AEP and others. With a tariff of USc 28/kWh, the 10.2MW wind project meets the return on equity threshold for equity investors and is in the allowable range for the debt service coverage ratio requirement of lenders. The following next steps are recommended for the wind project in Hambapraing, Sumba. This list should be reviewed in light of the wind power development and pricing regulation that are ultimately issued, as this regulation may impose other requirements as well. Wind Measurement. The 60m ADB met-mast, which was commissioned one year ago, has seen a period of about 2 months of unavailability. Although the data has been corrected, wind measurements should be continued for at least one more year to reduce the uncertainty and enhance the bankability of the wind resource assessment. The 33m met-mast, which is more than 6 km away from the proposed site, is useful as a means to correlate and fill in data. This measurement should also continue. The ADB will hand over the met-mast to Government of Indonesia counterparts by the end of 2015. Arrangements should be put in place to ensure the sustainability of future operations. Wind Turbine Class and Extreme Wind Speed. Turbine selection requires analysis of extreme wind speed, which is not in scope of this study. Based on the wind speed analysis above, a Class III turbine is appropriate for the Hambapraing wind project. However, Vestas V52-850kW is an IEC Class I/II wind turbine. Switching to an IEC Class III wind turbine would yield higher energy production because of larger rotor size. Logistics Study. A logistics study should be conducted to confirm the size of blades, tower, nacelle and cranes that can be transported to the Hambapraing site. Project Siting. Although siting and engineering are not in the scope of this report, the following siting issues must be taken into account before detailed site engineering is initiated: Microwave interference Radar interference for weather, military and homeland security radars Obstruction to aviation airspace (wind turbines at Hambapraing are unlikely to be hazard to aviation because of distance to airport) Environmental and Social Impact Assessments. Studies that are required for most wind farms include: Wetlands study Avian migratory path study Endangered species and other wildlife habitat and breeding Noise, shadow flicker, visual impact and indigenous cultural impact studies

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9. Appendix I: Financial Analysis Details Cash flow for the 10.2MW wind project Table I-1. Detailed analysis of the wind project of the P50 with Vestas V52-850kW WTG. All numbers (except DSCR) are in thousand. Years Gross Income O&M Operating Income (NOI) Loan payments DSCR (NOI/Loan payment)

0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085) ($3,085)

Equity Cash flow Project Cash flow

$(7,047) $1,561 $1,561 $1,561 $1,561 $1,561 $1,561 $1,561 $1,561 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768

$4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 ($3,207) ($3,207) ($3,207) ($3,207) ($3,207) ($3,207) ($3,207) ($3,207) $0 $0 $0 $0 $0 $0 $0 1.49

1.49

1.49

1.49

1.49

1.49

1.49

1.49

0.00

0.00

0.00

0.00

0.00

0.00

0.00

$(23,491)$4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768 $4,768

Linear depreciation $1,566 $1,566 $1,566 $1,566 $1,566 Interest payment $1,973 $1,813 $1,633 $1,432 $1,206 Principal balance $16,443 $15,107 $13,609 $11,932 $10,054 $7,950 NOI-Interest$1,229 $1,389 $1,569 $1,770 $1,995 Depreciation Investment tax $1,175 $1,175 $1,175 $1,175 $1,175 deduction Taxable Income $ 54 $215 $394 $596 $821 Taxes (25%) -25% ($14) ($54) ($99) ($149) ($205) After tax project cash $(23,491)$4,754 $4,714 $4,669 $4,619 $4,563 flow After tax equity cash $(7,047) $1,547 $1,507 $1,462 $1,412 $1,356 flow Liquidity (equity) $(7,047) ($5,500) ($3,992) ($2,530) ($1,118) $238

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$1,566 $1,566 $1,566 $1,566 $1,566 $1,566 $1,566 $1,566 $1,566 $1,566 $954 $671 $355 $$$$$$$$5,594 $2,955 $$$$$$$$$2,248 $2,531 $2,847 $3,202 $3,202 $3,202 $3,202 $3,202 $3,202 $3,202 $1,175 $$1,073 $2,531 $2,847 $3,202 $3,202 $3,202 $3,202 $3,202 $3,202 $3,202 ($268) ($633) ($712) ($800) ($800) ($800) ($800) ($800) ($800) ($800) $4,500 $4,135 $4,056 $3,968 $3,968 $3,968 $3,968 $3,968 $3,968 $3,968 $1,293 $928 $849 $3,968 $3,968 $3,968 $3,968 $3,968 $3,968 $3,968 $1,530 $2,459 $3,308 $7,275 $11,243 $15,210 $19,178 $23,145 $27,113 $31,080


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Table I-2. Detailed analysis of the wind project of the P50 with Enercon WTG. All numbers are in thousand. Years Gross Income O&M Operating Income (NOI) Loan payments DSCR (NOI/Loan payment)

0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 $7,853 ($1,402) ($1,472) ($1,546) ($1,623) ($1,705) ($1,790) ($1,879) ($1,973) ($2,072) ($2,176) ($2,284) ($2,398) ($2,518) ($2,644) ($2,777) $6,451 $6,381 $6,307 $6,230 $6,149 $6,063 $5,974 $5,880 $5,781 $5,678 $5,569 $5,455 $5,335 $5,209 $5,077

Equity Cash flow Project Cash flow

$(6,420) $3,529 $3,459 $3,386 $3,308 $3,227 $3,142 $3,052 $2,958 $5,781 $5,678 $5,569 $5,455 $5,335 $5,209 $5,077 $(21,400)$6,451 $6,381 $6,307 $6,230 $6,149 $6,063 $5,974 $5,880 $5,781 $5,678 $5,569 $5,455 $5,335 $5,209 $5,077

($2,922) ($2,922) ($2,922) ($2,922) ($2,922) ($2,922) ($2,922) ($2,922) $0 2.21 2.18 2.16 2.13 2.10 2.08 2.04 2.01 0.00

$1,427 $1,427 $1,427 $1,427 Linear depreciation $1,798 $1,651 $1,488 $1,304 Interest payment $14,980 $13,762 $12,398 $10,870 $9,159 Principal balance $3,227 $3,303 $3,393 $3,499 NOI-InterestDepreciation $1,070 $1,070 $1,070 $1,070 Investment tax deduction $2,157 $2,233 $2,323 $2,429 Taxable Income -25% ($539) ($558) ($581) ($607) Taxes (25%) After tax project cash $(21,400)$5,912 $5,823 $5,726 $5,623 flow After tax equity cash $(6,420) $2,990 $2,901 $2,805 $2,701 flow $(6,420) ($3,430) ($529) $2,276 $4,977 Liquidity (equity)

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$1,427 $1,099 $7,243 $3,623

$1,427 $869 $5,096 $3,768

$1,427 $612 $2,692 $3,936

$1,427 $323 $$4,130

$1,427 $$$4,355

$0 0.00

$1,427 $$$4,251

$0 0.00

$1,427 $$$4,142

$0 0.00

$1,427 $$$4,028

$0 0.00

$1,427 $$$3,908

$0 0.00

$1,427 $$$3,782

$0 0.00

$1,427 $$$3,650

$1,070 $1,070 $$2,553 $2,698 $3,936 $4,130 $4,355 $4,251 $4,142 $4,028 $3,908 $3,782 $3,650 ($638) ($674) ($984) ($1,033) ($1,089) ($1,063) ($1,036) ($1,007) ($977) ($946) ($912) $5,510 $5,389 $4,990 $4,847 $4,693 $4,615 $4,533 $4,448 $4,358 $4,263 $4,164 $2,589 $2,467 $2,068 $1,926 $4,693 $4,615 $4,533 $4,448 $4,358 $4,263 $4,164 $7,566 $10,033 $12,102 $14,027 $18,720 $23,335 $27,868 $32,316 $36,674 $40,937 $45,101


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4.

MICRO-HYDRO SCREENING STUDY


December 2015

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The Government of Indonesia & Asian Development Bank ADB TA 8287-INO: Scaling Up Renewable Energy Access in Eastern Indonesia Micro Hydro Study Report 14 December 2015 Page 133 of 396

ADB TA 8287-INO: Scaling Up Renewable Energy Access in Eastern Indonesia Micro Hydro Study Report 14 December 2015

Prepared for:

Government of Indonesia & Asian Development Bank

Prepared by:

PT. Castlerock Consulting

Castlerock Consulting Graha Iskandarsyah, 7th floor Jl. Iskandarsyah Raya No. 66C Jakarta 12160 Indonesia Tel: +62 21 270 2404 Fax: +62 21 270 2405 www.castlerockasia.com Version: 1.0

Government of Indonesia / ADB – 12/14/15

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TABLE OF CONTENTS Foreword

i

1.

Summary 1.1 Background 1.2 Method 1.3 Result and Recommendation 1.4 Annexes

1-1 1-1 1-1 1-2 1-3

2.

List of Sites Considered

2-1

3.

Desk Study Results

3-1

4.

Individual Reports For Each Site 4.1 Paberamanera 4.2 Karita 4.3 Waikanabu 4.4 Pulu Panjang 4.5 Pondok 4.6 Katikutana 4.7 Kuki talu 4.8 Mahu Bokul 4.9 Maidang – tai Tiring 4.10 Maidang - Tanarara 4.11 Wula 4.12 Walan Ndimu 4.13 Wee Kombaka 4.14 Wambidi 4.15 Soru 4.16 Weeluri 4.17 Sodana 4.18 Mbatapuhu 4.19 Praibakul 4.20 Kawangu 4.21 Waiyengu

4-1 4-1 4-5 4-8 4-13 4-17 4-21 4-24 4-28 4-32 4-35 4-38 4-42 4-46 4-50 4-53 4-57 4-61 4-64 4-68 4-71 4-75

ii Government of Indonesia / ADB – 12/14/15

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1.

SUMMARY

1.1

BACKGROUND

Based on desk study using the GIS and Network Planner analysis, there are opportunities for larger grid-connected hydro plants as well as for mini grid micro hydro in Sumba. This activity focuses on the assessment of mini-grid micro-hydro opportunities. A desk study indicated 40 potential micro hydro sites. There are 13 sites located in western Sumba and 27 sites located in eastern Sumba. 1.2

METHOD

The desk study used methodology as follows: 1. Identify all mini grid location from Network Planner under “low cost” scenario. There are 300 site potential of these. 2. Of those mini grid locations, around 100 sites were within 1 km or less of a perennial river, as indicated on BIG digital maps. 3. Of those, the 40 were selected on the following basis: Calculated the change in elevation from 1 km upstream to 1 km downstream of the settlement. This provides an estimate of head. Calculated the catchment area upstream of the settlement. This is a proxy for water debit. The sites were ranked by the product of (head x catchment area), where sites with larger values were considered to be more prospective. For those 40 sites, Google Earth was used to: a. Count houses and other buildings within 1 km radius or less. Locations with more than 30 buildings within the radius were selected. b. Assess the settlement characteristic. Locations with relatively centralized settlement patterns were selected. c. Assess road access, distance to the site from the main road (jalan provinsi), sub main road (jalan kabupaten) and jalan desa. Locations with within 1 km or less of a road that is at least 3 m wide were selected. Based on above assessment there are 22 sites have been selected and recommended for field survey. The objective of the survey to determine the sites that are candidates for development and that should be evaluated through a detailed feasibility study. The parameter for field survey will summarize description of the following items: 1. Watershed characteristic This item will be analyzed by interview with local villager and spot ground survey and filling the parameter of river dimension and estimated head along the river. 1-1 Government of Indonesia / ADB – 12/14/15

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1. Summary. . ..

2. Social community General information of social and community will be collected by interview and secondary data on site. These will include demography, education, rate of income, livelihood, productive activity, etc. 3. Site accessibility These will describe distance the site from village road, kabupaten road and provincial road. Including road condition and types, also distance from the closest electricity LV/MV PLN lines. 4. Public Facility Describe such of public facilities buildings, such as school, village building, Puskesmas, Pustu (Puskesmas Pembantu), Mosque/Church, etc. 5. Initial information of System capital and operating cost Key component of the system will be sized and cost, including: engineering design turbine and generator (delivered on-site) civil works (material) civil works (labor could be provided by the community in-kind rather than a cash expense) LV distribution household connection Annual system operating and maintenance costs

1.3

RESULT AND RECOMMENDATION

The summary result of this field assessment as described on the below table: No.

Conclusion

Recommendation

Site

1.

There are 5 sites having high Need FS for DED potential for Micro Hydro Power Generation off grid system

Pulu Panjang, Karita, Pabera manera, Pondok, and Waikanabu

2.

There are 2 sites having Need FS for DED and potential for Micro Hydro discuss with PLN Power Generation connected on grid system

Soru and Wala Ndimu

3.

There is 1 sites having Individual Solar PV will potential for Micro Hydro but be efficient not efficient, intake distance

Sodana

1-2 Government of Indonesia / ADB – 12/14/15

Page 137 of 396

1. Summary. . ..

more than 4 km from the settlement and relative spreadly 4.

There are 5 sites have no potential head for Micro Hydro Development and more efficient for grid extention

Extended grid will be Wula, Kawangu, mostly recommended, Praibakul, We Luri only 2 Km distance from and We Kombaka the existing PLN grid.

5.

There are 6 sites have no Isolated or indivisual potential head for Micro Hydro system is recommended Development for these sites (Genset/PLTS)

Katikutana, Kutikula, Mabaha Bakul, maidang 1 and 2, Mabatapuhu and Wangga.

Note: Kananggar is canceled due PLN will developed Micro Hydro on this site. Wambidi is not accessible for site survey.

1.4

ANNEXES

1. List of 100 potential sites based on watershed 2. Result of Desk study using Google Earth 3. Field survey assessment form


Page 138 of 396

2.

LIST OF SITES CONSIDERED

Kabupaten

Region

Desa

Mini_Grid_ Min_Height Max_Height Watershed_ ID _m _m Area_Km2 60 62.5 300 209.41

Head

SUMBA TIMUR

Eastern

MAIDANG

237.5

SUMBA TIMUR

Eastern

LUKU KAMARU

66

87.5

425

117.56

337.5

SUMBA TIMUR

Eastern

MAIDANG

59

100

312.5

179.56

212.5

SUMBA TIMUR

Eastern

KALAMBA

109

212.5

400

184.12

187.5

SUMBA TENGAH

Western

SORU

113

350

450

312

100

SUMBA TIMUR

Eastern

KUKI TALU

47

150

350

130.74

200

SUMBA TIMUR

Eastern

PABERA MANERA

26

300

550

95.19

250

SUMBA TIMUR

Eastern

UMAMANU

55

12.5

100

234.94

87.5

SUMBA TIMUR

Eastern

WAIKANABU

46

137.5

400

76.59

262.5

SUMBA TIMUR

Eastern

MAHU BOKUL

54

87.5

300

89.9

212.5

SUMBA TENGAH

Western

WEE LURI

128

250

525

64.55

275

SUMBA BARAT DAYA

Western

DENDUKA

97

25

187.5

107.89

162.5

SUMBA TENGAH

Western

MADERI

129

112.5

512.5

43.07

400

SUMBA TIMUR

Eastern

KATIKUTANA

25

437.5

787.5

46.58

350

SUMBA TIMUR

Eastern

PRAI BAKUL

134

37.5

150

116.5

112.5

SUMBA BARAT DAYA

Western

WALLA NDIMU

107

62.5

187.5

101.62

125

SUMBA TIMUR

Eastern

KARITA

36

212.5

425

48.72

212.5

SUMBA TIMUR

Eastern

PULU PANJANG

65

437.5

550

84.14

112.5

SUMBA TIMUR

Eastern

KAWANGU

91

12.5

87.5

123.9

75

SUMBA TIMUR

Eastern

TAMBURI

24

212.5

412.5

42.82

200

SUMBA BARAT DAYA

Western

DANGGA MANGO

102

200

237.5

217.87

37.5

SUMBA TIMUR

Eastern

LA HIRU

18

225

425

40.46

200

SUMBA TIMUR

Eastern

WAIKANABU

32

237.5

462.5

32.86

225

SUMBA TIMUR

Eastern

WATU PUDA

38

62.5

175

64.02

112.5

SUMBA TIMUR

Eastern

KATIKU LUKU

45

350

625

23.14

275

Indicator of Potential

49,735 39,677 38,157 34,523 31,200 26,148 23,798 20,557 20,105 19,104 17,751 17,532 17,228 16,303 13,106 12,703 10,353 9,466 9,293 8,564 8,170 8,092 7,394 7,202 6,364 2-1 Government of Indonesia / ADB – 12/14/15

Page 139 of 396

2. List of Sites Considered. . ..

Kabupaten

Region

Desa

Mini_Grid_ Min_Height Max_Height Watershed_ ID _m _m Area_Km2 56 250 337.5 71.05

SUMBA TIMUR

Eastern

LAI MBONGA

SUMBA TIMUR

Eastern

WAIMBIDI

61

262.5

SUMBA TENGAH

Western

PONDOK

125

287.5

SUMBA TIMUR

Eastern

KALAMBA

114

112.5

462.5

Head 87.5

30.63

200

400

53.4

112.5

212.5

56.9

100

SUMBA BARAT DAYA

Western

WEE KOMBAKA

124

300

387.5

64.56

87.5

SUMBA TIMUR

Eastern

KANANGGAR

21

425

612.5

28.96

187.5

SUMBA TIMUR

Eastern

KOTAK KAWAU

68

37.5

112.5

71.33

75

SUMBA BARAT DAYA

Western

DELO

110

237.5

337.5

50.08

100

SUMBA TIMUR

Eastern

MAU BOKUL

49

337.5

500

29.43

162.5

SUMBA TENGAH

Western

WANGGA WAIYENGU

123

200

225

189.35

25

SUMBA TIMUR

Eastern

MBATAPUHU

117

300

387.5

51.17

87.5

SUMBA TIMUR

Eastern

W U L A

8

12.5

100

49.82

87.5

SUMBA TIMUR

Eastern

LAINJANJI

6

12.5

87.5

57.5

75

SUMBA TIMUR

Eastern

LAINJANJI

1

12.5

187.5

24.58

175

SUMBA TIMUR

Eastern

MAHU BOKUL

51

400

625

16.01

225

SUMBA TIMUR

Eastern

KURUWAKI

12

25

287.5

13.33

262.5

SUMBA TIMUR

Eastern

KAMANGGIH

34

412.5

637.5

14.95

225

SUMBA TIMUR

Eastern

TAPIL

33

200

375

19.17

175

SUMBA TIMUR

Eastern

MBATAKAPIDU

76

125

250

24.94

125

SUMBA BARAT

Western

SODANA

85

50

162.5

27.46

112.5

SUMBA TIMUR

Eastern

KALAMBA

111

212.5

412.5

14.02

200

SUMBA TIMUR

Eastern

WAIMBIDI

63

200

400

13.96

200

SUMBA BARAT

Western

SODANA

93

62.5

262.5

13.36

200

SUMBA BARAT DAYA

Western

KAHALE

88

12.5

87.5

34.04

75

SUMBA BARAT DAYA

Western

WEE LONDA

138

12.5

50

66.42

37.5


6,217 6,126 6,008 5,690 5,649 5,430 5,350 5,008 4,782 4,734 4,477 4,359 4,313 4,302 3,602 3,499 3,364 3,355 3,118 3,089 2,804 2,792 2,672 2,553 2,491


Page 140 of 396


Kabupaten

Region

Desa

SUMBA TIMUR

Eastern

KATIKU LUKU

SUMBA TIMUR

Eastern

MBATAKAPIDU

Mini_Grid_ Min_Height Max_Height Watershed_ ID _m _m Area_Km2 31 625 750 19.16 78

350

475

19.07

Head 125 125

SUMBA TIMUR

Eastern

HANGGARORU

23

87.5

112.5

93.09

25

SUMBA TIMUR

Eastern

PRAI KALALA

22

387.5

612.5

8.78

225

SUMBA TIMUR

Eastern

LAI MBONGA

57

287.5

350

30.72

62.5

SUMBA TIMUR

Eastern

MATAWAI AMAHU

64

425

612.5

10.08

187.5

SUMBA TENGAH

Western

MADERI

127

200

400

9.41

200

SUMBA TIMUR

Eastern

KATAKA

44

287.5

487.5

9.09

200

SUMBA TIMUR

Eastern

MEO RUMBA

40

400

487.5

20.36

87.5

SUMBA TIMUR

Eastern

WANGGA BEWA

13

75

162.5

20.06

87.5

SUMBA TIMUR

Eastern

PRAIMADITA

11

12.5

125

14.67

112.5

SUMBA TIMUR

Eastern

WATU PUDA

43

37.5

200

9.78

162.5

SUMBA TIMUR

Eastern

LAINJANJI

3

12.5

137.5

12.4

125

SUMBA TIMUR

Eastern

NGGONGI

7

37.5

50

123.69

12.5

SUMBA TIMUR

Eastern

MONDU LAMBI

53

25

75

30.45

50

SUMBA TIMUR

Eastern

WAIKANABU

35

187.5

425

6.24

237.5

SUMBA TIMUR

Eastern

LAILUNGGI

17

187.5

287.5

14.21

100

SUMBA TIMUR

Eastern

LA HIRU

19

187.5

437.5

5.35

250

SUMBA TIMUR

Eastern

TARIMBANG

39

37.5

150

11.23

112.5

SUMBA TIMUR

Eastern

MAU BOKUL

41

400

600

6.15

200

SUMBA BARAT

Western

PATIALA BAWA

70

12.5

112.5

12.26

100

SUMBA BARAT

Western

GAURA

72

0

125

9.69

125

SUMBA BARAT

Western

BALI LEDO

118

400

487.5

13.8

87.5

SUMBA BARAT

Western

WANOKAZA

121

437.5

637.5

5.5

200

SUMBA TIMUR

Eastern

WAHANG

16

12.5

62.5

21.52

50


2,395 2,384 2,327 1,976 1,920 1,890 1,882 1,818 1,782 1,755 1,650 1,589 1,550 1,546 1,523 1,482 1,421 1,338 1,263 1,230 1,226 1,211 1,208 1,100 1,076


Page 141 of 396


Kabupaten

Region

Desa

Mini_Grid_ Min_Height Max_Height Watershed_ ID _m _m Area_Km2 48 12.5 37.5 41.02

Head

SUMBA TIMUR

Eastern

MONDU LAMBI

SUMBA TIMUR

Eastern

RAMUK

15

125

237.5

SUMBA TIMUR

Eastern

KATIKUTANA

29

387.5

512.5

7.7

125

SUMBA TIMUR

Eastern

PRAIMADITA

9

25

62.5

25.45

37.5

SUMBA BARAT

Western

WETANA

77

25

125

8.6

100

SUMBA BARAT

Western

NGADU PADA

133

150

250

8.5

100

SUMBA TENGAH

Western

WELUK PRAI MEMANG

122

375

450

10.69

75

SUMBA BARAT

Western

BALI LEDO

120

375

487.5

7.01

112.5

SUMBA BARAT

Western

SODANA

92

37.5

212.5

4.42

175

SUMBA BARAT DAYA

Western

TOTOK

130

250

462.5

3.48

212.5

SUMBA TENGAH

Western

KONDA MALOBA

69

0

25

29.24

25

SUMBA TIMUR

Eastern

MBATAKAPIDU

82

187.5

300

6.26

112.5

SUMBA TIMUR

Eastern

TAMBURI

27

187.5

337.5

4.67

150

8.65

25 112.5

SUMBA TIMUR

Eastern

TARIMBANG

30

0

25

27.35

25

SUMBA TIMUR

Eastern

MAIDANG

62

62.5

200

4.76

137.5

SUMBA BARAT DAYA

Western

WALLA NDIMU

104

62.5

112.5

12.77

50

SUMBA TENGAH

Western

WENDEWA BARAT

139

12.5

162.5

4.2

150

SUMBA TENGAH

Western

SORU

115

375

437.5

9.68

62.5

SUMBA BARAT

Western

SODANA

96

137.5

362.5

2.63

225

SUMBA TIMUR

Eastern

KAYURI

42

12.5

50

15.63

37.5

SUMBA BARAT

Western

DEDE KADU

95

87.5

237.5

3.71

150

SUMBA TIMUR

Eastern

PRAIMADITA

5

12.5

87.5

7.12

75

SUMBA BARAT DAYA

Western

NOHA

119

112.5

125

39.91

12.5

SUMBA BARAT

Western

LABOYA DETE

89

25

162.5

3.56

137.5

SUMBA TIMUR

Eastern

MATAWAI MARINGU

58

100

162.5

7.53

62.5


1,026 973 963 954 860 850 802 789 774 740 731 704 701 684 655 639 630 605 592 586 557 534 499 490 471


Page 142 of 396


Kabupaten

Region

Desa

SUMBA BARAT

Western

BALI LOKU

SUMBA BARAT

Western

LOLO WANO

SUMBA TIMUR

Eastern

SUMBA TENGAH

Western

Mini_Grid_ Min_Height Max_Height Watershed_ ID _m _m Area_Km2 71 0 125 3.74

Head 125

136

100

212.5

4.01

112.5

NGARU KANORU

28

175

350

2.57

175

TANA MBANAS

135

225

300

5.89

75

SUMBA BARAT

Western

WELIBO

84

137.5

400

1.65

262.5

SUMBA TIMUR

Eastern

MATAWAI MARINGU

52

137.5

162.5

16.34

25

SUMBA TIMUR

Eastern

KAMBATA WUNDUT

87

450

462.5

32.53

12.5

SUMBA BARAT

Western

WETANA

86

137.5

312.5

2.25

175

SUMBA BARAT

Western

MAMODU

80

12.5

62.5

7.49

50

SUMBA TIMUR

Eastern

PRAIMADITA

4

0

62.5

5.91

62.5

SUMBA BARAT

Western

KAREKA NDUKU

126

350

550

1.81

200

SUMBA TENGAH

Western

MBILUR PANGADU

99

500

525

13.79

25

SUMBA BARAT DAYA

Western

DENDUKA

108

187.5

225

9.19

37.5

SUMBA BARAT

Western

WEE KAROU

98

162.5

387.5

1.43

225

SUMBA BARAT DAYA

Western

KARUNI

132

187.5

337.5

2.14

150

SUMBA BARAT

Western

HUPU MADA

90

50

137.5

3.48

87.5

SUMBA BARAT DAYA

Western

DANGGA MANGO

101

125

175

5.39

50

SUMBA TIMUR

Eastern

KAWANGU

94

12.5

62.5

5.02

50

SUMBA TIMUR

Eastern

LAINJANJI

2

12.5

75

3.93

62.5

SUMBA TIMUR

Eastern

MATAWAI AMAHU

67

375

475

2.18

100

SUMBA TIMUR

Eastern

MONDU LAMBI

50

12.5

62.5

4.35

50

SUMBA TIMUR

Eastern

NGGONGI

10

62.5

100

5.34

37.5

SUMBA BARAT

Western

BALI LEDO

116

425

475

3.32

50

SUMBA BARAT DAYA

Western

WAI HA

103

87.5

137.5

3.22

50

SUMBA BARAT DAYA

Western

WAI HA

105

62.5

150

1.75

87.5


468 451 450 442 433 409 407 394 375 369 362 345 345 322 321 305 270 251 246 218 218 200 166 161 153


Page 143 of 396


Kabupaten

Region

Desa

SUMBA BARAT DAYA

Western

MANGGA NIPI

SUMBA TIMUR

Eastern

N A P U

Mini_Grid_ Min_Height Max_Height Watershed_ ID _m _m Area_Km2 131 37.5 50 11.19 137

187.5

212.5

Head 12.5

5.27

25

SUMBA BARAT

Western

GAURA

79

87.5

150

2.09

62.5

SUMBA BARAT DAYA

Western

KAHALE

83

37.5

112.5

1.66

75

SUMBA TENGAH

Western

PRAI KAROKU JANGGA

106

400

475

1.57

75

SUMBA TIMUR

Eastern

WATU PUDA

37

387.5

462.5

1.56

75

SUMBA BARAT

Western

PATIALA DETE

81

100

300

0.57

200

SUMBA BARAT DAYA

Western

DANGGA MANGO

100

100

150

2.05

50

SUMBA BARAT

Western

WETANA

73

0

100

0.76

100

SUMBA BARAT

Western

BALI LOKU

75

0

25

2.88

25

SUMBA BARAT

Western

GAURA

74

0

87.5

0.61

87.5

SUMBA TIMUR

Eastern

LAMBAKARA

14

18.75

50

1.2

31.25

SUMBA TENGAH

Western

SORU

112

387.5

375

44.79

0

SUMBA TIMUR

Eastern

WAHANG

20

387.5

100

6.31

0


140 132 131 125 118 117 114 103 76 72 53 38 ‐560 ‐1,814


Page 144 of 396


450 400

Catchment Area, km2

350 300 250

Primary ‐ Western

200

Primary ‐ Eastern Secondary ‐ Western

150

Secondary ‐ Eastern

100 50 0 0

50

100

150

200

250

300

350

Head, m


Page 145 of 396

3.

DESK STUDY RESULTS

Kabupaten

Region

Desa

Mini_Grid _ID

SUMBA TIMUR

Eastern

MAIDANG

60

SUMBA TIMUR

Eastern

LUKU KAMARU

66

SUMBA TIMUR

Eastern

MAIDANG

59

SUMBA TIMUR

Eastern

KALAMBA

109

SUMBA TENGAH

Western

Soru

113

SUMBA TIMUR

Eastern

KUKI TALU

47

SUMBA TIMUR

Eastern

PABERA MANERA

26

SUMBA TIMUR

Eastern

UMAMANU

55

SUMBA TIMUR

Eastern

WAIKANABU

46

SUMBA TIMUR

Eastern

MAHU BOKUL

54

SUMBA TENGAH

Western

WEE LURI

128

SUMBA BARAT DAYA

Western

DENDUKA

97

SUMBA TENGAH

Western

MADERI

129

SUMBA TIMUR

Eastern

KATIKUTANA

25

SUMBA TIMUR

Eastern

PRAI BAKUL

134

SUMBA BARAT DAYA Western

WALLA NDIMU

107

SUMBA TIMUR

Eastern

KARITA

36

SUMBA TIMUR

Eastern

PULU PANJANG

65

SUMBA TIMUR

Eastern

KAWANGU

91

SUMBA TIMUR

Eastern

TAMBURI

24

Distance from Main Road (km)

House clustering Characteristic

Number of houses nearby river < 500 m

15 10 18 10.3 8.6 20 < 18.5 16 20 < 18 12.8 10.5 12 < 20 1.6 4.1 19 6.4 3.4 20 <

Centralized Spreadly Centralized Spreadly Centralized Spreadly Centralized Spreadly Centralized Centralized Centralized Spreadly Spreadly Centralized Centralized Centralized Centralized Centralized Centralized Spreadly

50< No population 30< < 10 60 < < 10 30 < No population 30< 40< 50 < < 20 < 10 20‐30 60 < 60 < 30< 50 < 50 < < 10

Conclusion

Selected Not Recommended Selected Not Recommended Selected Not Recommended Selected Not Recommended Selected Selected Selected Not Recommended Not Recommended Selected Selected Selected Selected Selected Selected Not Recommended 3-1

Government of Indonesia / ADB – 12/14/15

Page 146 of 396

Kabupaten

Region

Desa

Mini_Grid _ID

SUMBA BARAT DAYA

Western

DANGGA MANGO

102

SUMBA TIMUR

Eastern

LA HIRU

18

SUMBA TIMUR

Eastern

WAIKANABU

32

SUMBA TIMUR

Eastern

WATU PUDA

38

SUMBA TIMUR

Eastern

KATIKU LUKU

45

SUMBA TIMUR

Eastern

LAI MBONGA

56

SUMBA TIMUR

Eastern

WAIMBIDI

61

SUMBA TENGAH

Western

PONDOK

125

SUMBA TIMUR

Eastern

KALAMBA

114

SUMBA BARAT DAYA Western

WEE KOMBAKA

124

SUMBA TIMUR

Eastern

KANANGGAR

21

SUMBA TIMUR

Eastern

KOTAK KAWAU

68

SUMBA BARAT DAYA

Western

DELO

110

SUMBA TIMUR

Eastern

MAU BOKUL

49

SUMBA TENGAH

Western

WANGGA WAIYENGU

123

SUMBA TIMUR

Eastern

MBATAPUHU

117

SUMBA TIMUR

Eastern

W U L A

8

SUMBA BARAT

Western

SODANA

85

SUMBA BARAT

Western

SODANA

93

SUMBA BARAT DAYA

Western

KAHALE

88

Distance from Main Road (km)

House clustering Characteristic

Number of houses nearby river < 500 m

Conclusion

9.7 16.1 32.5 10.2 22.5 16.1 10 9.7 7.8 7.3 20.2 7.8 9.3 22.5 8.9 13.6 2 3.4 5.7 7.8

Spreadly Spreadly Spreadly Spreadly Spreadly Spreadly Centralized Centralized Spreadly Centralized Centralized Spreadly Spreadly Centralized Centralized Centralized Centralized Centralized Spreadly Spreadly

< 20 < 20 < 20 < 10 < 10 No population 40 < 30< < 10 30 < 30 < < 10 20< 30< 30< 20< 30‐40 40 < 20< 20<

Not Recommended Not Recommended Not Recommended Not Recommended Not Recommended Not Recommended Selected Selected Not Recommended Selected Selected Not Recommended Not Recommended Selected Selected Selected Selected Selected Not Recommended Not Recommended


Page 147 of 396

4.

INDIVIDUAL REPORTS FOR EACH SITE

4.1

PABERAMANERA

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 26 Kampung / Desa:MAUMARU/PABERAMANERA Koordinat GPS : S 10°00’10.4” E 120°29’23.4”

Kecamatan :Paberiwai Kabupaten :Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 27 June 2015

1. Karakteristik DAS Aliran air

Air sepanjang musim dengan debit air besar. Air berkurang pada berkurang saat musim kemarau (Juli-Oktober), tetapi berkurang tidak terlalu signifikan.

Nama Sungai

Paberamanera

Debit air (data sekunder)

Tdk ada data

Curah hujan/Bulanbasah

Tdk ada data

Perkiraan head

26 meter

2. Sosial Ekonomi Jumlah penduduk / KK

155 KK

Mata Pencaharian utama

Petani Ladang (jagung, padi ladang, ubi kayu), budidaya tanaman umur panjang (kemiri, sirih, pinang, kelapa, kopi)

Pendidikan rata2

Sebagian besar pendidikan SD, sebagian kecil SMP dan SMA

Rata2 jml org / KK

5 Orang

Pendapatan rata2/bln/KK

Tidak menentu

Komoditas utama

Jagung, kemiri, sirih, pinang, kelapa, kopi

Sumber energy saatini

Menggunakan Pelita, genset (sudah rusak)

Potensi industry

Kerajinan anyaman, pengolahan biji kemiri

Organisasimasyarakat

Tananua

3. FasilitasUmum


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4. Individual Reports For Each Site

BalaiDesa

1 unit

Puskesmas/posyandu

1 unit Pustu, 4 unit Posyandu

Sekolah

1 unit (SD)

Gereja/masjid

2 unit (gereja)

4. Aksesibilitas Jarak lokasi ke Jalan Provinsi

101 KM (Waingapu – Paberamanera)

Jarak lokasi ke Jalan Desa

700 meter (dari Gedung SD – Lokasi)

Kondisi jalan terdekat menuju lokasi

Badan Jalan 700 meter

Jarak lokasi ke jaringan LV/MV PLN

23 km (dari Jaringan PLN Melolo – Lokasi)

5. Informasi awal system desain dan Operasi Pemeliharaan Jarak intake (sungai) – pemukiman

700 km dari pemukiman

Jumlah rumah & bangunan

150 Rumah, 5 Bangunan

Ketersediaan Material lokal (batu/pasir/semen, dll)

Ada, dan mudahdidapat

Ketersediaan tenagaker jalokal

Cukup

Gambaran pembiayaan O M

Bersedia swadaya.


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6. Fotolokasi

Terjunan 1

SD Paberamanera

Jondisi Sungai di lokasi survey

Terjunan 2 dan 3

Lokasi Perkampungan


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7. Peta Lokasi

8. Sketsalokasi (sungai, jalan, pemukiman)

9. Informan : Benyamin Landumarada


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10. Kesimpulan : Lokasi layak untuk dibangun pembangkit mikro hidro

4.2

KARITA

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 36 Kampung / Desa :Karita Koordinat GPS : S 09°55’59.6” E120°02’38.5”

Kecamatan :Tabundung Kabupaten : Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 28 Juni 2015


Air sepanjang musim dengan debit air cukup, berdasarkan temuan lapangan tidak di temukan bukti banjir pada bibir sungai. Air berkurang pada saat musim kemarau (JuliNovember)

Nama Sungai

Mau Lewa


Tdk ada data


Tdkada data

Perkiraan head

Ada head : 23 meter


55 KK (Desa Karita), 32 KK (Desa Tapil)


Petani Ladang dan Peternak (Tradisional)

Pendidikan rata-rata


Rata2 jml org / KK

6 Orang


Tidak menentu, sangat tergantung hasil pertanian/ternak

Komoditas utama

Jagung, Ubi Kayu dan Ternak Besar (Kuda, Sapi, Kerbau), Kambing dan Babi

Sumber energy saat ini

Menggunakan Lampu Pelita, Sehen (sebagian besar sudah di tarik PLN)


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Potensi industry

Pengolahan Jagung


Ada LSM Yayasan Tananua

Lainnya

-

3. FasilitasUmum Balai Desa

1 unit

Puskesmas/posyandu


Sekolah

1 unit (SD)

Gereja/masjid

1 unit (gereja)

Lainnya

-

4. Aksesibilitas Jarak lokasike jalan Kabupaten

105 KM (dari Kota Waingapu – Simpang Karita)


1 KM (dari Simpang Karita – Lokasi)


1 KM (jalan pengerasan)


15 km (dari Jaringan PLN Malahar – Lokasi)

5. Informasi awal sistemd esain dan Operasi Pemeliharaan Jarak intake (sungai) – pemukiman

Arah Desa Karita (Kampung Maulewa) 1 km, Arah Desa Tapil (Kampung Desa Tapil) 5 KM


Desa Karita 59 Rumah, 4 Bangunan, Desa Tapil 30 Rumah 3 Bangunan.


Ada, dan mudahd idapat

Ketersediaan tenaga kerja lokal

Cukup


Bersedia dengan biaya swadaya.


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6.

Foto lokasi

Kondisi Sungai Mau Lewa di Desa Karita, Kecamatan Tabundung, Kab. Sumba Timur

Simpang Karita

Kondisi Jalan Menuju Lokasi

7. Peta Lokasi


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8. Sketsa lokasi (sungai, jalan, pemukiman)

9. Keterangan lain:tidak ada 10. Informan : Bapak K. Karamula dan Bapak Hillu K. Windi 11. Kesimpulan : Lokasi layak untuk dikaji lebih lanjut untuk pembangunan mikro hidro

4.3

WAIKANABU

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 46 Kampung / Desa:MANDORA/WAIKANABU Koordinat GPS: S 09°57’43.9” E 120°07’48.0”

Kecamatan :Tabundung Kabupaten : Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 30 June 2015


Air sepanjang musim dengan debit air besar. Air berkurang pada berkurang saat musim kemarau (Juli-Oktober), tetapi tidak terlalu signifikan.

Nama Sungai

Waikanabu


Tdk ada data


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Curah hujan/Bulan basah

Tdkada data

Perkiraan head

10 meter

2. Sosia Ekonomi Jumlahpenduduk / KK

90 KK


Petani sawah dan Petani Ladang

Pendidikan rata2


Rata2 jml org / KK

6 Orang


Tidak menentu

Komoditas utama

Padi Sawah, Padi ladang dan Jagung


Pelita

Potensi industry

Penggilingan Padi


-

3. FasilitasUmum BalaiDesa

1 unit

Puskesmas/posyandu


Sekolah

1 unit (SD)

Gereja/masjid

2 unit (gereja)

4. Aksesibilitas Jarak lokasi ke jalan Kabupaten

16 KM (Simpang Waikanabu Malahar – Desa Waikanabu)

Jarak lokasi ke Jalan Provinsi

131 KM (dari Kota Waingapu – Desa Waikanabu)


50 meter (dari jalan Desa)


Aspal Putus-putus 4-9 Government of Indonesia / ADB – 12/14/15

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5. InformasiawalsistemdesaindanOperasiPemeliharaan Jarak intake (sungai) – pemukiman

200 m dari pemukiman




Ada, dan mudah didapat


Cukup


Bersedia swadaya.

6. Foto lokasi

Bentuk Sungai Waikanabu di Kabupaten Sumba Timur


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Kondisi pemukiman di Desa Waikanabu di Kabupaten Sumba Timur

Pemukiman Warga

Kondisi Akses jalan di Desa Waikanabu, Sumba Timur


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7. Peta Lokasi



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9. Informan : Hamba Pullu 10. Kesimpulan :Lokasi Layak untuk dibangun pembangkit mikro hidro

4.4

PULU PANJANG

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 65 Kecamatan : Nggaha Ori Anggu Kampung / Desa: Pulu Panjang / Pulu Panjang Kabupaten : Sumba Timur Koordinat GPS : S 09.46.257 E 120.06.806 Surveyor : Warin & Umbu Bahi Tanggal Survey : 23 April 2015 1. Karakteristik DAS Kondisi aliran air Air sepanjang musim, kadang‐kadang banjir saat musim hujan (Januari‐April) dan debit air berkurang saat musim kemarau (Juli‐ Okt) Nama Sungai Pulu Panjang Dimensi Sungai Lebar 6‐8 m; kedalaman air 50‐80 cm Perkiraan head 22 m. Diukur dari selisih elevasi sungai dg jarak 100‐200m dg alat GPS garmin. Ada air terjun tapi tidak terlalu tinggi (2m). 2. Sosial Ekonomi Jumlah penduduk / KK 228 KK (total di Desa), khusus yang tinggal di Kampung Pulu Panjang 149 KK. Ada 138 KK di lampung lain yang akan mekar menjadi Desa Baru Paomba. Mata Pencaharian utama Petani dan Ternak Pendidikan rata2 SD (sebagian besar) dan SMP (sebagian kecil) Rata‐rata jml org / KK 5‐6 jiwa Pendapatan rata2/bln/KK Tidak tentu, tergantung hasil panen sawah dan penjualan ternak. Komoditas utama Jagung, ubi, sapi, kerbau, babi dan kuda, kambing. Potensi industri Industri pemipil jagung Organisasi masyarakat Tidak ada Fasilitas Umum 2 Gedung Sekolah (SD & SMP), 1 Gereja, 1 Pustu (Puskesmas Pembantu), 1 Balai Desa Keterangan Lain Baru saja ada pergantian Kepala Desa 3. Kondisi Pemakaian Energy Saat Ini Jarak dengan Jaringan PLN

Sumber listrik saat ini Belanja energy listrik

10 Km dari jaringan MV (Jalan raya Waingapu‐Lewa), 9 Km dari LV (berhenti pada 1 km dari jalan raya). Genset (penduduk yang mampu),lampu pelita (sebagian besar penduduk). Genset = 5 Lt BBM/hari; Pelita= 2 Lt per bulan. 4-13 Government of Indonesia / ADB – 12/14/15

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Keterangan Lainnya

Pernah mendapat SEHEN dari PLN, namun ditarik kembali oleh PLN karena pembayaran tidak lancar. Pernah mendapat bantuan mesin Genset dari Pemda namun sudah rusak (2012).

4. Akses Jalan Jarak lokasi ke jalan Utama Jarak lokasi ke Jalan Desa Kondisi jalan menuju ke lokasi

10 Km dari Jalan raya Waingapu – Waikabubak 100‐300 m dari pusat Desa 10 Km jalan menuju desa kombinasi aspal dan jalan tanah/batu. Kondisi baik dan bisa dilalui kendaraan roda 4

5. Informasi awal sistem desain, operasi dan pemeliharaan Jarak intake (sungai) – pemukiman Jumlah rumah & bangunan Ketersediaan Material lokal Ketersediaan tenaga kerja lokal Gambaran pembiayaan O M

Perkiraan kapasitas turbin

100‐300 m 55 (kampung terdekat) dan 78 (kampung tetangga, jarak 1 km dari lokasi) Ada, dan mudah didapat (30 km dari Kota Waingapu) Cukup Bersedia dengan swadaya namun harus dibina dan dipersiapkan. Pengalaman kerusakan Genset bantuan Pemda dan ditariknya SEHEN PLN harus dijadikan pertimbangan. 20‐30 Kw


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6. Peta lokasi

Jalan Raya Waikabubak Waingapu

Desa Pulu Panjang, Kec. Nggaho Orianggo, Sumba Timur

7. Sketsa / Denah lokasi (sungai, jalan, pemukiman)

ke dusun lain (Paomba)

S.Pulu

200m Keterangan: Lokasi Intake (bendung)

ke main road (10 km)

Lokasi Power house (turbin) 8. Informan:

1. Umbu Djuanda (Kepala Desa Pulu Panjang); 2. Hoki Ladan Rime (Warga)


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9. Foto Lokasi Lokasi power house, ada air terjun (2m) Gedung Sekolah SMP Pulu Panjang Jalan menuju Desa Pulu Panjang

Lokasi Intake, Sungai Pulu Panjang

Lokasi power house, ada air terjun (2m)

Gedung Sekolah SMP Pulu Panjang

Kepala Desa Pulu Panjang (tengah)

SEHEN yang sdh ditarik oleh PLN 4-16 Government of Indonesia / ADB – 12/14/15

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10. Kesimpulan & Rekomendasi Layak dibangun Pembangkit Listrik Mikro Hidro dengan system mini grid kapasitas 20‐30 Kw. Potensi penerima manfaat 55 rumah dan bisa diperluas / ditambah 78 rumah yang berlokasi di kampung Paomba (1.5 km). Perlu dilanjutkan dengan FS untuk penyusunan DED

4.5

PONDOK

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 125 Kampung / Desa:MANALUSU/PONDOK Koordinat GPS : S 10°00’10.4” E 120°29’23.4”

Kecamatan :Umbu Ratu Nggai Barat Kabupaten :Sumba Tengah Surveyor : Umbu Bahi Tanggal survey : 1 July 2015


Air sepanjang musim dengan debit air besar. Air berkurang pada berkurang saat musim kemarau (Juli-Oktober), tetapi tidak signifikan.

Nama Sungai

Paberamanera


Tdkada data


Tdkada data

Perkiraan head

7 meter

2. SosialEkonomi Jumlah penduduk / KK

200 KK


Petani sawah

Pendidikan rata2


Rata2 jml org / KK

5 Orang


Tidak menentu

Komoditas utama

Padi Sawah


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Menggunakan Pelita

Potensi industry

Penggilingan Padi


-


1 unit

Puskesmas/posyandu


Sekolah

1 unit (SD)

Gereja/masjid

1 unit (gereja)

4. Aksesibilitas Jarak lokasi ke Jalan Provinsi

11 KM (Waibakul – Pondok)

Jara klokasi keJalan Desa

500 meter (dari Kantor Desa – Lokasi)


Jalan pengerasan


10 km (dari Jaringan PLN Waibakul – Lokasi)


500 m dari pemukiman






Cukup


Bersedia swadaya.


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6. Fotolokasi

Kondisi sungai Pabera Manera di Desa Pondok, Sumba Timur

Kondisi Pemukiman Warga di Desa Pondok


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7. Peta Lokasi


9. Informan : Kawalu Ndaungu 10. Kesimpulan : Lokasi layak untuk dibangun pembangkit mikro hidro


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4.6

KATIKUTANA

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 25 Kampung / Desa:LA TIRING/KATIKUTANA Koordinat GPS : S 09°58’54.1” E120°15’54.1”

Kecamatan :MATAWAILAPAU Kabupaten : Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 26 June 2015


Air sepanjang musim dengan debit air besar. Terjadi pengurangan Debit Juli-November, tetapi tidak terlalu signifikan.

Nama Sungai

La Tiring


Tdk ada data


Tdk ada data

Perkiraan head

Tidak ada head


100 KK


Petani g (jagung, kemiri, siri, pinang, padi ladang, padi sawah) dan Peternak (Tradisional)

Pendidikan rata2


Rata2 jml org / KK

5 Orang


Tidak menentu

Komoditas utama

Jagung, kemiri, siri, pinang, padi ladang, padi sawah, ubi kayu dan Peternak


Menggunakan Pelita

Potensi industry

Olah pasca panen seperti jagung, kemiri

Organisasi masyarakat

Ada LSM Yayasan Tananua


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Lainnya 3. Fasilitas Umum Balai Desa

-

Puskesmas/posyandu


Sekolah

1 unit

Gereja/masjid

5 unit (gereja)

Lainnya

-


9 KM (dari simpang kantor kecamatan matawai lapau – Lokasi)


75 KM (dari Kota Waingapu – Simpang Kantor Kecamatan Matawailapau)


500 meter


Badan jalan dan bisa di akses dengan kendaraan tertentu

Jaraklokasi ke jaringan LV/MV PLN

7 km (dari Jaringan PLN Kecamatan Matawailapau– Lokasi)

5. Informasi awal sistem desain dan Operasi Pemeliharaan Jarak intake (sungai) – pemukiman

500 meter dari pemukiman

Jumlah rumah& bangunan

95 rumah dan 7 bangunan




Cukup


Bersedia swadaya.


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6. Foto lokasi Lokasi tidak bisa di foto karena pada saat sampai ke lokasi kondisi sudah gelap , jam 17.50 sore

7. Peta Lokasi



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9. Keterangan lain:tidak ada 10. Informan : Ayub Ndawa Radji 11. Kesimpulan : Lokasi tidak layak untuk dibangun pembangkit mikro hidro, tidak ditemukan head di sekitar lokasi desa. Lebih direkomendasikan untuk PLTS.

4.7

KUKI TALU

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 47 Kampung / Desa:Kuki Talu Koordinat GPS : S 09°54’19.4” E120°08’40.9”

Kecamatan :Tabundung Kabupaten : Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 28 June 2015


Air sepanjang musim dengan debit air cukup, berdasarkan pengakuan warga setempat sering terjadi banjir pada puncak musim hujan. Air berkurang pada musim kemarau (JuliNovember)

Nama Sungai

Sungai Marabung


Tdk ada data


Tdkada data

Perkiraan head

Ada head rendah( < 5m) namun debit air sungai kecil


110 KK


Petani Ladang, sawah dan Peternak (Tradisional)

Pendidikan rata2


Rata2 jml org / KK

5 Orang


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Tidak menentu (tergantung curah hujan)

Komoditas utama

Jagung, Padi Sawah dan Ternak Besar (Kuda, Sapi, Kerbau) dan Babi


Listrik Genset (bantuan PNPM tahun 2012)

Potensi industry

Penggilingan Padi


Tidak Ada


1 unit

Puskesmas/posyandu


Sekolah

1 unit

Gereja/masjid

5 unit (gereja)


8 KM (Simpang Kukitalu – Lokasi)


120 KM (dari Kota Waingapu – Simpang Kukitalu)

JaraklokasikeJalanDesa

1 KM (dari pusat Desa ke Lokasi)


Dari Pusat Desa – Lokasi hanya ada badan jalan




300 meter


Desa Karita 90 Rumah, 5 Bangunan




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Ketersediaantenagakerjalokal

Cukup

Gambaranpembiayaan O M

Bersediaswadaya.

6. Foto lokasi

Kondisi Sungai

Sarana Penerangan Jalan Warga, Genset PNPM

Kondisi Akses Jalan

Salah satu cabang sungai lain yang ada head tetapi airnya sangat kecil (dekat dengan lokasi survei)


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7. Peta Lokasi


9. Informan : Bapak ND Hamandika 10. Kesimpulan : Lokasi tidak layak untuk dibangun pembangkit mikro hidro, head rendah dan volume air sungai tidak cukup.


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4.8

MAHU BOKUL

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 54 Kecamatan: Kambata Mapambuhang Kampung / Desa:MBOTA NITU /Maidang/Mahubokul Kabupaten : Sumba Timur Koordinat GPS : S 09°52’02.2” E120°14’04.5” Surveyor : Umbu Bahi Tanggal survey : 29 June 2015


Air sepanjang musim dengan debit air besar, sering terjadi banjir besar pada puncak musim hujan. Air berkurang pada berkurang saat musim kemarau (Juli-November) tetapi tidak signifikan

Nama Sungai

Sungai Maidang


Tdk ada data


Tdk ada data

Perkiraan head

Tidak ada head


20 KK



Pendidikan rata2


Rata2 jml org / KK

5 Orang



Komoditas utama

Jagung dan petani tembakau


Pelita

Potensi industry

-


Koppesda 4-28 Government of Indonesia / ADB – 12/14/15

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Lainnya 3. Fasilitas Umum Balai Desa

-

Puskesmas/posyandu

1 unit Posyandu

Sekolah

-

Gereja/masjid

1 unit (gereja)

Lainnya

-

4. Aksesibilitas 8 KM (dari simpang Maidang – Pusat Desa) Jarak lokasi ke jalan Kabupaten Jarak lokasi ke Jalan Provinsi

36 KM (dari Kota Waingapu – Simpang Maidang)


4 KM (dari pusat Desa ke Lokasi)


Tidak ada jalan kendaraan menuju lokasi


43 km (dari Jaringan PLN Waingapu– Lokasi)


300 meter


19 Rumah, 1 bangunan




Cukup


Bersedia swadaya.


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6. Foto lokasi

Lokasi di ambil dari jalan jauh (kurang lebih 3,5 KM)

Jalan menuju lokasi tempat pengambilan gambar. Menuju Lokasi Mbotanitu


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7. Peta Lokasi


9. Keterangan lain: Karena pertimbangan jarak yang terlalu jauh dan sulitnya akses menuju ke lokasi, maka untuk diskusi untuk informasi dilakukan dengan Warga Kampung Tanarara, Maidang. Diskusi dilakukan dengan memperlihatkan Peta yang sudah tersedia terhadap warga dan masayarakat mengenal dengan baik lokasi yang dituju. Dikampung tersebut bermukim warga 2 Desa yakni Desa Maidang dan Desa Mahu Bokul dengan total 20 KK. Sesuai informasi dari warga Tanarara, bahwa lokasi tersebut tidak terdapat perbedaan ketinggian yang signifikan antara hulu dan hilir..


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10. Informan : Stefanus Wulang dan kawan-kawan 11. Kesimpulan : Lokasi tidak layak untuk untuk pembangunan pembangkit mikro hidro, akses jalan sangat sulit dan jumlah jumlah KK relative sedikit ( <20).

4.9

MAIDANG – TAI TIRING

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 59 Kampung / Desa:Tai Tiring/Maidang Koordinat GPS :-

Kecamatan : Kambata Mapambuhang Kabupaten : Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 30 June 2015


Air sepanjang musim dengan debit air besar, sering terjadi banjir besar pada puncak musim hujan. Air berkurang pada musim kemarau (Juli-November) tetapi tidak signifikan

Nama Sungai

Sungai Maidang


Tdka da data


Tdkada data

Perkiraan head

Tidak ada head


22 KK


Petani Ladangdan Peternak (Tradisional)

Pendidikan rata2


Rata2 jml org / KK

5 Orang



Komoditas utama

Jagung, ubi kayu dan Ternak Besar (Kuda, Sapi, Kerbau) dan Babi


Pelita 4-32 Government of Indonesia / ADB – 12/14/15

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Potensi industry

-


Koppesda

Lainnya 3. FasilitasUmum BalaiDesa

-

Puskesmas/posyandu

1 unit Posyandu

Sekolah

1 unit

Gereja/masjid

1 unit (gereja)

Lainnya

-

4. Aksesibilitas 8 KM (dari simpang Maidang – Pusat Desa) Jarak lokasi kejalan Kabupaten Jarak lokasi ke Jalan Provinsi


Jarak lokasi keJalan Desa

4 KM(dari pusat Desa ke Lokasi)


Tidak ada jalan kendaraan menuju lokasi

Jaraklokasikejaringan LV/MV PLN



500 meter






Tidak ada


Bersediaswadaya.


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6. Peta Lokasi


8. Keterangan lain: Karena pertimbangan jarak yang terlalu jauh dan tidak ada akses menuju ke lokasi, untuk diskusi dilakukan dengan Warga Kampung Tanarara, Maidang sebagai informasi awal untuk menuju ke lokasi. Diskusi dilakukan dengan memperlihatkan Peta yang sudah tersedia terhadap warga dan masayarakat mengenal dengan baik lokasi yang di tuju. Sesuai informasi dari warga Tanarara, bahwa lokasi tersebut tidak terdapat perbedaan ketinggian yang signifikan antara hulu dan hilir. 9. Informan : Stefanus Wulang dan kawan-kawan 10. Kesimpulan : Lokasi tidak layak untuk dibangun pembangkit mikro hidro.


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4.10

MAIDANG - TANARARA

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 60 Kampung / Desa:Tanarara/Maidang Koordinat GPS : S 09°50’08.1” E120°12’24.5”

Kecamatan :Kambata Mapambuhang Kabupaten : Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 30 June 2015


Air sepanjang musim dengan debit air besar, sering terjadi banjir pada puncak musim hujan. Air berkurang pada musim kemarau (Juli-November) tetapi tidak signifikan

Nama Sungai

Sungai Maidang


Tdkada data


Tdkada data

Perkiraan head

Tidak ada head


57 KK



Pendidikan rata2


Rata2 jml org / KK

5 Orang



Komoditas utama

Jagung, ubi kayu dan Ternak Besar (Kuda, Sapi, Kerbau) dan Babi


Pelita, Listrik Tenaga Surya (PLTS) oleh PNPM (sudah tidak berfungsi)

Potensi industry

-


Koppesda


Page 182 of 396



1 unit

Puskesmas/posyandu

3 unit Posyandu

Sekolah

1 unit

Gereja/masjid

2 unit (gereja)

Lainnya

-

4. Aksesibilitas 8 KM (dari simpang Maidang – Lokasi) Jarak lokasi kejalan Kabupaten Jarak lokasi ke Jalan Provinsi



300 meter (dari pusat Desa ke Lokasi)


Jalan pengerasan




300 meter




Ada, dan mudahdidapat


Cukup


Bersediaswadaya.


Page 183 of 396


6. Fotolokasi

Batas Akses

Kondisi Bentuk Sungai Maidang di Lokasi survey

Bentuk Sungai

7. Peta Lokasi


Page 184 of 396



9. Informan : Stefanus Wulang 10. Kesimpulan : Lokasi tidak layak untuk dibangun pembangkit mikro hidro

4.11

WULA

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 8 Kampung / Desa: Hakuli/Lei Pandak/Wula Koordinat GPS : S 10.11.277; E 120.31.497

Kecamatan : Wula Waijelo Kabupaten : Sumba Timur Surveyor : Warin & Umbu Bahi Tanggal survey : 22 April 2015


Air ada sepanjang musim, kadang-kadang banjir saat musim hujan;

Nama Sungai

Sungai Waijelo

Dimensi sungai

Lebar 8 m; Kedalaman air 50 cm

Perkiraan head

Kondisi topografi aliran sungai relative landai-datar.Tidak ditemukan head yang memadai ( kurang dari 2m)

2. Sosial Ekonomi


Page 185 of 396


Jumlah penduduk / Rumah

25 KK


Petani dan Ternak

Pendidikan rata2

SD

Rata2 jml org / KK

5-6 jiwa


Tidak tentu, tergantung hasil panen sawah dan penjualan ternak.

Komoditas utama

Jagung, ubi, sapi, Kerbau, babi dan kuda, kambing.

Potensi industri

Tidak ada


Tidak ada

Fasilitas Umum

Tidak ada

3. Kondisi Pemakaian Energy Saat Ini Jarak dengan Jaringan PLN

2 Km dari jaringan PLN (LV) desa Kawangu. 3.5 Km dari MV

Sumber listrik saat ini

SEHEN dan Pelita.

Belanja listrik

20-30 ribu per bulan

Keterangan Lainnya

Kondisi rumah tersebar

4. Akses Jalan Jarak lokasi ke jalan raya

5 Km dari Jalan Raya Waingapu – Simpang Wula

Jarak lokasi ke Jalan desa

2 Km I dar Jalan tanah Desa Wula

Kondisi jalan menuju ke lokasi

Jalan beraspal dan sebagian pengerasan batu, n hingga ke lokasi baik dan bisa dilalui kendaraan roda 4.

5. Informasi awal sistem desain, operasi pemeliharaan Jarak intake (sungai) – pemukiman

Tidak ada lokasi potensial, Head tidak ditemukan di sekitar lokas (radius 2 km) 4-39 Government of Indonesia / ADB – 12/14/15

Page 186 of 396



25, kondisi rumah tersebar.

Ketersediaan material lokal

Ada, dan mudah didapat (60 km dari Kota Waingapu)


Tidak tersedia, sangat terbatas


Bersedia dengan swadaya namun harus dibina dan dipersiapkan


Tidak berpotensi untuk lokasi Pembangkit Mikro Hidro

7. Peta lokasi

8. Informan: 1. Bustonimus (warga kampong Hakuli)


Page 187 of 396


9. Foto Lokasi

Kondisi Sungai Waijelo di Kampung Hakuli, Lei Pandak, Wula, Sumba Timur, tidak ditemukan head, tidak berpotensi untuk PLTMH

Kondisi Kampong Hakuli di Lei Pandak, Wula Waijelo, Sumba Timur , hanya 2 Km dari Jaringan Listrik PLN terdekat di Desa Wula.

10. Kesimpulan & Rekomendasi Lokasi tidal layak untuk dibangun Pembangkit Mikro Hidro dikarenakan tidak ditemukan head pada radius 2 km disekitar pemukiman. Lokasi sangat memungkinkan untuk dilayani listrik PLN karena hanya berjarak 2 Km dari jaringan terdekat PLN di Desa Wula.


Page 188 of 396


4.12

WALAN NDIMU

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 107 Kampung / Desa: Walan Ndimu Daya Koordinat GPS : S 09.38.439; E 119.03.832 Rakam

Kecamatan : Kodi Bangedo Kabupaten : Sumba Barat Surveyor : Warin & Devid Tanggal survey : 28 April 2015

1. Karakteristik DAS Kondisi aliran air

Aliran sungai sepanjang tahun, banjir saat musim hujan,.

Nama Sungai

Weha

Dimensi sungai

Lebar 8-10 m; Kedalaman air 60-100 cm.

Perkiraan head

20 m, ada air terjun 5 m

2. Sosial Ekonomi Jumlah penduduk / Rumah

243 KK di 4 Dusun.


Petani dan Ternak

Pendidikan rata2

SD , SMP.

Rata2 jml org / KK

5-6 jiwa


Tidak tentu, tergantung hasil panen sawah dan penjualan ternak

Komoditas utama

Jagung, ubi, sapi, kerbau, babi dan kuda, kambing.

Potensi industri

Industri pemipil jagung, pariwisata (pantai)


WMI

Fasilitas Umum

Balai Desa, Gedung SD, SMP, Polsek, SMP, Kantor Kecamatan, Gereja.


Jaringan listrik PLN sudah masuk di 2 dusun, sepanjang jalan Kodi Bangedo. Dusun yang belum ada listrik berjarak 4-6 Km dari LV. 4-42 Government of Indonesia / ADB – 12/14/15

Page 189 of 396



2 Dusun sudah mendapat listrik PLN, 2 dusun lain sebagian mendapatkan SEHEN.

Belanja listrik

30-50 ribu per bulan.


Dusun yang belum mendapat listrik 4-6 Km dari jalan Raya Kodi Bangedo


1-2 Km dari pusat Desa


Kondisi jalan beraspal baik, sebagian jalan batu hingga ke lokasi dan bisa dilalui kendaraan roda 4.


6 km dari pusat Desa, namun hanya kurang 1 km dari jaringan PLN


Sebagian besar sdh berlistrik PLN dan SEHEN


-


Cukup


Selama ini membayar listrik PLN dan SEHEN dengan lancar


20-30 Kw, lokasi sungai jauh dari lokasi dusun yang belum berlistrik (6 Km) namun dekat dengan jaringan PLN (1 km)


Page 190 of 396


6. Peta lokasi

7. Informan: 1. Wongo Dadi dan Marcelinus (Perangkat Desa).

8. Foto Lokasi


Page 191 of 396


Desa Walan Ndimu, sebagian besar area sudah mendapat aliran listrik PLN dan SEHEN.

Sungai Weha di Desa Walan Ndimu yang memeliki potensi head 20 m dan air terjun 5m, namun lokasinya jauh dari pemukiman yang belum berlistrik (lebih dari 6 Km).

9. Kesimpulan & Rekomendasi Lokasi memiliki potensi untuk dibangun Pembangkit Mikro Hidro namun jaraknya cukup jauh dari pemukiman (6 km) 4-45 Government of Indonesia / ADB – 12/14/15

Page 192 of 396


Lebih layak dibangun PLTM yang menyambung ke Grid PLN, jarak 1-2 Km dari jaringan terdekat. Untuk memenuhi listrik dari 2 dusun yang belum ada jaringan lebih efisien untuk memperpanjang jaringan dari pusat desa dan jalan raya utama Kodi yang hanya berjarak 2-3 Km menuju 2 Dusun yang belum berlistrik.

4.13

WEE KOMBAKA

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 124 Kampung / Desa: Wee Kombaka Daya Koordinat GPS : S 09.31.244 E 119.09.286 Rakam

Kecamatan : WejehaSelatan Kabupaten : Sumba Barat Surveyor : Warin & Devid Tanggal survey : 28 April 2015


Aliran sungai banjir saat musim hujan, namun debit air berkurang saat musim kemarau.

Nama Sungai

Wee Kombaka

Dimensi sungai

Lebar 4 m; Kedalaman air 30 cm. Lokasi di tepi hutan lindung.

Perkiraan head

Tidak ditemukan Head yang memadai (kurang dari 2m)


515 KK, di 4 dusun. Pusat dusun di Wano Guru.


Petani dan Ternak

Pendidikan rata2

SD , SMP.

Rata2 jml org / KK

5-6 jiwa


Tidak tentu, tergantung hasil panen sawah dan penjualan ternak, serta mencari kayu di hutan.

Komoditas utama


Potensi industri

Industri pemipil jagung, industry saw mill


Tidak ada 4-46 Government of Indonesia / ADB – 12/14/15

Page 193 of 396


Fasilitas Umum

Balai Desa, Gedung SD, SMP.


Jaringan listrik PLN sudah masuk di 3 dusun.


3 Dusun sudah mendapat listrik PLN, kecuali dusun 3 (Adalara) sebagian mendapatkan SEHEN.

Belanja listrik



8 Km dari simpang jalan utama WaitabulaWaikabubak.


4 Km dari pusat desa Wee Kombaka (Wano Guru)


Kondisi jalan beraspal baik hingga ke lokasi dan bisa dilalui kendaraan roda 4.


4 km


Sebagian besar sdh berlistrik


-


Cukup


Selama ini membayar listrik PLN dengan lancar


-


Page 194 of 396


6. Peta lokasi

7. Informan: 1. Yohanes Perus Rado; 2. Andreas Ahde Nali; 3. Heridion Mutuado

8. Foto Lokasi


Page 195 of 396


Lokasi Desa Wee Kombaka, 3 dusun sudah mendapat listrik PLN dan 1 dusun dengan listrik SEHEN

Sungai Wee Komba berada di tepi Hutang Lindung. Debit air kecil pada musim kemarau. Tidak layak untuk pembangkit listrik dan jauh dari pemukiman (4 Km).

9. Kesimpulan & Rekomendasi Lokasi tidal layak untuk dibangun Pembangkit Mikro Hidro dikarenakan tidak ditemukan sumber air sungai yang emmadai dan head pada sungai yang ada. Sebagian besar penduduk sudah mendapatkan listrik PLN baik grid maupun SEHEN. Lebih efisien memperpanjang jaringan 2 Km untuk menjangkau dusun yang belum mendapat listrik.


Page 196 of 396


4.14

WAMBIDI

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 61 Kampung / Desa: Wambidi Koordinat GPS : tidak terdata

Kecamatan: Kambata Mampabuhang Kabupaten : Sumba Timur Surveyor : Warin & Umbu Bahi Tanggal survey : 23 April 2015


-

Nama Sungai

-


-


-

Perkiraan head

-


--


-

Pendidikan rata2

-

Rata2 jml org / KK

-


-

Komoditas utama

-

Potensi industri

-


-

Fasilitas Umum

-

Keterangan Lain

Lokasi tidak bisa dijangkau, Jalan desa menuju ke lokasi desa Wambidi terputus 2 km dari desa Maidang.

3. Kondisi Pemakaian Energy Saat Ini 4-50 Government of Indonesia / ADB – 12/14/15

Page 197 of 396


Jarak dengan Jaringan PLN

-

Sumber listrik Saat ini

-

Belanja Energy

-

Keterangan Lainnya

-

4. Akses Jalan Jarak lokasi ke jalan Utama

28 Km dari Waingapu - Maidang


Terputus pada Km 2 dari Kantor Kecamatan. Lokasi masih 5-6 Km dari jalan yang terputus.


Terputus pada Km ke-2 dari jalan utama. Jalan menyempit, licin dan nlongsor. Lokasi Tidak bisa dialkses. Kondisi jalan sangat buruk dan berbahaya.


-


-

Ketersediaan Material lokal

-


-


-


-

7. Foto Lokasi


Page 198 of 396



Page 199 of 396


Kondisi jalan menuju Lokasi Desa Wambidi, terputus pada Km 28+2, setelah kantor kecamatan dan gedung sekolah. Jalan menyempit, longsor dan sangat licin (kondisi hujan). Lokasi tidak dapat diakses, diperkirakan jalan putus menuju ke lokasi masih 6-10 Km dari jalan yang terputus 8. Kesimpulan & Rekomendasi Lokasi tidak layak untuk dibangun Pembangkit Mikro Hidro dikarenakan tidak dapat disurvey, dan tidak didapatkan data lapangan. Akses menuju lokasi juga tidak memadai untuk pengiriman barang dan material dan peralatan (batu, semen, kabel, turbin, dsb).

4.15

SORU

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 113 Kampung / Desa: Wacu Kao/Soru Koordinat GPS : S 09.33.766; E 119.50.719

Kecamatan : Umbu Ratu Nggay Kabupaten : Sumba Tengah Surveyor : Warin & Umbu Bahi Tanggal survey : 25 April 2015


Page 200 of 396



Aliran sungai sepanjang tahun, berkurang saat musim kemarau.

Nama Sungai

Soru

Dimensi sungai


Perkiraan head

15 m


60 KK


Petani dan Ternak

Pendidikan rata2

SD

Rata2 jml org / KK

5-6 jiwa



Komoditas utama


Potensi industri

Industri pemipil jagung.


Tidak ada

Fasilitas Umum

Balai Desa, Gedung SD, SMP, Gereja.


12 Km dariarah Jalan Utama Waingapu-Waikabubak, 6 Km arah ke Rakawatu/Lewa.


Genset, SEHEN dan Lampu Pelita.

Belanja listrik



12 Km dari Jalan raya Waingapu-Waikabubak


6 Km dari pusat Desa Soru


Page 201 of 396



Kondisi jalan beraspal baik, sebagian jalan batu hingga ke rumah terluar, dilanjut jalan kaki 1 km menuju ke lokasi sungai.


3 km kampung terdekat, 5 km ke pusat desa.


60 namun tersebar di beberapa kampong, masingmasing 15-20 rumah.


-


Terbatas


Selama ini membayar listrik SEHEN namun sebagian tidak lancar dan ditarik kembali.


20-30 Kw, namun lokasi sungai jauh dari lokasi pemukiman terdekat (3 Km) . dan pusat desa (6 km).

6. Peta lokasi


Page 202 of 396


7. Informan: 1. Parabung Namukali Warga). 8. Foto Lokasi

Kampung Wacu kao, Desa Soru, Sumba Tengah. Sebagian besar listrik menggunakan SEHEN PLN.


Page 203 of 396


Sungai di Desa Soru, Kecamatan Umbu Ratu Nggay, Sumba Tengah. Kondisi sungai mempunyai potensi head 16 m untuk PLTMH, namun berjarak 3-5 Km dari pemukiman terdekat yang rumahnya 20-30 menyebar.

9. Kesimpulan & Rekomendasi Lokasi memiliki potensi untuk dibangun Pembangkit Mikro Hidro namun jaraknya cukup jauh dari pemukiman (3-4 km) ke pemukiman terdekat, Kampung Wacu Kao. Apabila dibangun PLTMH maka lebih baik connect dengan karingan PLN terdekat di Lewa/Rakawatu. Untuk memenuhi listrik pada kampong lebih efisien untuk menggunakan PLTS tersebar (SEHEN) dengan alasan rumah bersifat tersebar dan tidak begitu banyak , setiap kluster 15-20 rumah. PLN akan membangun PLTMG 2 x 50 Kw di lokasi lebih arah ke Hulu Sungai dan diinterkoneksikan dengan jaringan Lewa-Rakawatu-Tanambanaspada tahun 2015/2016.

4.16

WEELURI

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 4-57 Government of Indonesia / ADB – 12/14/15

Page 204 of 396


Mini grid _ID : 128 Kampung / Desa: Wai Pangali/Weeluri Koordinat GPS : S 09.30.144; E 119.31.351 Rakam

Kecamatan : Loli Kabupaten : Sumba Barat Surveyor : Warin & Devid Tanggal survey : 27 April 2015


Aliran sungai sepanjang tahun, namun sungai masuk ke dalam tanah sebelum memasuki Desa Weeluri.

Nama Sungai

Wai Luri

Dimensi sungai


Perkiraan head

Tidak ditemukan head di sekitar desa


50-60 rumah


Petani dan Ternak

Pendidikan rata2

SD , SMP.

Rata2 jml org / KK

5-6 jiwa



Komoditas utama


Potensi industri

Industri pemipil jagung, penggilingan padi.


Tidak ada

Fasilitas Umum



3 Km dari jaringan MV terdekat di Desa Loli.


Sebagian Genset dan sebagian mendapatkan SEHEN.

Belanja listrik

35 ribu per bulan.


Pemukiman di kanan-kiri jalan raya Loli - Mamboro 4-58 Government of Indonesia / ADB – 12/14/15

Page 205 of 396



Pemukiman di kanan-kiri jalan raya Loli - Mamboro


Kondisi jalan beraspal baik dan bisa dilalui kendaraan roda 4.


6 km, sungai kemudian masuk di bawah tanah


Sebagian besar SEHEN dan sebagian Genset


-


Cukup


Selama ini membayar SEHEN dengan lancar


Tidak ditemukan head di sekitar lokasi

6. Peta lokasi

7. Informan: 1. Yoseph Malik 4-59 Government of Indonesia / ADB – 12/14/15

Page 206 of 396


8. Foto Lokasi

Desa Wee Luri, sebagian besar listrik saat ini menggunakan genset dan SEHEN PLN.

Sungai Wee Luri di Desa Wee Luri Ndimu, tidak mempunyai potensi head yang memadai di sekitar lokasi desa dan pemukiman terdekat.

9. Kesimpulan & Rekomendasi 4-60 Government of Indonesia / ADB – 12/14/15

Page 207 of 396


Lokasi tidak memiliki potensi untuk dibangun Pembangkit Mikro Hidro. Lokasi desa dan pemukiman yang hanya berjarak 4-5 Km dari jaringan PLN terdekati di Desa Loli dan kondisi jalan raya yang strategis menghubungkan Waikabubak dan Mamboro layak dibangun jaringan listrik PLN MV dengan memeperpanjang jaringan yang ada saat ini di Loli.

4.17

SODANA

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 107 Kampung / Desa: Weetena/Sodana Koordinat GPS : S 09.41.840; E 119.22.355 Rakam

Kecamatan : Lamboya Kabupaten : Sumba Barat Surveyor : Warin & Devid Tanggal survey : 27 April 2015


Aliran sungai sepanjang tahun, berkurang saat musim kemarau.

Nama Sungai

Lulu

Dimensi sungai


Perkiraan head

12 m, ada air terjun 2-3 m


112 KK, tersebar di 4 kampung.


Petani dan Ternak

Pendidikan rata2

SD

Rata2 jml org / KK

5-6 jiwa



Komoditas utama


Potensi industri

Tidak ada


Tidak ada 4-61 Government of Indonesia / ADB – 12/14/15

Page 208 of 396


Fasilitas Umum



6 Km dari Jaringan Lamboya


Genset, SEHEN dan Lampu Pelita.

Belanja listrik



7 KM dari Jalan raya Lamboya


4 Km dari pusat desa Sodana/We Tana


Kondisi jalan beraspal baik, sebagian jalan batu hingga ke lokasi dan bisa dilalui kendaraan roda 4.


6 km dari pemukiman terdekat di We tana


80 namun tersebar di 4 kampung, masing-masing 1520 rumah.


-


Tidak ada


Selama ini membayar listrik SEHEN dengan lancar namun sebagian tidak lancar dan ditarik kembali.


15-20 Kw, namun lokasi sungai jauh dari lokasi pemukiman terdekat (6 Km) .


Page 209 of 396


6. Peta lokasi

7. Informan: 1. Maria Tabora (Guru SD Sodana); 2. Joseph Kanai (Warga). 8. Foto Lokasi

Kampung dan gedung sekolah di Kampung Weetana, Desa Sodana, sebagian mendapat penduduk listrik SEHEN PLN.


Page 210 of 396


Jalan menuju Sungai di Desa Sodana, Kecamatan Lamboya. Kondisi sungai mempunyai potensi head 12 m untuk PLTMH, namun berjarak 4 Km dari pemukiman terdekat yang rumahnya 20-30 menyebar.

9. Kesimpulan & Rekomendasi Lokasi memiliki potensi untuk dibangun Pembangkit Mikro Hidro namun karena jaraknya cukup jauh dari pemukiman (5 km) ke pemukiman terdekat, Kampung Weetana maka menjadi kurang layak dibangun. Untuk memenuhi listrik pada kampong lebih efisien untuk menggunakan PLTS tersebar (SEHEN) dengan alasan rumah bersifat tersebar dan tidak begitu banyak , setiap kluster 15-20 rumah.

4.18

MBATAPUHU

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 117 Kampung / Desa:Mbatapuhu Koordinat GPS : S 09°30’45.4” E119°59’23.2”

Kecamatan :Haharu Kabupaten : Sumba Timur Surveyor : Umbu Bahi Tanggal survey : 27 June 2015


Air sepanjang musim dengan debit air cukup, berdasarkan temuan lapangan tidak di temukan bukti banjir pada bibir sungai. Air berkurang pada berkurang saat musim kemarau (Juli-November)

Nama Sungai

Mbatapuhu


Tdkada data


Page 211 of 396



Tdkada data

Perkiraan head

Tidak ada head


63 KK



Pendidikan rata2


Rata2 jml org / KK

5 Orang


Tidak menentu (curah hujan)

Komoditas utama

Jagung, Ubi Kayu dan Ternak Besar (Kuda, Sapi, Kerbau), Kambing dan Babi


Menggunakan Pelita, Sehen (sebagian besar sudah di tarik PLN)

Potensi industri

Pengolahan Jagung


Ada Yayasan WVI


1 unit

Puskesmas/posyandu


Sekolah

1 unit

Gereja/masjid

5 unit (gereja)

4. Aksesibilitas Jarak lokasi kejalan Kabupaten

4 KM (dari Kantor Desa – Lokasi)

Jarak lokasi keJalan Provinsi

30 KM (dari Kantor Kecamatan – Lokasi)


4 KM tidak ada jalan (hanya bisa jalan kaki)


30 KM (dari Kantor Kecamatan – Lokasi)


Page 212 of 396



6 KM




Ada, dan mudahdidapat (60 km dari Kota Waingapu)


Cukup


Catatan pernah ditariknya sehen karena tidak mampu membayar

6. Fotolokasi

Jalan Kabupaten Menuju Desa Mbatapuhu

Sekolah Dasar Mbatapuhu

Kampung Mbatapuhu

Batas Akses Menuju Lokasi


Page 213 of 396


7. Peta Lokasi


9. Keterangan lain: Karena pertimbangan jarak yang terlalu jauh dan tidak ada akses menuju ke lokasi, untuk diskusi dengan Sekretaris Desa Mbatapuhu sebagai informasi awal untuk menuju ke lokasi. Diskusi dilakukan dengan memperlihatkan Peta yang sudah tersedia, dan Sekretaris Desa Mbatapuhumengenal dengan baik lokasi tersebut. Sesuai informasi dari Sekretaris Desa Mbatapuhu, bahwa lokasi tersebut tidak terdapat perbedaan ketinggian yang signifikan antara hulu dan hilir. 10. Informan : Sekretaris Desa Mbatapuhu 11. Kesimpulan : Lokasi tidak layak dibangun pembangkit mikro hidro


Page 214 of 396


4.19

PRAIBAKUL

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 134 Kampung / Desa: Praibakul Koordinat GPS : S 09.28.749; E 120.02.417

Kecamatan : Haharu Kabupaten : Sumba Timur Surveyor : Warin & Umbu Bahi Tanggal survey : 22 April 2015



Nama Sungai

Sungai Kapunduk

Dimensi sungai

Lebar 8-10 m; Kedalaman air 5-100 cm

Perkiraan head

Kondisi topografi aliran sungai relative landai-datar.Tidak ditemukan head yang memadai ( kurang dari 2m)


70 KK


Petani dan Ternak

Pendidikan rata2

SD & SMP

Rata2 jml org / KK

5-6 jiwa


Tidak tentu, tergantung hasil panen sawah dan penjualan ternak.

Komoditas utama

Jagung, ubi, sapi, Kerbau, babi dan kuda, kambing.

Potensi industri

Industri pemipil jagung


Tidak ada

Fasilitas Umum

Sekolah SD, Balai Desa, Gereja

3. Kondisi Pemakaian Energy Saat Ini 4-68 Government of Indonesia / ADB – 12/14/15

Page 215 of 396


Jarak dengan Jaringan PLN

2 Km dari PLTD PLN Haharu.


PLN, SEHEN dan PLTD bantuan PNPM Perdesaan.

Belanja listrik

SEHEN 35.000, PLTD 20.000 per bulan

Keterangan Lainnya

Rumah pada jarak 1 Km mendapat jaringan PLN, setelah 1 Km sebagian SEHEN dan PLTD bantuan dari PNPM Perdesaan (2012).


2 Km (Jalan Raya Pantaiu Utara Waingapu – Hambapraing)


2 Km (Jalan tanah Desa Praibakul)


Jalan beraspal dan sebagian pengerasan batu, n hingga ke lokasi baik dan bisa dilalui kendaraan roda 4.


Tidak ada lokasi potensial, Head tidak ditemukan di sekitar lokasi


70, tersebar di 3 kampung.




Tidak tersedia, sangat terbatas


Bersedia dengan swadaya namun harus dibina dan dipersiapkan. Pengalaman iuran Genset bantuan PNPM adalah Rp. 20.000/bulan/KK.




Page 216 of 396


7. Peta lokasi

8. Informan: 1. Agus Hambadita; 2. Hima Malitaka

9. Foto Lokasi

Kondisi Sungai Kapunduk di DEsa Praibakul, Sumba Timur. tidak ditemukan head, tidak berpotensi untuk PLTMH


Page 217 of 396


Jaringan Listrik PLN di Desa Praibakul, PLTD Haharu berlokasi 2 KM dari Desa.

10. Kesimpulan & Rekomendasi Lokasi tidal layak untuk dibangun Pembangkit Mikro Hidro dikarenakan tidak ditemukan head pada radius 2 km disekitar pemukiman. Lokasi sangat memungkinkan untuk dilayani listrik PLN karena hanya berjarak 2 Km dari PLTD Haharu dan akses jalan sangat memadai.

4.20

KAWANGU

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 91 Kampung / Desa :Palumung/ Kawangu Koordinat GPS : S 09.42.916; E 120.19.567

Kecamatan : Pandawai Kabupaten : Sumba Timur Surveyor : Warin & Umbu Bahi Tanggal survey : 22 April 2015



Nama Sungai

Sungai Kawangu

Dimensi sungai

Lebar 8-10 m; Kedalaman air 40-60 cm

Perkiraan head

Kondisi topografi aliran sungai relative landai-datar.Tidak ditemukan head yang memadai ( kurang dari 2m).

2. Sosial Ekonomi 4-71 Government of Indonesia / ADB – 12/14/15

Page 218 of 396


Jumlah penduduk / Rumah

25 KK di Kampung Palamung.


Petani dan Ternak

Pendidikan rata2

SD

Rata2 jml org / KK

5-6 jiwa


Tidak tentu, tergantung hasil panen sawah dan penjualan ternak. Hasil pertanian hanya untuk dimakan keluarga dan tidak dijual.

Komoditas utama

Jagung, ubi, sapi, kerbau, babi dan kambing.

Potensi industri

Industri pemipil jagung


Tidak ada

Fasilitas Umum

Tidak ada


2 Km dari jaringan terdekat PLN (LV).


SEHEN dan Genset

Belanja listrik

20-35 ribu/bulan

Keterangan Lainnya

Kampung hanya berjarak 2 Km dari jaringan terdekat PLN (LV), kondisi rumah tersebar


5 Km dari alan Raya Waingapu – Melolo


2 Km dari Jalan tanah pusat Desa Kawangu)


Jalan beraspal dan sebagian pengerasan batu hingga ke lokasi baik dan bisa dilalui kendaraan roda 4.


1 km, namun tidak ada lokasi potensial, head tidak ditemukan di sekitar lokasi


25, namun tersebar 4-72 Government of Indonesia / ADB – 12/14/15

Page 219 of 396





Tidak tersedia dan sangat terbatas


Bersedia dengan swadaya namun harus dibina/ dipersiapkan



7. Peta lokasi

8. Informan: 1. Langi Kandaramu (warga kampong Palamung)

9. Foto Lokasi


Page 220 of 396


Kondisi Sungai Kawangu di Kampung Palamung, Desa Kawangu, Sumba Timur, tidak ditemukan head sehingga tidak berpotensi untuk PLTMH

Jaringan Listrik PLN (MV) sudah masuk di Desa Kawangu sejauh 2.5 Km, dan LV sejauh 4.5 Km dari Simpang Jalan Raya Waingapu-Melolo.

10. Kesimpulan & Rekomendasi Lokasi tidal layak untuk dibangun Pembangkit Mikro Hidro dikarenakan tidak ditemukan head pada radius 2 km disekitar pemukiman. Lokasi sangat memungkinkan untuk dilayani listrik PLN karena hanya berjarak 2 Km dari jaringan listrik PLN yang terdekat.


Page 221 of 396


4.21

WAIYENGU

FORM SURVEY LAPANGAN MIKRO HYDRO SUMBA 2015 Mini grid _ID : 123 Kecamatan :Umbu Ratu Nggai Barat Kampung / Desa:Wangga Waiyengu Kabupaten : Sumba Tengah Koordinat GPS : S 09°31’55.0” E119°37’23.6” Surveyor : Umbu Bahi Tanggal survey : 1 July 2015 1. Karakteristik DAS Aliran air

Air sepanjang musim dengan debit air besar. Air berkurang pada saat musim kemarau (Juli-Oktober), tetapi berkurang tidak terlalu signifikan.

Nama Sungai

Wangga Weiyengu


Tdk ada data


Tdk ada data

Perkiraan head

Tidak ada head


190 KK


Petani Ladang dan pengumpul/penambang pasir

Pendidikan rata2


Rata2 jml org / KK

4 Orang


Tidak menentu

Komoditas utama

Jagung dan Pasir Kali


Menggunakan Pelita, Sehen (sebagian besar sudah di tarik PLN)

Potensi industry

-


-


Page 222 of 396


3. Fasilitas Umum Balai Desa

1 unit

Puskesmas/posyandu


Sekolah

1 unit (SD)

Gereja/masjid

1 unit (gereja)


4 KM (simpang Lawonda – Lokasi)


15 KM (dari Kota Waibakul – pusat Desa Wangga Waiyengu)


1 km (dari lokasi – kantor desa Wangga Waiyengu)


Baik dan berasal


4 km (dari Jaringan PLN – Lokasi)


1 km dari pemukiman






Cukup


Bersedia swadaya.


Page 223 of 396


6. Foto lokasi

Kondisi Sungai Wainyengu di Kampung Wangga, Kabupaten Sumba Tengah.

7. Peta Lokasi

8. Informan : Umbu Ndatta 9. Kesimpulan : Lokasi tidak layak untuk pembangunan mikro hidro


Page 224 of 396

5.

INVESTOR FORUM


December 2015

Page 225 of 396

AGENDA SUMBA ICONIC ISLAND INVESTMENT FORUM The Hermitage Hotel, Menteng ‐ Central Jakarta 15th December 2015 Time 08.00 – 08.30 Registration

Activity Opening Ceremony

08.30 – 08.40 08.40 – 08.50 08.50 – 09.00 09.00 – 09.20

Opening by MC Singing the National Anthem “Indonesia Raya” Opening Prayer Keynote Speech by Rida Mulyana (Director General of New, Renewable Energy and Energy Conservation (DGNREEC) – Ministry of Energy and Mineral Resources (MEMR), Republic of Indonesia) : “The Role of Government of Indonesia in Engaging the Private Sector for Renewable Energy Development in Indonesia”

1st Session 09.20 – 09.35 Presentation by Maritje Hutapea (Director for Various New and Renewable Energy, DGNREEC – MEMR) : “Commitment from the Government of Indonesia to Support the Involvement of Private Sector for the Sumba Iconic Island for 100% Renewable Energy Programme” 09.35 – 09.50 Presentation by the Local Government of East Sumba District: “Commitment from the Local Government of Sumba Island to support the Acceleration of Renewable Energy Development in East Sumba” 09.50 – 10.05 Presentation by General Manager of PT. PLN East Nusa Tenggara (NTT) Provincial Office: “Electrification Infrastructure Development and Planning of Sumba Island” 10.05 – 10.25 Q‐A session

Page 226 of 396

2nd Session 10.25 ‐10.35

Presentation by Mike Crosetti (Castlerock Consulting): “Least‐Cost Electrification Plan in Sumba Island”

10.35 – 10.55 Presentation by Warintoko (Castlerock Consulting): “Pre‐FS of Microhydro Project in East Sumba” 10.55 – 11.15 Presentation by Syaiful Bakhri Ibrahim (Castlerock Consulting): “Pre‐FS of Minihydro with Dam in Kadahang River (5 MW) and Praikalala River (3,5 MW)” 11.15 – 11.35 Presentation by Pramod (Innovative Wind Energy) : “Pre‐FS of Wind Project in Hambapraing ( 10 MW)” 11.35 – 11.55 Presentation by Romadhi Ridlo (Castlerock Consulting) : “Pre‐FS of Biomass Project (1 MW)” 3rd Session 11.55 – 12.40 Discussion with Financial Institution: “Financial Institution Point of View on RE Project Financing” ‐ PT SMI ‐ Bank BRI ‐ MCA Indonesia 12.40 – 12.45 Closing remarks 12.45 – 13.30 Lunch & Networking

Page 227 of 396

Sumba Least‐Cost Electrification Plan Sumba Iconic Island Investor Forum 15 December 2015

www.castlerockasia.com 1

The Sumba Iconic Island Initiative Current Situation • <30% electrification • ~15% renewable power supply

2025 Targets • 95% electrification • 100% renewable power supply

• What projects and associated investment are required to achieve the Iconic Island targets? • Development of a feasible, least‐cost plan – Grid vs. off‐grid – Expansion plan for grid‐connected generation – Network development

• Good planning supports private investment & optimizes public expenditure 2

Page 228 of 396

The planning methodology

Electrification Targets

http://castlerockasia.com/sumba/sii.html Grid vs. off‐ grid analysis

Geospatial planning tools: Network Planner Grid demand

Off‐grid investment opportunities

Private sector investment

Grid least‐cost generation expansion plan

On‐grid investment opportunities

PLN investment

EBT Resource Assessment

Generation planning tools: Homer

Load flow & transmission plan

Network infrastructure investment

Network planning tool: ETAP

Network operating requirements 3

Available technologies • The following technologies were candidates for the least‐cost generation expansion plan for the grid: – – – – – –

Wind PV Biomass Hydro Pumped storage Diesel

• All renewables were cheaper than diesel • However, feasible renewable capacity additions depend on other factors

4

Page 229 of 396

Key dependencies – load growth • Maximum technical availability – Limited by the resource: hydro, biomass – Limited by the ability of grid to absorb power: PV, wind • Maximum capacity of techology = 25% of system peak demand

GWh Sales per Year

350 300

RUPTL 2015‐2024

250 Electrification Target = 95% in 2025 Electrification Target = 95% in 2020

200 150 100 50 0

Year 5

Key dependencies – transmission infrastructure • Wind & hydro far from load centers require HV transmission • PLN plans HV line for commissioning in 2017

6

Page 230 of 396

Principal findings Investor Forum?

Load depndt.

Trans. depndt.

Microhydro

n.a.

n.a.

Comprehensive reconnaissance study conducted.

Community PV

n.a.

n.a.

Requires subsidy to be affordable. No subsidy mechanism in place.

RoR Minihydro

No

No

All identified RoR locations > 500 kW already claimed.

Storage Hydro

No

Yes

Preliminary study for Praikalala (3.5 MW) and Kadahang (5 MW)

Pumped Storage

Yes

Yes

Not clear if financially feasible at current diesel price. Large investment.

Biomass

No

No

Wind

Yes

Yes

PV

Yes

Yes

Technology

Comment

Off‐grid

On‐grid

PreFS for 1 MW. PreFS for 10 MW at Hambapraing Utility‐scale PV regulation to be revised. 7

THANK YOU ! www.castlerockasia.com 8

Page 231 of 396

ADB TA 8287‐INO: Scaling Up Renewable Energy Access in Eastern Indonesia

Study Potensi PLTMH di Pulau Sumba

DAFTAR ISI

• • • •

Latar Belakang Metode Hasil Study Potensi Resiko

2

Page 232 of 396

1

Latar Belakang • Rasio Elektrifikasi di Pulau Sumba masih sangat rendah ( < 40%) • 85% Kebutuhan listrik di P.Sumba saat ini dipasok dari PLTD (7 Mw) • Sebagian besar pola pemukiman penduduk di Perdesaan P. Sumba yang menyebar dan berjauhan memerlukan listrik off grid • Potensi Pengembangan Pembangkit Listrik dari Sumber Energi Terbarukan menjadi prioritas (Sumba Iconic Isand) • Perlu dilakukan survey potensi PLTMH di Sumba untuk mendukung listrik off grid

3

Kondisi Elektrifikasi Pulau Sumba Tahun 2013

Sumber: Desa berlistrik PLN Area Sumba

4

Page 233 of 396

2

Metode Tahap I Desk Study : 1. Identikasi lokasi mini grid pada Network Planner basis “low cost” scenario, ditemukan 300 lokasi potensial. 2. Disaring 100 lokasi yang berdekatan (1km) dari sungai berdasarkan peta BIG. 3. Disaring menjadi 40 lokasi terpilih berdasarkan: • Beda elevasi pada 1 km aliran sungai untuk memperkirakan head. • Perkiraan luas area tangkapan air untuk memperkirakan debit air. • Berdasarkan perkiraan beda elevasi dan luas area tangkapan air dilakukan perangkingan lokasi potensial PLTMH

5

Hasil Desk Study Tahap I

6

Page 234 of 396

3

Metode Tahap II Desk Study : Menganalisis 40 lokasi dengan Google Earth dengan mempertimbangkan : a. Menghitung jumlah bangunan pada radius 1 km lokasi untuk memilih lokasi yang memiliki lebih dari 30 bangunan/rumah b. Menganalisis pola pemukiman yang relatif berdekatan untuk dipilih. c. Memilih lokasi yang memiliki akses jalan, minimal bisa dilalui mobil kendaraan roda 4.

7

Hasil Analisis Desk Study Tahap II No.

Kabupaten

Region

Desa

Mini_Grid Distance from Main Road Number of houses nearby _ID (km) river < 1 km 60 15 50< 59 18 30< 113 8.6 60 < 26 18.5 30 < 46 20 < 30< 54 18 40< 128 12.8 50 < 25 < 20 20‐30 134 1.6 60 <

1 2 3 4 5 6 7 8 9

SUMBA TIMUR SUMBA TIMUR SUMBA TENGAH SUMBA TIMUR SUMBA TIMUR SUMBA TIMUR SUMBA TENGAH SUMBA TIMUR SUMBA TIMUR

Eastern Eastern Western Eastern Eastern Eastern Western Eastern Eastern

MAIDANG MAIDANG Soru PABERA MANERA WAIKANABU MAHU BOKUL WEE LURI KATIKUTANA PRAI BAKUL

10 11 12 13 14 15

SUMBA BARAT DAYA SUMBA TIMUR SUMBA TIMUR SUMBA TIMUR SUMBA TIMUR SUMBA TENGAH

Western Eastern Eastern Eastern Eastern Western

WALLA NDIMU KARITA PULU PANJANG KAWANGU WAIMBIDI PONDOK

107 36 65 91 61 125

4.1 19 6.4 3.4 10 9.7

60 < 30< 50 < 50 < 40 < 30<

16 17 18

SUMBA BARAT DAYA Western SUMBA TIMUR Eastern SUMBA TIMUR Eastern

WEE KOMBAKA KANANGGAR MAU BOKUL

124 21 49

7.3 20.2 22.5

30 < 30 < 30<

19 20 21 22

SUMBA TENGAH SUMBA TIMUR SUMBA TIMUR SUMBA BARAT

WANGGA WAIYENGU MBATAPUHU W U L A SODANA

123 117 8 85

8.9 13.6 2 3.4

30< 20< 30‐40 40 <

Western Eastern Eastern Western

8

Page 235 of 396

4

Metode Tahap III Survey Lapangan : 1. Watershed characteristic Melakukan observasi : Dimensi sungai, kondisi aliran air, perkiraan head. 2. Social community Pendataan kondisi demography, education, pendapatan, pekerjaan, aktivitas produksi , dsb. 3. Site accessibility Pendataan kondisi akses jalan dan akses terdekat dengan jaringan PLN 4. Public Facility Pendataan jenis dan fasilitas layanan publik: sekolah, tempat ibafah, puskesmas, dsb. 9

HASIL SURVEY TAHAP III No. 1.

Kesimpulan Rekomendasi Ada 5 lokasi sangat berpotensi Diperlukan FS dan DED untuk PLTMH mini grid

Lokasi (Desa) Pulu Panjang, Karita, Pabera Manera, Pondok, and Waikanabu Soru and Wala Ndimu

2.

Ada 2 lokasi berpotensi PLTMH Diperlukan FS & diskusi lbh disambungkan ke Jaringan PLN lanjut dg PLN Sumba

3.

Ada 1 lokasi berpotensi untuk Lebih efisien dikembangkan PLTMH namun tidak efisien, 4 km Solar PV off grid jarak intake ke pemukiman

4.

Ada 5 lokasi tidak berpotensi untuk Disambungkan dengan Wula, Kawangu, PLTMH, jarak dengan jaringan PLN jaringan PLN yang ada dg Praibakul, We Luri and relatif dekat jarak 2 Km We Kombaka

5.

Ada 6 lokasi yang tidak berpotensi Lebih efisien dikembangkan untuk PLTMH dan berjarak sangat Solar PV off grid jauh dengan jaringan PLN

Sodana

Katikutana, Kutikula, Mabaha Bakul, Maidang 1 and 2, Mabatapuhu and Wangga.

10

Page 236 of 396

5

Contoh Hasil Survey: Desa Pabena Manera

11

Analisis Finansial Deskripsi

Pulu Panjang

Karita

Pabera Manera

Pondok

Waikanabu

Potensi Pelanggan (KK)

128

90

155

100

90

Potensi (Kw)

35

40

50

25

30

Biaya Investasi (Rp juta)

1,890

2,160

2,700

1,350

1,620

Produksi Listrik (Kwh/bulan)

8.820

10,008

12,600

6,300

7,560

Pendapatan (Rp jt/bulan)

6,175

7,056

8,820

4,410

5,292

Biaya O & M (Rp/bulan)

3,700

4,233

5,292

3,080

3,175

Pendapatan Bersih (Rp juta/bulan)

2,365

2,823

3,528

1,330

2,116

12

Page 237 of 396

6

Potensi Resiko • Melesetnya biaya rencana investasi (transportasi logistik) dikarenakan kondisi akses jalan yang buruk. • Pengalaman kemauan membayar yang rendah di Pulau Sumba berisiko terhadap keberlangsungan operasi dan pemeliharaan • Terbatasnya ketersediaan penyedia jasa setempat untuk memenuhi memasok peralatan PLTMH di Pulau Sumba • Apabila mengacu kepada peraturan yang ada maka diperlukan izin tarif dari Pemerintah daerah melalui Peraturan Daerah, dan ini akan memakan waktu cukup lama dikarenakan harus dibahas bersama DPRD Provinsi.

13

Terimakasih

Page 238 of 396

7

Studi Pendahuluan Tentang Kemungkinan Pembuatan Storage Hydro (Bendungan) Untuk Pembangkit Tenaga Listrik di Sumba 15 Desember 2015

Pemilihan & Penilaian Lokasi Pemantauan Sungai Kambaniru

2

Temuan Umum 14/12/2015 ARTELIA

Daftar Isi

Tujuan & Ruang Lingkup Kegiatan

Page 239 of 396

Daftar Isi

Tujuan & Ruang Lingkup Kegiatan Pemilihan & Penilaian Lokasi Pemantauan Sungai Kambaniru

14/12/2015 ARTELIA

3

Temuan Umum

Tujuan & Ruang Linkup Kegiatan Tujuan Umum Program Sumba Sebagai Pulau Ikonik Energi Terbarukan Meningkatkan rasio elektrifitas dari 30% saat ini menjadi 95%, Meningkatkan produksi listrik dari sumber energi terbarukan dari 15% saat ini menjadi 100%.

Tujuan Khusus Pembangkitan yang dapat di-dispatch dibutukan untuk mencapai tujuan umum tersebut sisi operasi sistem Kajian sumber daya EBT didanai oleh ADB mengidentifikasikan tiga calon lokasi PLTM dengan bendungan. Dikonfirmasikan oleh least- cost analysis. Study pendahuluan ini didanai oleh AFD sebagai dasar untuk menentukan apakah lokasi tersebut menjamin pengembangan lebih lanjut.

Aktifitas

Aktifitas 2 / Penilaian Lokasi (November 2014 – Pebruari 2015) Aktifitas 3 / Persiapan pembuatan kurva durasi arus Sungai Kambaniru River - 2015

Desain stasiun pengukuran hidrologi dan arus air Pengoperasian stasiun pengukuran hidrologi dan arus air Laporan berupa rekomendasi apakan pembangunan harus terus untuk setiap lokasi, dan juga penjabaran langkah berikutnya. Kurva durasi arus Sungai Kambaniru

Page 240 of 396

4

(November – Desember 2014)

Hasil yand diperoleh

14/12/2015 ARTELIA

Aktifitas Aktifitas 1 / Desain & pemasangan stasiun pengukuran hidrologi serta arus air

Daftar Isi

Tujuan & Ruang Lingkup Kegiatan Pemilihan & Penilaian Lokasi Pemantauan Sungai Kambaniru

14/12/2015 ARTELIA

5

Temuan Umum

Penilaian Lokasi Proses pemilihan lokasi Untuk memaksimalkan potensi kontribusi PLTM bendungan, tiga daerah aliran sungai (DAS) terbesar dan dekat jaringan PLN diidentifikasikan: Praikalala, Kadahang & Kambiniru Karena lokasi Kambiniru akan dibutuhkan perpindahan tempat tinggal, Bupati Sumba Timur meminta lokasi itu tidak diprioritisasikan Kambiniru

Praikalala Kadahang

14/12/2015 ARTELIA

6

Ada 9 DAS > 200 km2 Di Pulau Sumba

Page 241 of 396

Penilaian Lokasi Lokasi yang memungkinkan Studi teoritis dilakukan pada peta topografi sekala 1:25.000 dan citra satelit untuk mendukung pekerjaan dilapangan. Beberapa konfigurasi dipertimbangkan di masing-masing lokasi Lokasi

Struktur

Aksesibilitas

Sungai MEMBORO (nama lokasi: Praikalala)

Bendungan Praikalala dengan Melalui jalan saluran pembawa terowongan, Memboro-Waiurang pembangkit 3.5 MW

Sungai KADAHANG (nama lokasi: Kadahang)

Bendungan Kadahang melalui terowongan, pembangkit yang dihasilkan 5 MW

14/12/2015 ARTELIA

7

Melalui jalan PantaiCemara – dan jalan desa Tapendang

Rencana Praikalala

14/12/2015 ARTELIA

8

Photo Fig 5-1 du rapport

Page 242 of 396

14/12/2015 ARTELIA

9

Rencana Praikalala

Rencana Praikalala Rencana ini mencakup 10 sampai 20 m tinggi bendungan dan berlokasi 1.5 km ke hulu di pertemuan dengan Sungai Loko Madori, 1.5 km terowongan saluran pembawa (headrace tunnel) Sebuah bak penenang sebagai ruang penampung pipa pesat (penstock) Pembangkit listrik dengan ketinggian (head) 55m dan daya terpasang 3.5 MW

14/12/2015 ARTELIA

10

Rencana Operasi akan disesuaikan dengan jenis pembangkitan Run of River (RoR) yang disesuaikan dengan kebutuhan harian mengikuti kurva permintaan energi listrik dari jaringan PLN (grid). Ketinggian bendungan akan cukup untuk membuat reservoir dengan volume air yang dibutuhkan harian untuk operasi sistem.

Page 243 of 396

14/12/2015 ARTELIA

11

Rencana Hulu Kadahang

Rencana Hulu Kadahang

14/12/2015 ARTELIA

12

Photo Fig 5-6 du rapport

Page 244 of 396

Rencana Hulu Kadahang Rencana ini mencakup 10 - 20 m tinggi bendungan dan berlokasi di hulu Sungai Kadahang 2.1 km saluran pembawa (headrace tunnel) yang terbuat dari beton terbuka Sebuah bak penenang sebagai ruang penampung pipa pesat (penstock) Pembangkit listrik dengan ketinggian (head) 55m dan daya terpasang 5 MW Rencana Operasi akan disesuaikan dengan jenis pembangkitan Run of River (RoR) yang disesuaikan dengan kebutuhan harian mengikuti kurva permintaan energi listrik dari jaringan PLN (grid). Seperti rencana Praikalala

14/12/2015 ARTELIA

13

Ketinggian bendungan akan cukup untuk membuat reservoir dengan volume air yang dibutuhkan sehari-hari.

Kondisi Geologi

Semua kondisi geologi berada dalam formasi sedimen, dengan napal, batu pasir, tufa dan sisipan batu gamping Dalam semua kasus, masa batuan secara umum terlihat mempunyai karakteristik mekanik rendah, meskipun berada pada lebih dari 100 - 150 m tebing yang tinggi atau lereng yang sangat curam dan juga terdapat pada lapisan yang kompeten yang dapat diamati kejadiannya di tepi lembah.

14/12/2015 ARTELIA

14

Kami dapat mempertimbangkan bahwa karakteristik mekanik masa batuan adalah cukup untuk mendukung struktur gravitasi sederhana (<50 m), tetapi masalah utama adalah permeabilitas masa batuan tersebut. Hal ini harus mendapatkan perhatian khusus apabila ingin membangun bendungan dengan volume air yang cukup besar.

Page 245 of 396

Kapasitas Setiap Rencana Praikalala

Kadahang

Mean annual rainfall mm Annual runoff mm Catchment area km²

2500 928 240

2250 740 440

Average inflow Mm3/year

222.72

325.6

7.06

10.32

12.5 m

25 m

12.5 m

25 m

1.99 4.86 0.21 1.90 2.60 11.56

6.72 4.86 0.21 2.00 2.60 16.39

8.68 6.81 0.48 2.90 1.20 20.08

23.75 6.81 0.48 3.00 1.20 35.24

6.43 0.40

6.79 0.40

7.64 0.50

8.21 0.50

18.40

23.58

28.22

43.95

Installed Power MW :

3.32

3.86

4.63

5.64

Energi yang dihasilkan GWh :

21.57

25.06

30.18

37.14

0.10

0.11

0.11

0.14

Construction cost M US$Dam Headrace tunnel Penstock Power station Access road Total civil works M US$ M&E equipment Transmission line Total CW + M&E + TL M US$

Biaya pokok produksi

US$/kWh

Biaya pekerjaan sipil yang diperkirakan berdasarkan pengalaman internasional dan diperiksa terhadap model MITI

BPP proyek ini dibawah FiT sesuai Permen ESDM 19/2015

15

Ketinggian Bendungan

14/12/2015 ARTELIA

Average discharge

m3/s

Hidrologi berdasar curah hujan dan metode Turc, konsisten dengan pengalaman PLTM lain di Sumba.

Penilaian Awal Dampak Sosial Praikalala 25 50

Kadahang 12.5 25 50

Kambiniru/Maidang 25 50

Perkiraan jumlah rumah tangga terdampak dengan pendekatan analisa kedekatan penduduk (proximity)

0

0

0

0

0

0

21

72

Perkiraan jumlah Penduduk terdampak dengan pendekatan analisa kedekatan penduduk (proximity)

0

0

0

0

0

0

98

331

Jumlah Bangunan dari analisa digital peta BIG

0

0

0

0

0

0

52

101

Perkiraan jumlah rumah tangga terdampak dengan pendekatan analisa digital peta BIG

0

0

0

0

0

0

42

81

Perkiraan jumlah penduduk terdampak dengan pendekatan analisa digital peta BIG

0

0

0

0

0

0

192

371

Perhitungan manual jumlah bangunan menggunakan citra satelit Google Earth (2013)

0

0

0

0

0

0

66

104

Perkiraan jumlah penduduk terdampak dengan pendekatan analisa digital peta BIG

0

0

0

0

0

0

302

476

Tiga metodologi yang digunakan untuk menghitung jumlah rumah tangga yang akan terdampak: Lokasi terdampak genangan relatif terhadap sebaran populasi vs populasi analisis kedekatan sebaran penduduk Analisa peta digital dari Badan Informasi Geospasial (BIG) yang mengidentifikasikan struktur Bangunan. Analisa manual menggunakan citra satelit Google (2013) untuk menghitung struktur individual bangunan di daerah dampak genangan. Page 246 of 396

16

12.5

14/12/2015 ARTELIA

Tinggi Bendungan (m)

Daftar Isi

Ringkasan Tujuan & Ruang Lingkup Kegiatan Pemilihan & Penilaian Lokasi Pemantauan Sungai Kambaniru

14/12/2015 ARTELIA

17

Temuan Umum

Hidrologi diasumsikan Asumsi hidrologi – Berdasar data curah hujan dan metode Turc – Konsisten dengan pengalaman PLTM Lokomboro

18

Kadahang

14/12/2015 ARTELIA

Praikalala

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Tujuan stasiun hidrologi

14/12/2015 ARTELIA

– Desain dan evaluasi pembangkit listrik tenaga air memerlukan informasi yang akurat dari kurfa durasi arus sungai (FDC) – Sekarang ini, tidak ada FDC yang akurat untuk Sumba • Belum ada sungai di Sumba yang di ukur secara langsung • Model Hidrologi belum dikalibrasi untuk kondisi di Sumba • Proyek PLTA seperti Lokomboro hanya menyediakan data untuk produksi energi listrik, dimana tidak ada data mengenai aliran yang terjadi selama perioda pemadaman listrik atau banjir – Stasiun hidrologi dapat memberikan data satu tahun atau lebih untuk mendukung investasi yang berhubungan dengan masalah hidrologi – Data ini dapat dikalibrasi terhadap data curah hujan untuk perkiraan jangka panjang • Beberapa stasiun cuaca di Sumba mempunyai > 10 tahun data curah hujan – Lokasi di Maidang pada Sungai Kambiniru dipilih untuk pengukuran stasiun hidrologi sementara, dengan alasan: • Mempunyai DAS terbesar di Sumba • Berpotensi untuk dibangun bendungan yang besar • Hasilnya dapat di ekstrapolasikan ke DAS lainnya di Sumba

19

Kegunaan stasiun hidrologi sementara di Sumba

Pengukuran Debit Air di Maidang

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14/12/2015 ARTELIA

Lokasi terbaik terdapat di Jembatan Maidang yang berada di Sungai Kambaniru – Lebar Sungai: 50m – Aliran sungai terendah (November): 4.4 m/s Aksesibilitas yang bagus Penjaga stasiun dapat diperoleh dari desa terdekat Kondisi hidrolik dapat diterima Salm on alat ukur yang dapat di pasang dari atas jembatan AWLR (Pengukur ketinggian air otomatis) sudah dipasang Pengukuran arus air dapat dilakukan secara periodik sepanjang tahun AWLR data dapat digabungkan dengan pengukuran arus sungai untuk mendapatkan kurva durasi arus sungai (FDC) Hasilnya dapat dibandingkan dengan data curah hujan jangka panjang dari stasiun pengamatan cuaca BMKG di Malahar, Tanarara and Waingapu

20

Lokasi Sungai Kambaniru

Hasil sampai saat ini Hasil 11 bulan pertama AWLR dipasang sejak awal Januari 2015 Pengukuran debit air ongoing Kurva durasi arus sungai untuk tahun pertama diharapkan pada triwulan pertama tahun 2016

Hidrograf di Maidang

400 350

Period of maximum wind and solar output

Level of River, cm

300 250 200 150 100

Jun 2015

Nov 2015

Daftar Isi

Ringkasan Tujuan & Ruang Lingkup Kegiatan Pemilihan & Penilaian Lokasi Pemantauan Sungai Kambaniru Temuan Umum 22

Jan 2015

14/12/2015 ARTELIA

‐50

Anomaly due to low water conditions; to be corrected

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0

21

50

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Resiko utama Hidrologi –

Pengukuran sungai di Sumba sedang berjalan.

Geologi –

Survei lapangan pendahuluan dibutuhkan.

Biaya diperkirakan –

Lokasi terpencil

–

Terowongan

Implementasi Permen ESDM 19/2015 Struktur PJBL –

PJBL yang berlaku saat ini tidak membayar kapasitas pembangkit yang tersedia, hanya membayar energi yang diproduksi

–

Konsep PJBL yang diusulkan oleh PLN sesuai Permen ESDM 19/2015 mungkin bisa mengatasi kapasitas tersedia tapi tidak dapat digunakan karena gangguan jaringan PLN

–

Lebih baik kalau bisa menggunakan PJBL struktur biaya ABCD Biaya produksi PLTM lebih rendah dibanding PLTD – bahkan jika tidak ada pertumbuhan beban

–

Dukungan pemda

–

Dukungan biaya pengembangan, e.g. Infraco

14/12/2015 ARTELIA

–

23

Faktor yang menringankan

Temuan Utama Lokasi terbaik dari sisi biaya pokok produksi adalah: Dua Sungai, Kadahang and Praikalala, tampaknya layak untuk studi lebih lanjut sebagai bendungan kecil sebagai kolam penampungan air harian

Langkah Berikutnya

14/12/2015 ARTELIA

24

Hidrologi : Melanjutkan penyusunan data hidrologi Pemaparan dan sosialisasi temuan kepada para pemangku kepentingan Geologi : Melakukan kajian aspek geologi (~USD 15,000) Kompilasi semua informasi yang berhubungan dengan aspek geologi dan hidrogeologi pada sekala lokal dan regional, Kunjungan lapangan pada lokasi yang diidentifikasi sebagai bendungan yang potensial. Topografi: Survei topografi untuk mengkonfirmasi ketinggian bendungan dan penampang melintang ketinggian sekitar bendungan. Studi Kelayakan: Pembaharuan hasil analisa dari masalah yang berhubungan dengan teknis, keuangan, sosial dan lingkungan

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ARTELIA2525 14/12/2015 ARTELIA

Terima Kasih atas perhatiannya

Page 251 of 396

Wind Resource Assessment and Pre‐feasibility for Wind Energy Projects in Sumba

Investor Forum December 15, 2015 Pramod Jain, Ph.D. President, Innovative Wind Energy, Inc. pramod@i‐windenergy.com +1‐904‐923‐6489

IWE

1

Agenda • Project description • Background and work/analysis conducted to date – Preliminary wind resource assessment

• • • •

Demand analysis Expected wind regulations Preliminary financial assessment Key risks

IWE

2

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Sumba Iconic Island Initiative Least‐cost Generation Plan • The least‐cost generation plan determined wind power penetration of 10MW by 2025 • Wind measurement campaign was initiated to better understand the wind resource • 3Tier and past wind data was used to determine that Hambapraing was the area with good wind resource • Hambapraing has reasonably good road and grid access, and is in planned route for higher voltage transmission line that will interconnect east and west parts of Sumba • 60 meter met‐mast was installed in Hambapraing in October 2014 • After the culmination of one year of wind measurement, a preliminary wind resource assessment and wind project financial assessment is being undertaken

IWE

3

Project Description • 10MW wind farm in the Hambapraing area of Sumba • 12 turbines, each of size 0.85MW

Area of interest

IWE

4

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Site Details

HIVOS 33m met‐ tower

ADB 60m met‐ tower

Road, 20kV line

Highest wind resource area

IWE

5

Summary of one year data from ADB met‐mast • Wind data from 57m anemometer & 53m wind vane • Data corrected for missing data and long‐term correction

IWE

6

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Turbine Selection and Locations Logistical capabilities suggest that 0.85 MW wind turbine generator (WTG) with 65m hub height and 52m rotor is the largest WTG that can be transported and deployed at reasonable cost in Sumba

Road, 20kV line

8x0.85MW WTGs Elevation: 465m

4x0.85MW WTGs Elevation: 426m IWE

7

Wind Resource Map of Hambapraing with Micrositing

Area 1 8 WTGs

Area 2 4 WTGs

• Red zones have the highest wind density • One Kilometer away from the measurement tower is a red zone • Resolution is 100m by 100m • Area 1 near met‐tower can site 8 WTGs • Area 2 can site 4 WTGs

IWE

8

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Micrositing of 12x0.85MW WTGs • Eight WTGs in Area 1 and four WTGs in Area 2 are sited with a distance of 10D • Contour plot of the area is displayed • Wind rose at the turbine sites show the primary direction of wind is ESE

IWE

9

Average annual energy production (AEP) WTG

Latitude (m)

Longitude Elevation (m) (m)

1 2 3 4 5 6 7 8 9 10 11 12

189049.3 188910.7 188772.1 188633.5 188494.9 188356.2 188217.6 188079 191596.3 191591.3 191603 191717.8

‐1054305 ‐1054385 ‐1054464 ‐1054544 ‐1054624 ‐1054704 ‐1054784 ‐1054864 ‐1060845 ‐1061019 ‐1061215 ‐1060700

464.8 470.4 471.5 474.4 469.6 465 461.2 460.4 428 426 427.6 425.1

Wind speed (m/s) 7.31 7.33 7.33 7.38 7.33 7.29 7.26 7.26 7.55 7.53 7.52 7.55

Gross AEP (GWh) 2.578 2.596 2.595 2.637 2.603 2.577 2.551 2.551 2.754 2.738 2.739 2.755

Net AEP (GWh)

Wake loss (%)

Capacity factor

2.521 2.527 2.53 2.572 2.544 2.523 2.505 2.537 2.726 2.714 2.737 2.727

2.22 2.66 2.52 2.44 2.26 2.09 1.77 0.53 0.99 0.87 0.08 1.04

0.339 0.339 0.340 0.345 0.342 0.339 0.336 0.341 0.366 0.364 0.368 0.366

Net AEP of 12 WTG wind farm = 31.163 GWh AEP and capacity factors are before losses IWE

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Page 256 of 396

Losses and Uncertainty of AEP 10% losses Net AEP (GWh)

Net AEP after losses (GWh)

Net Capacity factor

31.163

28.047

31.4%

12% uncertainty Exceedance Probability Type P50 P75 P90 P95

AEP (GWh) As an example, AEP at P90 is 23.72 GWh, which means that there is 90% confidence that the AEP will be 23.72 GWh or more.

28.047 25.775 23.722 22.510

Wind Energy Belongs in the Least‐Cost Plan • Levelized Cost of Energy for wind energy is cheaper than diesel in Sumba • The high quality resource is in the Hambapraing area • Sufficient land area is available for 10MW wind farm • Measurements are ongoing in Leipori; it may have potential for wind development • Hence wind uptake is not limited by the resource or cost of competing technologies but by the ability of the grid to absorb production • The least‐cost planned assumed that wind capacity could not exceed 25% of peak system demand. Current system peak demand is around 11 MW with 15% grid electrification ratio. Over 10 years this is forecast to grow to about 40 MW if the target of 95% electrification ratio is achieved. IWE

12

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Wind Energy Policy • ESDM is developing wind energy feed‐in tariff (FiT) • Eastern island grid that are primarily supplied by diesel are expected to get FiT of 28 US cents per kWh • Proposed regulation requires PLN to conduct grid integration study to determine level of wind energy penetration • To qualify developers should have completed at least one year of wind measurement

IWE

13

Preliminary financial assessment: Assumptions

Total installed cost (TIC) Total O&M Costs Annual escalation of O&M Size of wind farm Sale price of energy Depreciation Tax rate, WACC* Life of project Financing Structure Debt duration/interest Required return on equity Investment tax deduction (ITD) ITC years Turbine

Scenario 1 $2,303/kW $0.11/kWh 0% 10.2MW $0.280/kWh 15‐yr accelerated 25%, 13.8% 15 years 70% debt/30% equity 8 years/12% 18% 5%

Scenario 2 $2,098/kW $0.05/kWh 5% 10.2MW $0.280/kWh 15‐yr accelerated 25%, 13.8% 15 years 70% debt/30% equity 8 years/12% 18% 5%

6 years Vestas V52‐850kW

6 years Enercon 850kW

IWE

14

Page 258 of 396

Preliminary financial assessment: Results

Annual Energy production (GWh) Total Installed Cost (million $) Total Annual Revenue (million $) Project IRR, after‐tax (%) Return on Equity, after tax (%) Debt service coverage ratio Simple payback period on equity (years) Levelized Cost of Energy (current $/kWh)

Scenario 1 P50 P75 P90 28.047 25.775 23.722 $23.49 $23.49 $23.49 $7.85 $7.22 $6.64 17.2 15.7 14.2 24.1 20.6 17.5 1.49 1.37 1.26

Scenario 2 P50 P75 P90 28.047 25.775 23.722 $21.40 $21.40 $21.40 $7.85 $7.22 $6.64 24.7 22.6 20.7 44.7 38.8 33.7 2.12 1.94 1.79

5

7

9

3

3

3

$0.245

$0.257

$0.270

$0.187

$0.198

$0.210

IWE

15

Key Risks Success of 10MW of wind power installations is predicated on the following • Growth in demand from 10MW in 2015 to 40MW in 2025 • Interconnection of east and west grids of Sumba with 70kV or higher voltage line • Ability of grid to absorb 10MW of wind power – Concentration of wind projects in one area may cause grid integration issues, which needs to be studied – Energy storage may be required in the grid, which would increase cost – Hybrid controllers for managing diesel, hydro, solar PV and wind generators and high‐speed communication network would be required to manage the projected mix of generation – Wind energy forecasting and tools for system operations IWE

16

Page 259 of 396

Key Risks Success of 10MW of wind power installations is predicated on the following: • Wind tariff of 28 US cents per kWh • Required upgrades to port, roads and bridges as recommended by the logistics study can be implemented • Project siting study for microwave, radar, and aviation airspace interference do not uncover any issues • Environmental impact assessment for birds, wildlife and others does not uncover any issues • Land access is granted in a timely manner

IWE

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Page 260 of 396

ADB TA 8287‐INO: Scaling Up Renewable Energy Access in Eastern Indonesia Pre‐feasibility Study on Biomass Power Projects in Sumba Island Jakarta 14 December 2015

CONTENTS • • • • • • • •

Section 1: Project objectives Section 2: Physical description of the project Section 3: Background and work/analysis conducted to date Section 4: Demand analysis Section 5: Legal basis Section 6: Financial analysis Section 7: Key risks Section 8: Conclusion

Page 261 of 396

1

Section 1 Project Objectives • Assessment of potential biomass resources in Sumba Island • Assessment of small‐scale biomass combined heat power, gasification and direct‐fired combustion technology based on the biomass resources availability • Assessment on economically available biomass fuel (Project site selection) • Conduct financial analysis of small scale Biomass power plant in Sumba Island

Physical Description of the Project • Identification of potential Biomass sources for electricity generation through on‐site survey, conducted in the periode 2013 ‐ 2014 • Assess technically and financial feasibility on the development of Biomass Power Plant for electricity generation based on the potential biomass sources in the Sumba Island

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2

Background and work/analysis conducted to date Background • •

Program: developing renewable energy in Sumba Island (including from biomass energy), for achieving 100% renewable energy and 95% electrification ratio by 2025 Electricity from biomass: 10 MW (by 2025)

Biomass identification in Sumba Island Type Biomass

Remarks

Food crops residues ‐ Rice husk, maize, cobs, coconut shells, candle nut shells

Generally, constraints by its availability rice husk (only low potential ± 0.5 MW, constraints by seasonal variation and climate in Sumba Island and collection method)

Forest plantation ‐ Leucana Leucochephala (Lamtoro Gung)

‐ Ensure for not disturbing local food security ‐ high productivity plant (30 ton/ha/year), grows even in arid land throughout Sumba Island

Background and work/analysis conducted to date •

Review of potential forest plantation candidate sites, following the communication with local stakeholders (Dinas Kehutanan Sumba Timur, Dinas Kehutanan Sumba Barat and Dinas Kehutanan Sumba Tengah and PT Usaha Tani Lestari)

Regency/location

Village

Sub‐district

Potential area (ha)

Wood productivity (tons/year)

Technical Potential (tons/year)

Power Generation MWh/year

Sumba Timur (Candidate 1)

Meu Rimba

Kahaungu Eti

36,965

1,108,950

776,265

579,442

Sumba Timur (Candidate 2)

Rakawatu

Lewa

19,748

592,440

414,708

309,558

Sumba Tengah (Candidate 3)

Soru

Umbu Ratu Nggay

6,350

190,500

133,350

99,539

Sumba Barat (Candidiate 4)


Lamboya

4,720

141,600

99,120

73,988

* Assumptions: Biomass potential from Lamtoro Gung ,wood yield 30 tons/ha/year and technical availability of biomass 70%, with average calorific value 19.25 kJ/kg (4,597 kcal/kg).

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3

Background and work/analysis conducted to date Map indicating candidate locations for Lamtoro Gung energy plantation

Background and work/analysis conducted to date • Preliminary fuel analysis: Estimated land required for electricity generation capacity No

Remarks

Amount required

1



2



3

Wood Chip required from Lamtoro Gung tree (MC: 40%)

1,152 tons/month

4

Wood Chip required from Lamtoro Gung tree (MC:40% and 330d/y)

12,672 tons /year

5

Planting area for Lamtoro Gung tree (70% availability)

603.5 ha

6

Annual harvesting product (MC:40%)

30 tons/year/ha

7

An area of 1000 ha (70% availability) could produce wood log with diameter of 5 cm

21,000 tons/year

Assumption: 20% moisture content

Page 264 of 396

4

Background and work/analysis conducted to date Forest plantation Forest plantation (Lamtoro Gung) as biomass source for electricity managed by a third party (for securing biomass and biomass price) ‐ The location of plantation should be at reasonable distance from Biomass Power Plant (for acceptable transport price) ‐ Sumba Timur and Sumba Tengah (mainly savannah area, >60% of proposed sites area) Proposed sites for Lamtoro Gung energy plantation in Sumba Island Regency/ Candidate site Sumba Timur (Candidate 1) Sumba Timur (Candidate 2) Sumba Tengah (Candidate 3) Sumba barat (Candidate 4)

Village

Sub‐district

Meu Rimba

Kahaungu Eti

Rakawatu

Lewa

Soru

Umbu Ratu Nggay


Forest 37% (Protection forest) 9% (Production forest) 8% (Production forest) 35%

Savannah


Potential area (ha)

60%

3%

36,695

90%

1%

19,748

90%

2%

6,350

60%

5%

Lamboya

4,720


Estimation cost of forest‐sourced fuel

Biomass pre‐treatments/processing options: ‐ Physical process: particle size reduction, separation (screening), drying, compaction/pelletizing Costs related to preparation of biomass as fuel: Drying • Fresh woody Lamtoro Gung : MC 30‐50% MC must be reduced • Accepted Lamtoro Gung for fuel: MC 20% If possible: air‐dry to MC 30% (thereby save energy for drying, and thus the cost) Transportation ‐ From the forest landing to the power generation plant ‐ Transportation costs are calculated based on distance traveled and diesel fuel cost of Rp 6000/litre Projected Biomass purchasing and cost ‐ Assumed to be purchased from a third party (appointed by local government which is also responsible for the management of the plantations and harvesting) ‐ Estimated industrial plantation forest development cost pert ha would be Rp 15,356,350/Ha

Estimated cost and price of woody biomass in Sumba: • • •

wood production Rp 239,523/ton and delivery cost Rp 25,000/ton. products are sold at price of Rp 450,000/ton For feasibility report: assumed that the price of biomass is 40 USD per ton on air dry base (not wet, not dry weight)., excludes chipping cost after harvesting wood

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5

Background and work/analysis conducted to date Cost estimation of industrial plantation forest development per ha No Activity I. Non loan‐Cost component /Komponen Biaya Bukan A. Planning 1 Preparation of FS and EIA 2 Preparation RKUPHHK 3 Preparation RKTUPHHK 4 IMB (building permit) cost 5 Boundaries (Tata Batas) 6 Layout area Total A B.

Unit

Development of facilities and infrastructure 1 Making Building, Procurement and Construction Equipment Road 2 Maintenance of Infrastructure Total B

C. 1 2 3 4

Administration and general Education and Training Research and development General costs Appraisal Total C Total I

Cost/Unit

Ha Ha Ha Ha Ha Ha

32,500 25,000 12,500 14,000 40,000 196,000 320,000

Ha Ha

2,450,000 32,750 2,482,750

Ha Ha Ha Ha

49,000 98,000 980,000 71,000 1,198,000 4,000,750

Background and work/analysis conducted to date Estimated cost II. Cost component of revolving loan fund as working capital A. Planting 1 Nursery and Seedling 2 Land preparation 3 Cultivation Total A B. 1 2 3 4 5

C.

Maintenance Maintenance Year I Maintenance Year II Maintenance Year III Further Maintenance I Further Maintenance II Total B

Protection and Forest safeguard 1 Pest and Disease control 2 Fire control 3 Security Forests Total C

D.

Food crop cost (in a agroforestry pattern) Total D

E.

Obligation to the country (fee, land value tax) 1 contribution IUPHHK 2 Property taxes Total E Total II

Ha Ha Ha

2,420,000 3,214,000 684,000 6,318,000

Ha Ha Ha Ha Ha

1,082,000 852,000 748,000 425,000 213,000 3,320,000

Ha Ha Ha

260,000 110,000 122,000 492,000

Ha

1,000,000 1,000,000

Ha Ha

2,600 3,000 5,600 11,135,600

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6

Estimated cost ‐ Lanjutan III. Cost component which can be borrowed or not as revolving fund E Liability To the Environment 1 Physical Chemistry Biology Ha 98,000 2 Social Environment Ha 122,000 Total E 220,000 Total III 220,000 Total (I+II+III)

15,356,350

Background and work/analysis conducted to date Fuel supply agreement options: o Wood delivered to storage facility in the form of wood log o Wood delivered to storage facility in the form of wood chip • Technology options For biomass utilized as fuel for electricity generation other than heat: ‐ Direct combustion in conventional boiler/steam turbine/condenser technology ‐ Gasification with selection of gas turbine or internal combustion engine

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7

Background and work/analysis conducted to date Selection of power generation technology Items

Gasification

Combustion

Remarks

Plant capacity

Minimum 10 kW

Economical combustion – steam power generation process > 3 MWe

Direct combustion technology is mature (proven) than gasification but direct combustion has higher emissions and a less efficient conversion process

Electrical Efficiency

biofuel‐to‐electricity efficiency 30‐40 % and overall performance efficiency around 90 %

15‐35%

Utility‐water

Elimination of water use, if power generation without steam turbine

5.3 m3/MWh*)

Engine

Gas engine

Combustion is usually carried out in a boiler to generate steam for electricity generation by steam turbine. the electrical efficiency is greater than by steam turbine. Biomass power plant is to be developed in Sumba Island with dry climate area low cost, and reliability; it also works well even at low loads

Status of technology

Mature

mature

*) Source: CENTRAL ELECTRICITY AUTHORITY New Delhi ‐ India, 2010 Review of Land Requirement for Thermal Power Stations

Background and work/analysis conducted to date Selection of power generation technology Biomass Power Plant: gasification technologies • Status of the technology (commercialized Gasification technology for woody biomass power plant) • Plant capacity • Minimal water use Drawback gasification: ‐ requires short maintenance interval resulting in low availability ‐ Biomass gasification results in tars (but solved with gas cleaning system)

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8


Estimate size of power facility

Size of Biomass power plant ‐

dimensioned with regard to potential available Lamtoro Gung wood chips in respective candidate sites and reasonable plant size

Candidate site

Power Plant size * (MW)

Connection distance to 20 kV PLN’s grid

Kapohakpenang (Candidate 1)

61.26

50 km

Rakawatu (Candidate 2)

32.73

15 km

Pahedutili (Candidate 3)

10.52

12 km

Lamboya (Candidate 4)

7.82

5 km

*Based on technical potential of lamtoro gung wood and the selected technology is gasification and Technical availability was assumed to be 70%

•

Power plant location Reasonable distance from the plantation to the power plant: maximum 20 km (related to the transportation cost of the harvested wood from the plantation sites to the plant)

•

Grid connection The electricity generated from the plant is to be connected to PLN’s grid as local demand is lower than the generation.

Background and work/analysis conducted to date Biomass power plant operation, assumptions: ‐ Load factor: 77% (for all candidate sites) Gasification Plant configuration:

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9

Demand analysis Electricity in Sumba Island Current supply: 55% from renewable energy Peak load (2013/2014): 10.3 MW (PLN‐RUPTL 2015 to 2024)

Plan PLN: increase capacity from 16.0 to 21.7 MW over 2014 – 2020 (RUPTL 2015‐ 2024), consisting of 6.7 MW diesel capacity in operation, 3.0 MW of biomass capacity, 0.5 MW of hybrid, and the remaining 11.5 MW as small hydro. 1 MW Biomass PP (RUPTL 2012‐2023)

Demand analysis • Despites the potential of the wood available in all candidate sites capable for producing > 2 MW, it is suggested to develop biomass power plants of 1 MW (based on projected electricity demand over 10 years in the Island only around 10 MW, and considering the capability of PLN transmission line to which the electricity of the plant is connected) • Grid connection The electricity generated from Biomass plant is to be connected to PLN’s grid as local demand is lower than the generation.

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10

Legal Basis Candidate site 1: Sumba Timur regency • An area of 36,000 ha suggested for the energy plantation: located in Meu Rimba Village, Kahaungu Eti Sub‐district. area (3%), about 37% protection forest • 500 ha of Candidate 1 was converted to community forest based on Decision of the Ministry of Forestry (Surat Kuasa) 110/Menhut‐II/2009. An additional conversion of 2,754 ha from the protected forest at this Candidate location to community forest is being proposed by the Forestry Office of Sumba Timur to the Ministry of Forestry. • obtained business License on Industrial Forest Plantation (hutan tanaman industri /HTI) from The Ministry of Forestry based on SK.216/Menhut‐11/2013, 25 March 2013 for an area of 41,515 ha consisting of 4,720 ha in Sumba Island (Sumba Barat Regency) and of 36,795 Ha in Flores Island (Kupang Regency). Candidate site 2: Sumba Timur regency • The proposed site is located in Rakawatu Village, Lewa Sub‐district totalling an area of 19,000 ha. Most of this is savannah area (90%) though about 1% is a farm area and the remaining is production forest. Candidate site 3: Sumba Tengah regency • The 3rd site proposed for the energy plantation is in Soru village, Umbu Ratu Nggay Sub‐district. savannah (90%) while farm land constitutes of only 2%. also covers protection forest which could be used for energy plantation. Candidate site 4 : Sumba Barat regency • The site covers an area of 4,720 ha and is in Lamboya Sub‐district. This area is under the management of a private company, PT Usaha Tani Lestari. • the Indonesian forestry laws and regulations allow the use of Protected Forests (Hutan Lindung) and Production Forests (Hutan Produksi) for uses like forest energy plantations.

Legal Basis • electricity price specified in the Ministerial regulation No.27/2014 on small and medium scale power generation from biomass and biogas • Indonesia current day electricity tariff for medium voltage is IDR 1150 / kWh x F (=IDR 1840/kWh)

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11

Financial Analysis • •

Calculation based on cost data in 2014 Basic currency: Indonesia Rp is US $1=Rp 13,000

•

Project cost structure 1 MW Biomass Power Plant

No

Plant Item/Description 1 Detail Design & Engineering Charges

Quantity Lump Sum Lump Sum 2 Nos.

Biomass Sizing & Conveying System, Biomass Drying 3 Skip‐Charger Biomass Gasifier along with basic accessories and auxiliaries with Dry Gas Filtration System 2 Sets. 4 Dry Gas Filtration System Flare system Lump 5 Gasifier Cooling Tower Sum Lump 6 Condensate Neutralization System Sum Lump 7 52 TR Chiller Sum 2

8 Producer Gas Engine & Other Related Accessories 5 Nos. 9 Radiator for Engine Cooling Sub Total 10 Packing & Transportation Charges 12 13 14 15

Startup Power For The System Installation and Civil & foundation work Grid Interconnection Building Total Contingency (4%) Total Plant Cost

Lump Sum

Basic Price in USD Site 1 Site 2 52,195

52,195

Site 3 52,195

Site 4 52,195

125,000 125,000 125,000 125,000 43,510

43,510

43,510

43,510

1,042,460 1,042,460 1,042,460 1,042,460

26,320

26,320

26,320

26,320

48,430

48,430

48,430

48,430

95,940

95,940

95,940

95,940

732,475 732,475 732,475 732,475 (5 x (5 x (5 x (5 x 146,495) 146,495) 146,495) 146,495) 65,800

65,800

65,800

65,800

2,232,130 2,232,130 2,232,130 2,232,130 215,407 215,407 215,407 215,407 40,000 40,000 40,000 40,000 166,667 166,667 166,667 166,667 1,500,000 450,000 360,000 150,000 100,000 100,000 100,000 100,000 4,254,204 3,204,204 3,114,204 2,904,204 170,168 128,168 124,568 116,168 4,424,372 3,332,372 3,238,772 3,020,372

Financial Analysis Conditions for Financial Evaluation ‐ Construction term of the plant is 11 months; and term of evaluation is 20 years. ‐ Scheduled year of start‐up 2018 ‐ Unit production price is Rp 1840/kWh. Maintenance (7% Gasifier cost+0.01US$/kWh) Major overhaul (3% EPC every 5 years) Insurance (0.5% of investment cost) Biomass fuel cost Water Community Development Depreciation

US$ 146,313 US$66,964 US$ 22,122 40 US$/ton US$ 3,564 US$ 5,769/y US$ 122,168

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12

Financial Analysis Based condition (sales prices USD0.142/kWh, and biomass price is 40 US$/t) Site

IRR

Site No.1 Site No.2 Site No.3 Site No.4

9.33% 14.73% 15.35% 16.94%

Payback Period 14 year 11 year 11 year 10 year

NPV ($213,796) $365,850 $415,534 $531,463

Sensitivity of investment cost only 80% Site Site No.1 Site No.2 Site No.3 Site No.4

IRR 13.46% 20.07% 20.83% 22.80%


NPV $255,905 $719,622 $759,369 $852,112

Sensitivity of biomass price is 30 US$/t Site Site No.1 Site No.2 Site No.3 Site No.4

IRR 13.57% 20.18% 20.95% 22.92%


NPV $334.435 $914,080 $963,764 $1,079,693

Sensitivity: sales prices US$0.1538/kWh, biomass price US$40 Site Site No.1 Site No.2 Site No.3 Site No.4

IRR 13.19% 19.70% 20.45% 22.39%


NPV $285,176 $864,821 $914,505 $1,030,434

Financial Analysis •

Results of pre‐feasibility study of Biomass power plant in Sumba Island Site 1 Site 2 Site 3 Site 4 Peak Capacity (kW)‐gross 1200 1200 1200 1200 Peak Capacity (kW)‐net 1056 1056 1056 1056 Continuous duty‐gross (kW) 1020 1020 1020 1020 Continuous duty‐net (kW) 898 898 898 898 Gasifier Type Down Draft Down Draft Down Draft Down Draft Electricity to the grid (kWh) 8,363,520 8,363,520 8,363,520 8,363,520 Electricity produce (gross)‐kWh 9,504,000 9,504,000 9,504,000 9,504,000 Biomass consumption (t/y)‐ 20%MC 11,310 11,310 11,310 11,310 Biomass consumption (t/y)‐Dry Base 9,048 9,048 9,048 9,048 Biomass consumption (t/y) ‐40%MC 15,080 15,080 15,080 15,080 Parasitic load (kW) 144 144 144 144 Environment Baseline Diesel PP Diesel PP Diesel PP Diesel PP GHG reduction 2,480 2,755 2,761 2,767 (tCO2e/y) Energy substitution 1,777,248 1,777,248 1,777,248 1,777,248 effect (liter diesel oil/yr) Cost performance

Initial investment (US$) IRR Investment payback period

4,424,372

3,332,372

3,238,772

3,020,372

9.33% 14 year

14.73% 11 year

15.35% 11 year

16.94% 10 year

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13

Key Risks • Plantation establishment (critical phase of a biomass energy project) ‐ Relates to wood supply to power plant (any miss calculation can result in expensive delays in power generation) ‐ Issues that must be addressed include: site preparation, seedling or cutting supply and quality, availability of required soil microorganisms, nursery operation, spacing of plantings, fertilization, watering, weed control, road construction, protection of nursery stock and plantings from insect pests, disease, animals, humans, fire, and other threats

Key Risks •

Risks related to the Biomass fuel

Risks

Mitigation

Seasonal variation‐ climate

Variation of feedstock supply and price

Reasonable buffer stock (outdoor storage 15 days)

Plant disease

Lower production

Periodical checking and well managed plantation

Fuel supply contract

Contract violation by biomass suppliers

Insurance, possible backup source of biomass, large storage

Land availability

Lack of transparency of land acquisition or permit on land utilization

Advise from local government is necessary

Competitive users

Illegal logging

Socialization to local people for energy plantation for energy generation

Transportation distance

Price varies to distance

To include fuel price sensitivity and inflation

Fire risks

Particularly during dry season

Minimize irresponsible actions

Public acceptance

Inform public to the benefit of biomass PP

Information to stakeholders and local people

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Key Risks • Biomass Power Plant technology selection: Gasification technology ‐ The presence of tars in syngas: minimized using cleaning system technology or if necessary, pre‐ drying of wood is performed prior to gasification for sustaining combustion

Conclusion and Recommendation • It is concluded that the investment of Biomass Power Plant in Sumba is technically viable and financially feasible.

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15

The key points of the next steps • Project Proponent should review this pre‐FS in term of the project scheme, technical aspect, and financial feasibility • Project Proponent start to engage with the PLN Distribution (Wilayah) of NTT in order to get the PPA, and local authority to get environmental permit • Project Proponent engages with the EPC who will construct the plant, and the technology suppliers, especially for the gasification, gas engine, and civil work and structure construction. • Project Proponent introduce the project to the potential financing institution to get project finance as proposed

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16

6.

KICK-OFF FOR ELECTRIFICATION WORKING GROUP


December 2015

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Workshop Summary Workshop on Improving Electricity Access Using Renewable Energy Lokakarya Peningkatan Akses Kelistrikan Berbasis Energi Terbarukan di Indonesia

Doubletree Hotel Jakarta 19 March 2015

i Workshop on Electricity Access

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TABLE OF CONTENTS 1.

Introduction

1-1

2.

Agenda

2-1

3.

List of Invitee and Attendance List

3-1

4.

Summary

4-1

5.

Next Steps

5-1

APPENDICES - Presentation Materials Appendix A : Achieving Universal Electricity Access Appendix B : Electricity Access - Break-Out Groups Appendix C : Electricity Access - Lessons from SII Appendix D : Summary of Break-out Group 1 – Planning & Implementation Appendix E : Summary of Break-out Group 2 – Financing & Subsidy

ii Workshop on Electricity Access

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1.

INTRODUCTION

Indonesia has achieved monumental results in bringing electricity to 84% of its widespread population. In the past 10 years alone, PLN, the national electric utility, has managed to connect approximately 20 million households, or some 78 million people. However, the approaches to electrification that have served the country so well in the past are increasingly ill-suited to reaching the remaining 16% of its population, representing nearly 40 million people. In combination with the continuing extension of the grid, these remaining connections may also require alternative approaches incorporating clear service quality standards, innovations in planning and financing, new implementation approaches, expanded use of renewable energy and close collaboration with local government. A workshop on achieving universal electricity in Indonesia was conducted at the Doubletree Hotel in Jakarta on 19 March 2015. The objective of this seminar was to present the ongoing activities of key government stakeholders and share different perspectives on Indonesia's electrification challenge. The workshop also focused on identifying how to achieve the government’s goals through planning and implementing large-scale electrification programs in Indonesia. The seminar was hosted by the Directorate General of New and Renewable Energy Resources (DG-EBTKE), Ministry of Energy and Mineral Resources (MEMR) and supported by Asian Development Bank (ADB). Participants included officials from Indonesia’s Ministry of Finance (MOF), Ministry of Energy and Mineral Resources (MEMR), the State Ministry of National Development Planning (BAPPENAS), Coordinating Ministry for Economic Affairs (CMEA), and State-Owned Enterprises including PT PLN, as well as representatives of the ADB and the World Bank. The workshop agenda is provided in Chapter 2 and list of invitees as well as attendance list is provided in Chapter 3. The speakers focused on the key financial, infrastructural, and institutional problems that constrain the expansion of electricity access in Indonesia. The workshop was opened by the Director General, EBTKE. Presentations were delivered by representatives from the Directorate General, EBTKE, MEMR; the Directorate General, Electricity, MEMR; BAPPENAS; the World Bank; and the ADB.

1-1 Workshop on Electricity Access

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2.

AGENDA

Date Venue

: 19 March 2015 : Double Tree hotel

Time

Description

Speaker

08.00 – 09.00

Registrasi

09:00 - 09: 15

Pembukaan oleh Dirjen EBTKE

Direktur Jenderal EBTKE, KESDM

09.15 – 09.35

Review Target dan Pencapaian Rasio Eletrifikasi Indonesia hingga tahun 2014

Direktur Jenderal Ketenagalistrikan, KESDM

09.35 – 09.55

Keberhasilan dan Tantangan Program Listrik Perdesaan di Indonesia oleh PLN

Direktur Utama PT PLN (Persero)

09.55 – 10.15

Kebijakan Pendanaan dan Subsidi Kelistrikan di Indonesia

Kepala Badan Kebijakan Fiskal

10.15 – 10.35

Efektivitas Perencanaan antara Instansi pada Program Kelistrikan di Indonesia

Deputi Bidang Sarana dan Prasarana, BAPPENAS

10. 35 – 10.50

Rehat

10.50 – 11.05

Pembelajaran Peningkatan Akses Energi Listrik pada Program Sumba Iconic Island

ADB

11.05 – 11.20

Review Program Bantuan Teknis Program Eletrifikasi di Indonesia

World Bank

11.20 – 12.00

Diskusi dan Tanya Jawab

Fasilitator/Moderator

12.00 – 13.00

Makan siang dan Istirahat

13.00 – 14.15

Diskusi Kelompok I

Fasilitator

14.15 – 14.30

Break

Fasilitator

14.30 -15.45

Diskusi Kelompok II

Fasilitator

15.45 – 16.30

Ringkasan Hasil Diskusi Kelompok

Fasilitator

Rencana Aksi dan Jadwal Kegiatan selanjutnya


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3.

LIST OF INVITEES AND ATTENDANCE LIST

List of Invitee 1. Direktur Jenderal Ketenagalistrikan, Kementerian ESDM 2. Deputi Bidang Koordinasi lnfrastruktur, Kementerian Koordinator Bidang Kemaritiman 3. Deputi Ill Bidang Koordinasi Energi dan Sumber Daya Mineral, Koordinator Bidang Perekonomian

Kementerian

4. Direktur Energi, Telekomunikasi dan lnformatika, Deputi Bidang Sarana dan Prasarana, BAPPENAS 5. Direktur Perencanaan Pembangunan Daerah, Ditjen Bina Pembangunan Daerah, Kementerian Dalam Negeri 6. Direktur Pendayagunaan Pulau-Pulau Kecil, Direktorat Jenderal Kelautan, Pesisir dan Pulau-Pulau Kecil, Kementerian Kelautan dan Perikanan 7. Direktur Pembinaan Program Ketenagalistrikan, Direktorat Jenderal Ketenagalistrikan, Kementerian ESDM 8. Asisten Deputi Urusan lnfrastruktur Energi, Deputi Bidang Peningkatan lnfrastruktur, Kementerian Desa, Pembangunan Daerah Tertinggal dan Transmigrasi 9. Kepala Pusat Kebijakan Pembiayaan Perubahan lklim dan Multilateral, Kebijakan Fiskal

Sadan

10. Kepala Pusat Penelitian dan Pengembangan Teknologi Ketenagalistrikan, Energi Baru, Terbarukan dan Konservasi Energi, Kementerian ESDM 11. Direktur Konstruksi dan Energi Baru Terbarukan, PT PLN (Persero) 12. ADB 13. Bank Dunia


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3. List of Invitees and Attendance List Attendance List No. Name

Title/Company

1 Rida Mulyana

Direktur Jenderal EBTKE

2 Dadan Kusdiana

Direktur Bionergi

3 Wanhar

Kasubdit Progres DJK

4 Puguh Imanto

World Bank

5 Edimor Gu..

ADB

6 Hartono

Dit Bio energi

7 Anna Rufuida

DJEBTKE

8 Noor Khayati

DJK

9 Agus Saptono

DJEBTKE

10 Sandra W

HIVOS

11 Tody Ferdica

DJEBTKE

12 Adolf Leopold Sihombing P3TKEBTKE ‐ KESDM 13 Cecep S

EBTKE

14 Alihuddin

DJEBTKE

15 Fabby Tumiwa

IESR

16 Heru SS

PLN

17 Dimas

PLN

18 Gery Baldi

PSTKEBTKE

19 Iis Hernaningsih

Dit Jen Perencanaan

20 Berkana

ADB

21 Siswa Trihadi

KPDT Desa

22 Jadhie J A

Bappenas

23 Syaiful NST

P3TKEBTKE ‐ KESDM

24 Agus Wibowo

Menko Ekon

25 Abinanto

Castlerock

26 Iryan Permana D

EBTKE

27 Maura Lilis

Adb (Cons)

28 Penny Rahim… 29 Anggifa A.

BKF ‐ Kemenkeu

30 Agus Tri Wandoyo

DAK ‐ DEA

31 Setiadi Indra DN

Kemenko Ekon‐Listrik


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4.

SUMMARY OF PRESENTATIONS & DISCUSSIONS

1. Pidato Dirjen EBTKE Target rasio elektrifikasi Indonesia 100% pada tahun 2019, namun 10-15% terakhir adalah wilayah yang tersulit (off grid) Elektrifikasi pada wilayah off grid memerlukan biaya yang mahal sehingga memerlukan koordinasi, partisipasi dan investasi dari berbagai pemangku kepentingan. Keterlibatan PLN sebagai BUMN yang diberikan mandate untuk melayani listrik sangat penting dan strategis. Pembelajaran pada program Sumba Iconic island memerlukan tindaklanjut dari berbagai instansi terkait, terutama pada sisi kebijakan usaha, tariff dan subsidi listrik pada lokasi off grid, serta partisipasi dari investasi swasta. 2. Paparan DJK Kondisi kelistrikan pada tahun 2014: kapsitas pembangkit 53.5 MW, Konsumsi 199 TWh, Produksi 228 TWh, dan rasio elektrifikasi 84.35% Traget rasio elektrifikasi nasional pada tahun 2019 menurut RUKN adalah 97.35% dan akan mencapai 99.35% pada tahun 2020. Jumlah sambungan baru rata-rata 2.47 juta per tahun Tingkat pertumbuhan konsumsi listrik Indonesia adalah 8% pertahun. Kebutuhan penambahan daya listrik yang diperlukan 10.000 MW per tahun Penambahan jaringan distribusi yang diperlukan hingga tahun 2019 adalah 30.000 kms Anggaran penyediaan listrik perdesaan tahun 2015 (APBN-P) Rp. 5.237 T, terdiri dari DJK Rp. 201 M, UIP-APBN Rp 1.172 T, dan Lisdes Rp. 3.863 T. 3. Paparan Bappenas Kedaulatan Pangan dan Energi terbasuk dimensi pembangunan prioritas pada RPJMN 2015-2019 Sasaran rasio elektrifikasi minimal 96.6% tercapai pada tahun 2019 Pemerintah akan membangun pembangkit listrik 35.000 MW pada tahun 20152019, 10.000 MW oleh PLN dan 25.000 MW oleh Swasta (IPP). Investasi yang diperlukan untuk pembangunan pembangkit diperkirakan Rp.608 Trilyun oleh PLN dan Rp.580 Trilyun oleh pihak swasta Kebutuhan pasokan listrik tambahan tsb sangat diperlukan bagi pembangunan infrastruktur pada tahun 2015-2019, antara lain: Jalan Tol dan Jalan arteri baru, Jalur Kereta Api, Pelabuhan untuk Tol Laut, Bandara baru, waduk dan irigasi untuk kedaulatan pangan. Sangat diperlukan koordinasi antar instansi pemerintah dan partisipasi swasta dalam pelaksanaan pembangunan infrastruktur prioritas tersebut, termasuk ketenagalistrikan. 4. Sesi Diskusi & Tanya Jawab Kemenko Perekonomian: Program kelistrikan yang sudah ada dan sudah berjalan baik harus tetap dilanjutkan, sedangkan yang belum berjalan dengan baik perlu diperbaiki, baik aspek regulasi maupun sinergi dan kooordinasi antar pemangku kepentingan.


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4. Summary of Presentations & Discussions Kemenkeu: Bappenas dan kemenkeu berperan penting dalam program pembangunan, termasuk bidang energy. Mulai dari proses perencanaan sistem hingga skema pengelolaan dan subsidi. Channeling pendanaan termasuk subsidi baik sifat off grid dan on grid dengan PT. PLN menjadi sangat penting. Semua kebijakan pendanaan adalah keputusan pada kemenkeu. Untuk channeling off grid subsidi opex masih memungkinkan, namun untuk on grid belum memungkinkan karena ada UU otonomi daerah yang baru. Anggaran di kementrian lewat proses DIPA kategorinya PSO selama ini penyerapannya rendah sehingga sedang dipertimbangkan untuk memberikan penyertaan modal kepada PT PLN. DAK untuk membangun listrik pedesaan, selama ini aturannya fisik padahal skemanya sangat fleksibel (bisa fisik dan non fisik). Konsep seperti ini harusnya masuk di DAK, karena hal ini merupakan channeling pelimpahan kewenangan. Hal ini perlu dikawal oleh kementerian ESDM. Bappenas: UU ketenagalistrikan menugaskan PLN untuk menyediakan listrik di Indonesia, sehingga PLN punya kewenangan sekaligus kewajiban. Dengan UU ini, PLN wajib melistriki seluruh wilayah Indonesia. PLN bisa melaksanakan program tersebut baik dengan dana dari Pemerintah maupun non Pemerintah, yang terpenting memenuhi sasaran rasio elektrifikasi 96,6% pada tahun 2019. Apapun skemanya, on/off grid/PPP PLN harus membangun listrik (meningkatkan rasio elektrifikasi Nasional), bisa dengan mempertimbangkan least cost analysis system, baik capex ataupun opex. Namun demikian tidak bisa hanya berpedoman kepada RUPTL saja. Kalau hanya berdasarkan least cost saja maka Pembangkit yang dibangun hanya PLTU saja karena paling murah, namun harus dipertimbangkan juga bahwa bahan bakar fosil akan habis suatu saat. Selama ini PLN ingin mebangun dalam bentuk proyek atau subsidi langsung besar dari pemerintah. Seharusnya PLN dapat mencari modal sendiri untuk membangun infrastruktur dan pemerintah akan menutup sisa kebutuhan pendanaan opex selama kewajiban PLN untuk memenuhi kebutuhan listrik masyarakat terpenuhi. DJK: DJK menyambut baik ide/pendapat dari Bappenas. Dengan mempertimbangkan situasi kondisi saat ini, sebetulnya pada tahun 2016 PLN sudah tidak memerlukan APBN untuk program UIP dan Lisdes. Harus dipastikan bahwa PLN serius menangani program ini karena berdasarkan UU PLN memang berkewajiban. Pertimbangan penggunaan APBN pada program Lisdes adalah mudahnya pengawasan. Ditengarai jika tidak ada dukungan APBN, maka kegiatan pengawasan akan cenderung lebih lemah. Selama ini sering terjadi kesalahpahaman antara PLN dengan DJK terkait program Lisdes melalui APBN. Kemen Koperasi dan UKM: Selama ini prosedur penyerahan capex kepada PLN rumit dan sulit. Diperlukan kebijakan atau aturan yang lebih jelas dan mudah untuk diimplementasikan di lapangan. PLN: Pada RUPTL tetap ditulis bahwa untuk program Lisdes sumber pendanaan dari APBN dan APBD. Untuk APBD sudah banyak KSO, contohnya Pemda memberikan diesel kepada desa dan kemudian PLN yang melaksanakan operasi dan pemeliharaan. Program Lisdes saat ini lebih banyak untuk membangun jaringan dan distribusi listrik, dan hanya sedikit saja untuk membangun pembangkit. Jika pembangunan EBT merupakan salah satu kunci pembangunan jangka panjang maka APBN sebaiknya mendukung pembangunan pembangkit listrik sumber EBT. Berdasarkan penugasan PLN dari presiden bahwa PLN harus melistriki daerah perbatasan dalam 1 tahun, sehingga PLN dibolehkan membeli diesel tapi dengan sistem hybrid dengan energy terbarukan untuk kebutuhan ini.


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4. Summary of Presentations & Discussions 5. Rekomendasi Breakout Session Kebijakan dan Implementasi: Perencanaan ketenagalistrikan on-grid dan off-grid sudah digariskan di RUKN dan RUKD yang disusun berdasarkan RUPTL. Identifikasi off-grid yang sulit dilistriki PLN sudah diidentifikasi. PLN ditugaskan untuk tetap melistriki daerah yang belum berlistrik. Isu di kebijakan dan perencanaan kelistrikan: Prioritas politik pemerintah daerah Perubahan insfrastruktur akses jalan baru, jaringan listrik baru Pembangkit, gardu induk dan transmisi masuk RUPTL, distribusi lebih fleksibel (kadang ad hoc) Untuk service standards: disesuaikan di masing masing daerah, tidak bisak dseragamkan untuk R-1 450 VA Untuk kewenangan kelistrikan baik off-grid dan on-grid, sesuai dengan UU 30/2009: Pemerintah pusat dan pemerintah daerah bertanggung jawab menyelenggarakan pendyediaan listrik Pelaksanaan penyediaan listrik dilakukan oleh PLN Pemerintah daerah masih belum sadar apa yang harus mereka lakukan EBTKE tetap mempunyai wewenang kuat untuk off-grid, tetapi tanggung jawab Pemda harus ditingkatkan untuk memastikan anggaran APBD yang cukup untuk O&M dan dapat diproses dengan tepat waktu. Listrik tidak bisa gratis untuk masyarakat, tetapi harus dicari jalan bagaimana mendapatkan subsidi untuk O&M. Peraturan ESDM no 10/2012 mengenai pelaksanaan kegiatan fisik energi terbarukan, pada saat serah terima asset disebutkan bahwa Pemda sanggup menerima dan mengelola fasilitas fisik (contoh: PLTMH, PLTS) Untuk program Listrik Desa institusi yang sudah ada seperti DEN seharusnya dioptimalkan untuk perencanaan ketenagalistrikan, tidak perlu membentuk suatu institusi baru. Institusi yang sudah ada perlu diberdayakan dan dioptimalkan peran sertanya di dalam perencanaan dan implementasi ketenagalistrikan. Investasi dan Subsidi Adanya resiko bagi PLN atau pihak lain bahwa regulasi yang ada belum dapat mengakomodir semua mekanisme perpindahan aset dan kepemilikannya sehingga meimbulkan kekhawatiran. Subsidi tidak perlu diberikan ke PLN namun bisa dibuat di dalam DAK di bawah Kementrian yang berwenang, misalnya KESDM. Target LISDES dibagun berdasarkan RUKN dan RUPTL yang tentunya berkorelasi dengan dana yang ada di dalam APBN. Pada saat ini ada pembagian yang cukup jelas, bahwa untuk “off grid” akan dikerjakan oleh EBTKE dan “on grid” adalah DJK Tariff dibangun rekomendasi dengan dasar TDL (tarif dasar listrik) untuk wilayah tertentu dalam pembangunan listrik desa, dengan diberikan harga yang sama maka LISDES juga merupakan bagian nasional subsidi Mekanisme pemberian Subsidi dalam diskusi masih tetap menggunakan format yang telah ada yaitu kepada PLN dan DAK di kementrian yang berwenang. 4-3 Workshop on Electricity Access

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4. Summary of Presentations & Discussions Monitoring dan evaluasi mengacu kepada UU 23/2014, dimana propinsi menjadi perpanjangan tangan dari Pemerintah Pusat dan perwakilan pemerintah pusat. Langkah selanjutnya ; perlu membuat “Keppres” yang dikordinasikan oleh Kementrian Koordinator Ekonomi. Keppres ini akan fokus didalam “Pembangunan Listrik Desa” di seluruh wilayah. Dasar pembuatan keppres ini adalah RUKN (rencana umum ketenagalistrikan nasional). KESDM bisa menjadi penggagas ide ini. Transfer asset melalui DAK bisa diberikan kepada propinsi, baru diserahkan kepada wilayah atau kabupaten yang berkepentingan.


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5.

NEXT STEPS

Next steps resulting from the workshop: A new, two-pronged framework for rural electrification is needed: o

Improved planning, financing and implementation of publicly financed gridextension projects implemented by PLN

o

A new framework for private sector participation for electrification of offgrid areas (non-PLN areas)

A high-level discussion of these issues and possible solutions can be considered for inclusion in the 2015 RUKN An inter-ministerial working group should be established to consider how this new framework can be developed In the near-term, the working group should produce an action plan to define the policies, regulations and activities required to implement this new framework.


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APPENDIX A: ACHIEVING UNIVERSAL ELECTRICITY ACCESS

A-1 Workshop on Electricity Access

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Achieving universal electricity access in Indonesia Jakarta 13 April 2015

Current situation • Indonesia has made remarkable progress in electrification – 84% electrification ratio as at end 2014 – PLN adding some 3.7 million customers per year (2013)

• However, Indonesia faces new & different challenges – Population growth of 1.4% p.a. ~900,000 new households p.a. – Some 40 million people remain without electricity – As in other countries, the last 10 to 15% of the population is the most costly and difficult to serve The rate of electrification often decreases significantly for the last 10 to 15% of the population due to the cost and difficulty of serving these households

2

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1

Barriers to universal access • KEN target: “approach 100% by 2020” • PLN challenges – Under pressure to reduce subsidy (PSO) but remote households typically most costly to serve – Off‐grid service will become increasingly important • Sumba indicates off‐grid solutions least‐cost for 1/3 of remaining households • PLN not organizationally set up for off‐grid development • PLN faces many competing investment needs

• Government challenges – Fragmentation: LisDes, DAK, other line ministry programs • No comprehensive least‐cost plan • 2015 LisDes: Rp 2.6 t; DAK: Rp 0.7 t; EBTKE & others: Rp 0.7 t

– Many off‐grid projects fail – focus to date on projects, not sustainability – 2015 target connections: LisDes 209,000 & Listrik Hemat 93,000 3

A new framework for electrification? Electrification Policy

PLN (grid) • • •

Funding adequacy Designation of grid vs. off‐grid areas Subsidy funding options – – – –

•

Designation of off‐grid (non‐PLN) business areas by DJK for “micro IPPs”

LisDes – cumbersome Equity – uncertainty for future years & not results‐based “PSO+” – fund electrification like PSO. Considered investment? “Designated account” – similar to SLA process

Supervision

• • • •

Service standards – R1 450 VA? Tariffs – TDL? Role of renewables Participation modality – –

•

Tender for business area concessions e.g. 10 years? Build‐operate?

Subsidy funding options – –

• •

Private (off‐grid)

Capital subsidy from DAK? Operational subsidy from ???

Legal basis – revision to PP 14/2010? Implementation & supervision

4

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Immediate next steps? • Establish inter‐ministerial working group – – – – – – – – –

Role of PLN & others Planning Tariff levels Service standards Business modalities Role of renewables Funding Supervision Legal basis

From The Jakarta Globe, “A Bright Future for the Village Where the Lights Don’t Go Out”, 10 April 2015…..

• Develop Electrification Action Plan • Define principles in RUKN • Establish Electrification Policy 5

ADB consultants …available to support Government • Sustainable & Inclusive TA team – – – – – – –

Mike Crosetti William Derbyshire David Braithwaite Bruce Smith Tatiana Tumenggung Andre Susanto Miranti Aisyah

• Other experts – Donald Hertzmark

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APPENDIX B: ELECTRICITY ACCESS - LESSONS FROM SII

B-1 Workshop on Electricity Access

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Lessons Learned from the Sumba Iconic Island Program Lokakarya Peningatan Akses Energi Listrik Perdesaan Berbasis Energi Terbarukan di Indonesia Jakarta 19 March 2015

www.castlerockasia.com

The Sumba Iconic Island (SII) Initiative Current Situation • ~30% electrification • ~15% renewable power supply

2025 Targets • 95% electrification • 100% renewable power supply

• A multi‐stakeholder initiative established in 2010 by ESDM & Hivos – – – –

Pilot projects Planning Policy & regulatory support Promotion & coordination

• Led by EBTKE with participation by – – – – – –

Other ministries Pemda (province and kabupaten) PLN Hivos and other NGOs Private sector Development partners

• ADB support since 2013

2

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Experience in Sumba shows the need for a new approach to electrification • ADB support for the Sumba Iconic Island has included: – A feasible, least‐cost plan to determine investment needs • Grid vs. off‐grid • Expansion of grid‐connected generation • Network development

– This indicated a need for sustainable off‐grid supply – …leading to the design of PV mini‐grid pilot programs – …that could not proceed due to regulatory barriers.

• Findings of the ADB work: – Tools are available to support least‐cost electrification planning – Indonesia requires a new framework for electrification if it is to achieve universal access

3

Electrification Targets

The planning methodology http://castlerockasia.com/sumba/sii.html

Grid vs. off‐ grid analysis

Off‐grid investment opportunities

Private sector investment PLN investment

Geospatial planning tools: Network Planner

Grid least‐cost generation expansion plan

On‐grid investment opportunities

Generation planning tools: Homer Load flow & transmission plan

Network planning tools: ETAP

Network infrastructure investment

Network operating requirements 4

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Current situation (~30% electrification) Settlements & Buildings with Existing 20 kV Network

Existing 20 kV network

5

Situation in 2025 (95% electrification) – Base Case Number of households in Sales in 2025, 2025 GWh grid 129,130 285.9 mini‐grid 4,162 2.1 off‐grid 33,396 9.9 Total 166,688 297.9

Existing 20 kV grid Future 20 kV grid Grid connected settlements Future PV mini‐grids Individual household PV systems not shown 6

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Situation in 2025 (95% electrification) – Low Case Number of households in Sales in 2025, 2025 GWh grid 138,670 290.0 mini‐grid 17,208 6.5 off‐grid 10,810 1.4 Total 166,688 297.9

Existing 20 kV grid Future 20 kV grid Grid connected settlements Future PV mini‐grids Individual household PV systems not shown 7

Mini‐grid & off‐grid investment Base Case

Low Case

‐ capital cost (USD)

6.6 million

21.2 million

‐ number of households

4,162 (3%)

17,208 (10%)

1,597

1,234

‐ capital cost (USD)

43.1 million

6.2 million

‐ number of households

33,396 (20%)

10,810 (7%)

1,290

574

129,130 (77%)

138,670 (83%)

285.9

290.0

166,688 (100%)

166,688 (100%)

Mini‐Grids

‐ capex / household (USD) Off‐Grid

‐ capex / household (USD) Grid ‐ number of households ‐ Total annual grid sales (GWh) Total number of electrified households in 2025

8

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Total investment summary Not cheap… But cheaper than the alternative Off-grid & Mini-grid* Grid - Generation** - Network - Other*** TOTAL Total per household

71% Renewable 49.7

87% Renewable 49.7

215.9 171.9 12.9 450.4 2,702

434.9 171.9 19.5 676.0 4,055

Values are overnight capital costs stated in million USD, except for “total per household”, which is expressed in USD. * Base Case assumed. ** Net of existing generation *** “Other” represents an estimate of the costs of a control system and other studies and implementation activities. Assumed to be 3% of all grid capex. 9

Grid vs. Off‐Grid Findings • Grid extension – Least‐cost means of electrification for ~80% of households – This drives a nearly six‐fold increase in grid load by 2025 – Generation expansion planning & investment is therefore critical

• Mini‐grid & off‐grid solutions – Least cost means of electrification for ~20% of households – …which represent nearly 1/3 of remaining households to be electrified

Off‐grid & mini‐grid solutions will be important to achieve univesal access

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Developing a model for sustainable mini‐grids • Many off‐grid projects fail – – – – –

Inadequate understanding of community needs Poor design and workmanship Lack of post‐commissioning technical support No mechanism to ensure funding for O&M Customer payment obligations higher than willingness‐to‐pay (WTP)

• A sustainable solution will be characterized by the following: – – – –

Prior community engagement and load surveys Rigorous specifications, supervision and payment terms Provision of post‐commissioning technical support Secure funding for O&M • Customer payment discipline, aligned with WTP • Operational subsidies where required

11

Model 1: PLN Operation & Maintenance • PLN is the only public institution capable of sustaining a solution – – – –

Qualified manpower throughout the country Proven billing & collection systems that impose payment discipline An institutionalized operational subsidy mechanism An established regulatory framework (licensing, pricing)

• ADB’s first model attempted to build on PLN’s strengths – Asset would remain property of pemda due to difficulty of transferring assets to PLN.

• ….but could not move forward – Initially relied on Permen 4/2012 which obliges PLN to purchase power at feed‐in tariff, but informed it was no longer valid for PV (even off‐ grid) – Then proposed PLN KSO with pemda, but PLN was reluctant to take on O&M responsibility for third‐party assets. 12

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Model 2: Private sector build‐operate • Private sector strengths – – – – –

Able to provide qualified manpower under the right conditions Billing & collection systems available Model used elsewhere Pemda could still retain the asset Build‐operate model aligns interest for proper design, construction, O&M

• Regulatory barriers – License issued by provincial government based on DJK business area – Tariffs must be approved on a project‐by‐project basis by Provincial DPRD – No secure provision for operational subsidies • If tariffs set to fully cover O&M, then much higher than TDL and perhaps WTP • The poorest households will be paying the highest tariffs

13

1

ADB

Transfers the asset

2

ESDM

Transfers the asset

3

Pemda

Transfers the asset

4

Model 2 Details Procures Builder‐Operator for construction

Owner

Sets business area Issues license

Builder‐ 5 4. The Owner receives the Asset and an annual fee from the Pemda for expenses and system expansion. The operator

Owns & expands

“The Asset” PV System, Operates & maintains the PV system Batteries, Operates & maintains the Inverters network & metering

Customers

2. ESDM determines the business area and transfers the Asset to the Pemda. 3. Pemda then transfers the Asset to a cooperative or regional government‐owned company to serve as Owner. The Pemda also issues an electricity license to the Builder‐Operator (B‐O).

Pays annual subsidy/fee Joint Operating Agreement 6

1. ADB procures the Builder‐Operator, which constructs the Asset and installs consumer wiring. Upon commissioning ADB transfers the Asset & warranties to ESDM and consumer wiring to consumers.

7 Pays for electricity at tariff approved by Pemda

Owner is responsible to add system capacity if it is additional capacity is needed in the future. 5. The B‐O operates and maintains the Asset, which includes the PV arrays, batteries, inverters, distribution network, and meters. B‐O is also responsible to honor warranties. 6. The B‐O operates & maintains the Asset under a joint operating agreement (kerjasama operasi, KSO) with the Owner. The Owner contributes the Asset. 7. The customers will be B‐O customers using prepayment meters, and will pay for electricity at a tariff to be approved by the Pemda per PP 14/2012. This requires approval of the DPRD. 14

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Review of the Current Situation • Indonesia has achieved 84% electrification access. • However, existing mechanisms are poorly suited to provide access for the remaining 16% The GoI spends signficant amounts for electrification, but there has been no nation‐wide analysis of the costs required to serve the remaining 16% of households that do not yet have electricity

It is unknown whether current levels of expenditure are adequate to reach the target

• •

KEN target of 100% access by 2020 Analysis for eastern Indonesia indicates that off‐grid solutions would be least‐cost for up to 1/3 of remaining households

Off‐grid solutions will be an important part of achieving universal access at least‐cost.

• •

Household willingness‐to‐pay in remote areas is low Off‐grid supply can cost > Rp 20,000/kWh

Capital and operational subsidies are required

GoI spends more than Rp 1 trillion annually for electrification activities which have not been planned on a least‐cost basis and are outside of PLN‐executed programs

A single, comprehensive plan is required to ensure efficiency & effectiveness of all electrification expenditure

• • • •

Many off‐grid projects fail. Other than PLN, there is no public institution with the capacity to sustain off‐grid solutions. PLN is financially constrained for new capex & organizational structure not conducive to off‐grid work Regulations governing private sector involvement are ad hoc & cumbersome

A new regulatory regime is needed to mobilize private sector initiative for off‐grid supply. 15

Key issues • Targets • Planning – “Many Partners, One Team, One Plan” • Funding – Capital subsidies – Operational subsidies

• Who will implement? – On‐grid: PLN – Off‐Grid: ???

• Supporting regulations Under Law 23/2014….. There is currently no legal basis for off‐grid supply in the absence of : • Definition of business area by DJK • Provision of license by Pemda Provinsi • Approval of tariff on project‐by‐project basis by DPRD Provinsi 16

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Resource availability • Used HOMER to determine least‐cost mix

Maximum available MW

No pumped storage

With pumped storage

PV

10

30

• Resource availability based on Deliverable B report

Wind

10

20

Biomass

10

10

• Maximum available capacity of each generation type

RoR Hydro

6.8

6.8

Storage Hydro

10 / 20

10

• Cost and hourly performance

Pumped Storage

0

18

Diesel

60

60

• Future load from geospatial analysis

18

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Least‐cost generation analysis • 2025 grid peak demand 52 MW, 286 GWh annual consumption • Maximum available capacity for each technology based on: – Maximum grid penetration: PV, wind – Resource availability: biomass, run‐of‐river hydro, storage hydro – Unconstrained: diesel

• Least‐cost mix achieves 71% reliance on renewables • Seasonal hydrology and wind availability forces continued use of diesel

19

Pumped storage can increase renewable penetration • HOMER indicates pumped storage could increase penetration to 87% • Actual penetration could be higher through optimal operational planning

20

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Transmission infrastructure requirements • Transmission needs determined from 2025 load flows using ETAP – Reduced system representation – Scenarios reflecting variability in resources

• 150 kV transmission backbone required

150 kV network 20 kV network Lumped loads 150/20 kV substation Generating station 21

On‐grid generation investment Pump Storage Case – 10 MW Storage Hydro Capacity Production Capital Cost Capacity Production Capital Cost Capacity Production Capital Cost (MW) Share (million USD) (MW) Share (million USD) (MW) Share (million USD) Base Case – 20 MW Storage Hydro

PV Wind Hydro (ROR) Hydro (Storage) Pumped Storage Biomass Diesel TOTAL less existing RoR hydro** less existing diesel*** TOTAL excl. Existing

10.0 10.0 6.8 20.0 ‐ 10.0 60.0 116.8 2.3 10.7 103.8

6% 8% 37% ‐ 20% 29% 100%

30.0 33.0 20.6 80.0 ‐ 45.0 60.0 268.6 7.0 10.7 250.9

Base Case – 10 MW Storage Hydro

10.0 10.0 6.8 10.0 ‐ 10.0 60.0 106.8 2.3 10.7 93.8

6% 8% 37% ‐ 20% 29% 100%

30.0 33.0 20.6 45.0 ‐ 45.0 60.0 233.6 7.0 10.7 215.9

30.0 20.0 6.8 10.0 18.0 10.0 60.0 154.8 2.3 10.7 141.8

16% 15% 36% 8% 20% 13% 108%*

90.0 66.0 20.6 45.0 126.0 45.0 60.0 452.6 7.0 10.7 434.9

USD 0.357/kWh USD 0.279/kWh USD 0.276/kWh Levelized Cost of Energy**** Notes: * Percentage of consumer load. Sums to >100% because of production required to operate pumped storage as well as meet load. ** Based on PLN data for Lokomboro A&B (derated), April 2013 *** Based on PLN data for all diesel sets >350 kW and derated, April 2013 **** Total system generation levelized costs at the busbar, including existing plant. Network costs are excluded.

22

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Transmission investment Total Capex (USD million) 150 kV lines 23.7 150 kV substations 19.8 New 20 kV lines 48.0 New 20/0.4 kV transformers 15.3 20 kV line regulators 0.3 20 kV field circuit breakers 0.6 LV Line 48.2 Customer connections 16.0

TOTAL

171.9

23

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APPENDIX C: ELECTRICITY ACCESS - BREAK-OUT GROUPS

C-1 Workshop on Electricity Access

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Lokakarya Peningkatan Akses Energy Listrik Perdesaan Berbasis EBT Diskusi Kelompok Jakarta 19 March 2015

Format of the Break‐Out Groups • Two groups established: – Electrification Planning & Implementation – Electrification Financing & Subsidies

• Join the group that is most relevant to your job • Objective is for each group to: – Identify key issues – Propose possible solutions – debate the options! – Recommend next steps

• • • •

No fixed agenda, but sample topics and options provided Each group to appoint its own chairman and rapporteur Chairmain & rapporteur will report feedback to the workshop Timing – 1.5 hours (including coffee break) to discuss & prepare presentation – Up to 0.5 hours for each group presentation and feedback 2

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Break‐out Group 1: Planning & Implementation Sample Topics (1) Sample Topic

Sample Option 1

1. Electrification Government electrification policy technology refers only to grid extension.

Sample Option 2 Government electrification policy encompasses both grid extension & off‐grid supply.

2. Electrification All households receive a minimum Service standards depend on the service of R‐1 450 VA service (24/7) cost of serving an area. For standards example, in the highest cost areas, households receive 3 lights for 5 hours/night at 95% reliability. 3. Planning

PLN should determine the least‐ cost means to electrify the entire country, grid & off‐grid – even if PLN is not responsible to implement off‐grid electrification.

4. Business area Based on planning results, areas designation where off‐grid supply is least‐cost should be identified and designated as non‐PLN business areas.

A new or existing government agency (national or pemda?) should plan electrification nationally, incorporating PLN’s own plan & also planning for non‐PLN/off‐grid areas. Rural electrification business areas should not be carved out for non‐ PLN supply. Non‐PLN supply should be allowed only for industrial estates. 3

Break‐out Group 1: Planning & Implementation Sample Topics (2) Sample Topic

Sample Option 1

Sample Option 2

5. Implementation The Government should assign Responsibility PLN for all electrification in Indonesia (on‐ and off‐grid) <> Pemda Provinsi should be responsible for off‐grid supply.

Non‐PLN/off‐grid business areas should be tendered to the private sector <> A new national agency or BUMN should be established for off‐grid

6. Role of Renewables

There should be no restriction on the types of power generation used in off‐grid areas, provided it is least‐cost & reliable

Supply to off‐grid areas should be based entirely on renewables, possibly with use of diesel only for back‐up supply.

7. Legal Basis

Existing regulations are sufficient

New regulations are required (Specify)

8. Next Steps

Menko, ESDM, Bappenas, MoF, MoHA etc to formally establish inter‐ministerial working group to establish electrification policy & processes. ADB to support.

Each agency continues to develop it’s own apporach, with future ad hoc meetings like this to coordinate. 4

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Break‐out Group 2: Financing & Subsidy Sample Topics (1) Sample Topic

Sample Option 1

Sample Option 2

1. Need for Subsidy

The Government (and pemda?) The total level of subsidy provided must rigorously target subsidies, for electrification must decrease, but be prepared to provide higher regardless of the impact on access. subsidies per household for eligible households, regardless of impact on total subsidy level

2. Electrification Targets

Electrification targets should be set according to available funding.

100% access by 2020 is “non‐ negotiable”. The Government must provide the funding required.

3. Consumer Pricing

All households in Indonesia pay TDL (except Batam & Tarakan)

Tariffs in high‐cost areas should be set higher than TDL. (But then do the poorest households pay the highest tariffs?)

4. Value for Money

Government should provide capital subsidy for off‐grid supply, then tender to private sector based on lowest operational subsidy requirement.

Off‐grid supply should be responsibility of PLN or Pemda. Government will define standards for electrification, then require them to tender for contractors.

5

Break‐out Group 2: Financing & Subsidy Sample Topics (2) Sample Topic 5. Non‐PLN Subsidy Mechanism

Sample Option 1

Sample Option 2

Via PLN. PLN will enter into KSO with off‐grid suppliers, and will pay them an operational subsidy ultimated funded via PLN PSO

Via new mechanism funded by DAK. Government will establish a Badan Layanan Umum (BLU) to receive DAK funds in year project commissions, and disburse subsidy over concession period

6. Monitoring & Strict M&E must be established, and M&E is needed, but only for Evaluation payments tied to results achieved helping to refine the program. 7. Legal Basis

Existing regulations are sufficient

New regulations are required (Specify)

8. Next Steps

Menko, ESDM or Bappenas to formally establish inter‐ministerial working group to establish electrification policy & processes <> Explore international funding sources, like Green Climate Fund

Each agency continues to develop it’s own apporach, with future ad hoc meetings like this to coordinate.

6

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Existing LisDes process Bappenas

KESDM DJK

KemKeu DJA

KemKeu DJP

Prepare Rencana Umum Ketenagalistrikan Nasional (RUKN)

PLN Pusat

Electrification targets

Prepare (1) Road Map LisDes, and (2) inputs to Rencana Usaha Penyediaan Tenaga Listrik (RUPTL)

Provide inputs for electrification targets

Compile Road Map LisDes and finalize RUPTL

Determine funding sources for investment

via RKP Provide indicative budget ceiling

Reviews conformity of RKA-KL with RKP

Pemda & Instansi Lain (e.g. MenHut)

Provide planning guidance to Wilayah

Electrification targets Prepare Recana Pembangunan Jangka Menengah Nasional (RPJM-N)

PLN Wilayah & Business Units

Prepare budget request for Program Listrik Perdesaan (LisDes) and Proyek Induk Pembangkit & Jaringan (UIP-APBN) as part of Rencana Kerja & Anggaran Kementrian/ Lembaga (RKA-KL)

Discuss electrification needs with DJK Discuss and finalize Anggaran Pendapatan & Belanja Negara (APBN) for approval by Dewan Perwakilan Rakyat (DPR)

After approval of APBN by DPR and work approval by P2K, pay contractor for LisDes and UIP-APBN

Manage funds for UIP-APLN Conduct procurement & manage UIP-APLN

Appoint Pejabat Pembuat Komitmen (P2K) from PLN for LisDes & UIP-APBN Construct & commission UIP-APBN & LisDes projects

Transfer completed LisDes and UIP-APBN projects to PLN as government equity

Issue licenses & permits

Construct & commission UIP-APLN projects

Own assets Operate & maintain assets

Monitor & report against elect. targets

8

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4

Possible process for private sector engagement MEMR / DGE (budget through DGB)

PLN Wilayah

Establish Satker Lisdes

Satker Lisdes

Pemda (Province)

Operational Satker Lisdes

Second personnel to Satker Lisdes

Private Developer

Preparation

Second personnel to Satker Lisdes Establishes electrification standards in Electrification Policy

Strengthens planning skills, e.g. geospatial planning

Prepares wilayah electrification plan

Proposes projects & business areas

Estimates long-term electrification funding needs; aligns targets with funding Review & approve proposed projects. Start APBN budget process

Prior year

Notify Pemda of indicative funding from DAK for off-grid projects

Express interest in administering DAK projects

Finalize DAK budget incl. indicative future years

Prepare & submit proposal

Prepare & issue tender

Evaluate bids and issue contract Constructs System

Current year

Pays for construction per HPS

Applies for & receives DAK funding Receives asset

Pays operational subsidy based on system output

Future years

Future DAK allocations for operational subsidy Updates program design & electrification targets based on M&E results

Conducts Monitoring & Evaluation; Reports to DGE

Operates & maintains system; bills & collects customer payments

Takes over operations at end of contract period or retenders

9

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5

APPENDIX D: SUMMARY OF BREAK-OUT GROUP 1 – PLANNING & IMPLEMENTATION

D-1 Workshop on Electricity Access

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Break‐out group 1 PLANNING & IMPLEMENTATION

Ringkasan Diskusi: Perencanaan dan Implementasi ‐ Perencanaan ketenagalistrikan on‐grid dan off‐grid sudah digariskan di RUKN. RUKD disusun berdasarkan kepada RUPTL. Identifikasi off‐grid yang sulit dilistriki PLN sudah diidentifikasi. Isu di kebijakan dan perencanaan kelistrikan: Prioritas politik pemerintah daerah Perubahan insfrastruktur akses jalan baru, jaringan listrik baru Pembangkit, gardu induk dan transmisi masuk RUPTL, distribusi lebih fleksibel (kadang ad hoc)

‐ Untuk service standards: disesuaikan di masing masing daerah, tidak bisak dseragamkan untuk R‐1 450 VA ‐ Untuk kewenangan kelistrikan baik off‐grid dan on‐grid, sesuai dengan UU 30/2009: PLN tetap bertanggung jawab untuk daerah daerah yang tidak terlistriki Listrik: tanggung jawab pemerintah pusat dan pemerintah daerah Pemerintah daerah masih belum sadar apa yang harus mereka lakukan

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Ringkasan diskusi: Perencanaan dan implementasi ‐ EBTKE tetap punya wewenang kuat untuk off‐grid, tetapi tanggung jawab Pemda harus ditingkatkan bagaimana memastikan anggaran APBD yang cukup untuk O&M? tidak bisa gratis untuk masyarakat, tetapi harus dicari jalan bagaimana mendapatkan subsidi untuk O&M ‐ Sudah ada peraturan ESDM no 10/2012 mengenai pelaksanaan kegiatan fisik energi terbarukan pada saat serah terima, pemda sanggup menerima dan mengelola ‐ PLTMH vs PLTS

lebih murah

‐ Institusi yang sudah ada seperti DEN seharusnya dioptimalkan untuk perencanaan ketenagalistrikan, tidak perlu membentuk suatu institusi baru. ‐ institusi yang sudah ada perlu diberdayakan dan dioptimalkan peran sertanya di dalam perencanaan dan implementasi ketenagalistrikan

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2

APPENDIX E: SUMMARY OF BREAK-OUT GROUP 2 – FINANCING & SUBSIDY

E-1 Workshop on Electricity Access

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FINANCING & SUBSIDY Break Out Group 2

Ringkasan Diskusi (1) Need for Subsidy

Adanya resiko bahwa regulasi yang ada belum dapat mengakomodir semua khususnya perpindahan aset dan kepemilikannya Subsidi nya tidak perlu ke PLN tapi bisa di buat didalam DAK dibawah Kementrian yang berwenang

(2) Electrification Targets

Target LISDES dibagun berdasarkan RUKN dan RUPTL yang tentunya berkolerasi dengan dana yang ada di dalam APBN Pada saat ini ada pembagian yang cukup jelas, bahwa untuk “off grid” akan dikerjakan oleh EBTKE dan “on grid” adalah DJK

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Ringkasan Diskusi (3) Consumer Pricing

Dibangun rekomendasi dengan dasar TDL (tarif dasar listrik) untuk wilayah tertentu dalam pembangunan listrik desa Dengan diberikan harga yang sama maka LISDES juga merupakan bagian nasional subsidi

(4) Value of Money

Capital subsidi

Ringkasan Diskusi (5) Non PLN Subsidy Mechanism

Dalam diskusi masih tetap menggunakan format yang telah ada yaitu PLN DAK di kementrian yang berwenang

(6) Monitoring & Evaluation

Diskusi dimulai adanya UU pasal 23. Dimana propinsi menjadi perpanjangan tangan dari Pemerintah Pusat Dalam diskusi direkomendasikan bahwa Propinsi yang menjadi perwakilan pemerintah pusat.

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Ringkasan Diskusi (7) Legal Basis

Sama dengan point pertama bahwa regulasi adalah point pertama yang harus dibahas dan selanjutnya adalah kordinasi Adanya keinginan dimasukkan “issues” semua ini kedalam RUKN

(8) Langkah Selanjutnya Membuat “keppres” yang dikoordinasaikan oleh Ke-mentrian Koordinator Ekonomi. Keppres ini akan fokus didalam “Pembangunan Listrik Desa” di seluruh wilayah. Dasar pembuatan keppres ini adalah RUKN (rencana umum ketenagalistrikan nasional) ESDM menjadi penggagas dari semua ini. Transfer asset melalui DAK bisa diberikan kepada propinsi, baru diserahkan kepada wilayah atau kabupaten yang berkepentingan

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3

Selesai

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Efektivitas Perencanaan Antar Instansi Pada Program Kelistrikan di Indonesia

Kementerian Perencanaan Pembangunan Nasional/BAPPENAS Jakarta, 19 Maret 2015

STRATEGI PEMBANGUNAN NORMA PEMBANGUNAN M U

A

3 DIMENSI PEMBANGUNAN DIMENSI PEMBANGUNAN MANUSIA

Pendidikan

DIMENSI PEMBANGUNAN SEKTOR UNGGULAN

DIMENSI PEMERATAAN & KEWILAYAHAN

Kedaulatan Pangan

Antarkelompok Pendapatan

Kesehatan

Kedaulatan Energi & Ketenagalistrikan

Perumahan

Kemaritiman dan Kelautan

Mental / Karakter

Pariwisata dan Industri

Antarwilayah: (1) Desa, (2) Pinggiran, (3) Luar Jawa, (4) Kawasan Timur

KONDISI PERLU Kepastian dan Penegakan Hukum

Keamanan dan Ketertiban

Politik & Demokrasi

Tata Kelola & RB

QUICK WINS DAN PROGRAM LANJUTAN LAINNYA

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PENINGKATAN KAPASITAS DAYA LISTRIK PER PER WILAYAH TAHUN 2015-2019 Pertumbuhan Ekonomi (Persen)

Wilayah

2015

2016

2017

2018

2019

Sumatera Jawa Bali Nusa Tenggara Kalimantan Sulawesi Maluku Papua

Wilayah

Penambahan Kapasitas (GW) 2015

2016

2017

2018

2019

2015 2019 *

Sumatera Jawa Bali

Nusa Tenggara Kalimantan Sulawesi Maluku Papua

Sasaran dan Kebijakan Pembangunan Ketenagalistrikan Nasional 1.

Peningkatan pelayanan ketenagalistrikan nasional termasuk wilayah perdesaan, terpencil dan perbatasan melalui peningkatan kapasitas (availability), jangkauan (accessibility), dan kualitas (acceptability) pasokan tenaga listrik serta dengan memperbesar peran swasta.

2.

Peningkatan optimalisasi bauran energi untuk ketenagalistrikan: – kebijakan Domestic Market Obligation (DMO ) produksi gas dan batubara nasional untuk ketenagalistrikan. – pemanfaatan energi terbarukan.

3.

Kebijakan harga yang tepat dengan pengalihan subsidi energi (listrik) yang konsumtif ke sektor produktif untuk percepatan infrastruktur dan kesejahteraan rakyat.

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2

RENCANA PERCEPATAN PEMBANGUNAN PEMBANGKIT LISTRIK 35.000 MW 2015-2019 2014

Kapasitas Pembangkit 2014 adalah 50,7 GW dan Rasio Elektrifikasi 81,5* Persen Pertumbuhan Ekonomi 6,7 persen

triliun, terdapat kekurangan sebesar Rp 359 triliun, diharapkan dari

anggaran

pemerintah, yang sebagian dalam bentuk Penyertaan Modal Negara (PMN) dan pinjaman/penerusan pinjaman, agar kondisi keuangan PT. PLN menjadi sehat. Debt

Kapasitas pembangkit sekitar 85,7 GW dan

2019

Kemampuan investasi PT PLN dan bantuan APBN selama lima tahun sebesar Rp 250

Rasio Elektrifikasi 96,6 persen

Equity Rasio PT. PLN saat kondisinya kronis sekitar 257 %. Investasi yang paling mendesak untuk mengatasi krisis listrik/potensi krisis listrik. Diperlukan program penyehatan kondisi keuangan PT. PLN melalui :

Oleh PLN: Pembangkit: 10,8 GW ( berikut Transmisi 46,6 ribu kms; Gardu Induk 105 GVA; Jaringan Distribusi 150 ribu kms)

Penyesuaian tarif dasar listrik mencapai nilai keekonomiannya pada tahun 2017,

Oleh Swasta: Pembangkit 25 GW (berikut transmisi 360 kms)

ada serta beban sasaran bauran energi)

dengan tarif yang mencerminkan kemampuan investasi PT. PLN secara mandiri (memperhitungkan beban investasi sesuai kondisi demografi dan geografi yang Merlukan injeksi Penyertaan Modal Negara untuk meningkatkan kesehatan PT.PLN Subsidi yang semakin tepat sasaran (hanya untuk pengguna dibawah 60 KWh)

Kebutuhan Investasi :

per bulan

PT. PLN 609 triliun dan Swasta Rp 580 triliun

Fasilitasi pemerintah dalam mengatasi hambatan (bottleneck) investasi, berupa: (a) penjaminan pemerintah untuk investasi; (b) Percepatan persetujuan PKLN;

Konsumsi Listrik per kapita (kWh) 843

beli listrik IPP yang lebih menarik terutama energi terbarukan; (f) fasilitasi penyediaan

1.200

PLTM, 737

PLTA; 634

PS, 1,040

(c)

fasilitasi pembebasan lahan; (d) mempermudah perijinan (e) penyesuaian harga jual gas untuk pembangkit listrik: serta (g) perlindungan hukum bagi pelaksana proyek.

PLT Lain, 81

PLTG/MG, 4,288 PLTGU, 9,165

PLTU, 25,839

PLTP, 1,160 Dalam MW

5

*Perkiraan pada saat awal penyusunan RPJMN 2015-2019

Rasio Elektrifikasi Rasio Elektrifikasi 2014 serta target 20142019

Pulau Jawa‐Bali Jawa‐Bali Jawa‐Bali Jawa‐Bali Jawa‐Bali Jawa‐Bali Jawa‐Bali Kalimantan Kalimantan Kalimantan Kalimantan Kalimantan Maluku Maluku Nusa Tenggara Nusa Tenggara Papua Papua Sulawesi Sulawesi Sulawesi Sulawesi Sulawesi Sulawesi Sumatera Sumatera Sumatera Sumatera Sumatera Sumatera Sumatera Sumatera Sumatera Sumatera Rasio Elektrifikasi Rata‐ rata Rasio Elektrifikasi Nasional

Provinsi Bali Banten DI Yogyakarta DKI Jakarta Jawa Barat Jawa Tengah Jawa Timur Kalbar Kalsel Kaltara Kalteng Kaltim Maluku Maluku Utara NTB NTT Papua Papua Barat Gorontalo Sulbar Sulsel Sulteng Sultra Sulut Aceh Babel Bengkulu Jambi Kepri Lampung Riau Sumbar Sumsel Sumut

REALISASI Rasio Elektrifikasi (%)

2004 2009 2013 2015 2016 2017 2018 2019 76,60 73,71 78,08 83,70 86,51 87,92 92,70 95,00 57,88 70,04 86,27 94,39 97,00 98,31 99,02 99,38 82,11 70,55 80,57 85,58 88,09 89,34 93,70 95,88 81,30 90,57 99,99 99,99 99,99 99,99 99,99 99,99 57,84 67,13 80,15 86,66 89,92 91,54 93,50 95,80 82,09 70,29 86,13 94,05 96,03 97,02 98,03 99,02 59,10 65,63 79,26 86,08 89,48 91,19 95,60 97,81 44,50 55,45 70,80 78,48 81,70 85,20 90,60 95,43 68,77 82,03 88,66 91,98 93,63 94,46 96,71 ‐ 70,60 76,00 78,70 84,30 91,80 95,55 51,23 66,45 74,06 77,87 83,40 91,00 94,80 49,60 67,22 83,81 92,11 94,00 95,20 96,00 98,25 51,19 69,45 78,36 82,82 85,04 87,30 89,00 95,00 51,26 58,52 87,67 90,00 91,70 92,55 93,00 95,40 28,10 32,49 64,43 80,40 84,00 87,65 91,30 95,81 22,50 28,54 54,77 67,89 75,50 85,05 91,40 94,70 28,59 32,90 36,41 69,50 77,00 83,52 88,70 94,90 28,89 33,21 75,53 90,30 91,00 92,70 93,55 95,60 44,83 67,81 79,30 82,70 87,50 92,70 95,30 36,65 55,19 65,00 73,00 83,50 90,50 95,68 54,49 68,50 82,33 89,25 91,00 92,70 93,55 95,80 53,06 71,02 80,30 85,70 89,00 91,60 95,24 54,33 46,14 74,53 88,73 93,50 95,89 97,08 98,70 47,10 64,28 81,82 90,59 93,20 94,51 95,16 96,80 56,40 90,76 89,72 93,00 94,64 95,46 96,02 97,50 53,10 65,08 97,13 98,30 98,89 99,18 99,32 99,40 57,08 78,53 89,26 91,70 93,00 95,70 97,05 39,80 41,09 75,14 92,17 94,05 95,60 96,38 97,25 67,00 56,79 69,66 77,00 80,67 85,40 90,80 95,63 37,10 53,43 77,55 89,61 92,30 93,65 94,32 97,25 38,90 56,79 77,56 87,95 90,00 91,03 93,02 95,80 61,10 69,64 80,22 85,51 88,16 89,48 91,70 95,60 39,80 63,13 70,90 76,30 79,00 89,80 95,20 97,90 67,50 78,41 87,62 92,23 94,53 95,68 96,25 98,80 59,13

76,41

85,15

88,19

91,09

93,90

96,61

65,80

80,16

85,15

88,19

91,09

93,90

96,61

TARGET

2011

2012

2013

2014

2015

2016

2017

2018

2019

72,95

76,56

80,16

81,51

85,18

88,19

91,09

93,90

96,6

2

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3

Pola Koordinasi Perencanaan dan Implementasi Program Pembangunan Ketenagalistrikan Nasional UKP4 Monev

Kemenko Perekonomian

Kemenko Kemaritiman

•Persetujuan PKLN •APBN (Incl Subsidi) •Koordinasi pengembangan TKDN •APBN (Incl Subsidi) Kemenko Kemaritiman

Kemenko Perekonomin

KemAgraria‐TR: Pengadaan lahan, Pemda Kejaksanaan : Re-eksaminasi dan peningkatan profesionalitas penegakan hukum

BKPM (PTSP) : Penggunaan Lahan Izin prinsip PMA Ijin Jetty Izin usaha Rekomendasi IPPKH dan dukungan pengadaan lahan • Ijin pinjam pakai kawasan hutan • (icl Perhutani) • IPPKH AMDAL dll • • • • •

Kementerian ESDM, KemUMKM, Kem Daerah tertinggal, Kementerian Kominfo, Pemda: • Kebijakan dan Regulasi Sektor, Feed in‐Tariff, DMO • Koordinasi penyediaan energi primer • Perencanaan, penyiapan, pelaksanaan, pengoperasian, dan monev Lisdes • Pemutihan PMN APBN • Penyiaran, telekomunikasi yang perlu listrik

Tim Koordinasi (UP3KN ) dan PMO ESDM

Kemkeu • Jaminan Pemerintah & Ijin Kementerian Pertahanan: Multiyears contract • Penggunaan lahan TNI • APBN (Incl Subsidi) • Penyempurnaan Regulasi PMN, PNBP, Pajak, skema result based approach • Regulasi Direct Lending dengan jaminan pemerintah • Regulasi Penyertaan Modal Negara

Kementerian BUMN, KemenHub, KemPU: • Persetujuan pinjaman • Persetujuan Penyertaan Modal Negara • Koordinasi penggunaan jalur KA, jalan tol, penggunaan lahan BUMN lainnya al Pelindo • Koordinasi penggunaan jalur jalan tol • Koordinasi penyediaan energi primer

Kementerian PPN/Bappenas •Arah & Kebijakan Pembangunan (RPJMN, RKP) • Penerbitan Bluebook, Mekanisme Direct Lending •APBN (Incl Subsidi) •KPS (PPP Book) •Monev

7

INFRASTRUKTUR YANG HARUS DIBANGUN 2015-2019 MEMERLUKAN DUKUNGAN PENYEDIAAN LISTRIK

Jalan baru 2.650 Km Jalan tol 1.000 Km Pemeliharaan jalan 46.770 Km

Pembangunan 15 Bandara baru Pengadaan 20 Pesawat Perintis Pengembangan Bandara untuk pelayanan Cargo Udara di 6 Lokasi Pembangunan 24 Pelabuhan baru Pengadaan 26 Kapal Barang Perintis Pengadaan 2 Kapal Ternak Pengadaan 500 unit kapal Rakyat

Pembangunan Jalur KA 3.258 km di Jawa, Sumatera, Sulawesi dan Kalimantan (KA Antar kota 2.159 km; dan KA Perkotaan 1.099 km) Pembangunan Pelabuhan Penyeberangan di 60 lokasi Pengadaan kapal penyeberangan (terutama perintis) sebanyak 50 unit Pembangunan BRT di 29 kota Pembangunan angkutan massal cepat di kawasan perkotaan (6 Kota metropolitan, 17 Kota besar)

8

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4

INFRASTRUKTUR YANG HARUS DIBANGUN 2015-2019 MEMERLUKAN DUKUNGAN DPENYEDIAAN LISTRIK Pembangunan 49 Waduk Baru dan 33 PLTA Pembangunan/Peningkatan jaringan irigasi 1 Juta Ha Rehabilitasi 3 Juta Ha Jaringan Irigasi Jangkauan Pitalebar/broadband di 100% kab/kota Indeks e-government mencapai 3,4 (skala 4,0) Pengmbangan e-pengadaan, ekesehatan, e-pendidikan, dan e-logistik Pembangunan sistem air limbah komunal di 227 kota/kab dan terpusat di 430 kota/kab Pembangunan IPLT untuk pengelolaan lumpur tinja perkotaan di 409 kota/kab Pembangunan TPA sanitary landfill dan fasilitas 3R di 341 kota/kab dan fasilitas 3R terpusat & komunal di 294 kota/kab Pengurangan genangan seluas 22.500 Ha di kawasan permukiman

Pembangunan Rusanawa 5.257 Twinblok (515.711 rumah tangga) Bantuan stimulan perumahan swadaya 5,5 Juta rumah tangga Penanganan kawasan kumuh 37.407 Ha Fasilitasi kredit perumahan untuk MBR 2,5 Juta rumah tangga Pembangunan SPAM di perkotaan 21,4 juta sambungan rumah (268.680 liter/detik) Pembangunan SPAM di perdesaan 11,1 juta sambungan rumah (22.647 desa) Pembangunan 2 kilang minyak 2x300 ribu barrel Pembangunan FSRU 5 lokasi Jaringan gas kota sebesar 1 juta sambungan rumah Pembangunan SPBG 78 unit Pembangkit listrik sebesar 35 ribu MW Gas bumi untuk 600 ribu nelayan Eksplorasi minyak bumi di laut dalam

9

TOL LAUT DALAM MENDUKUNG POROS MARITIM DUNIA

Keterangan Program 24 Pelabuhan Strategis Short sea shipping Fasilitas kargo umum dan bulk Pengembangan pelabuhan non-komersil Pengembangan pelabuhan komersil lainnya Transportasi multimoda untuk mencapai pelabuhan Revitalisasi industri galangan kapal Kapal untuk 5 tahun ke depan Kapal patroli Total

Nilai (Rp.Milyar) 243,696 7,500 40,615 198,100 41,500 50,000 10,800

Keterangan

Termasuk pengerukan, pengembangan terminal kontainer, serta lahannya Kapal, pelabuhan Panjang, sumur, Bojanegara, Kendal, Pacitan, Cirebon Rencana induk pelabuhan nasional 1.481 pelabuhan 83 pelabuhan Jalan akses, kereta pelabuhan, kereta pesisir. 12 galangan kapal Kapal container, barang perintis, bulk carrier, tug & barge, tanker, dan kapal 101,740 rakyat 6,048 Kapal patrol dari Kelas IA s/d V 699,999

10

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5

Pengembangan Transportasi Penyeberangan (Komplemen Konsep Tol Laut) Arah kebijakan pengembangan transportasi penyeberangan 2015-2019: •

Penyelesaian dan penguatan jalur lintas Sabuk Utara, Sabuk Tengah dan Sabuk Selatan serta poros penghubung. • Terobosan regulasi termasuk kebijakan pengadaan kapal oleh pemerintah dan pembentukan Otorita Pelabuhan Penyeberangan. Program Strategis dan Target:

Koridor Penyebe rangan

Keb. Biaya

Kondisi Saat ini dan Rencana Pembangunan

Sabuk Utara

Terdapat lintas yang belum terhubung yaitu: Tj. Pinang – Sintete, akan diselesaikan pada 20172019

Sabuk Tengah

Terdapat lintas yang belum terhubung: Wahai – Fak Fak, akan diselesaikan pada akhir tahun 2014. Akan dilakukan peningkatan layanan (pelabuhan dan kapal)

Sabuk Selatan

Telah terhubung sejak tahun 2013, akan dilakukan peningkatan layanan (pelabuhan dan kapal)

Pembangunan pelabuhan penyeberangan di 60 lokasi • Pembangunan kapal penyeberangan (terutama perintis) 50 unit • Pemisahan operator dan regulator (pembentukan Otorita Pelabuhan) • Pembangunan kapal untuk mengatasi bottleneck pada lintas utama termasuk lintas Merak -Bakauheni (melalui PMN pada BUMN) •

Rp. 40 T

11

RENCANA PEMBANGUNAN 15 BANDARA BARU DAN PENGEMBANGAN 10 BANDARA MELALUI KPS

Miangas

Letung

Siau

Juwata

Maratua

Muara Teweh Tojo Una2 Tambelan

Sultan Babullah Werur

Mutiara Morowali Tjilik Riwut Fatmawati

Samarinda Baru Sentani

Hananjoedin

Redin Inten II

Buntu Kunik

Namniwel

Matohara

Kertajati

Komodo

Koroway Batu

Kabir‐Patar

Keterangan: Rencana Pembangunan Bandara Baru Bandara Ditawarkan Ke Swasta 12

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6

Pembangunan Infrastruktur Mendukung 13 Kawasan Industri di Luar Jawa Kebutuhan penanganan infrastruktur untuk mendukung 13 Kawasan Industri sebesar Rp.55,444.8 Triliun SEKTOR

INVESTASI

Bandara Jalan Kereta Api

8,200.00 8,079.74 10,085,00

Ketenagalistrikan Pelabuhan Sumber Daya AIR

10,477.06 17,664.00 939.00

Total

55,444,80

SUMATERA 1. Kuala Tanjung - Sumut 2. Seimangke – Sumut 3. Tanggamus - Lampung KALIMANTAN 4. Batulicin – Kalsel 5. Ketapang - Kalbar 6. Landak - Kalbar;

PROYEK STRATEGIS Pelabuhan: Pembangunan Pel.Kualatanjung, Tanjung Perak, Pontianak, Bitung, Makassar, Banjarmasin, Kupang dan Halmahera Tol: Pembangunan Jalan Tol Manado Bitung Jalan: Pembangunan Jalan Lingkar Batulicin, Palu-Parigi, Lingkar Kupang, Jalan Susumuk-Bintuni Kereta Api: Pembangunan jalur KA antara Manado – Bitung, Sei Mangke – Bandar Tinggi - Kuala Tanjung, Pasoso – Tanjung Priok, DDT dan Elektrifikasi Manggarai–Bekasi -Cikarang, Lingkar Luar Kereta Api . Listrik: Pembangunan pembangkit listrik (PLTU Kualatanjung, Asahan 3, Pangkalan Susu, PLTU Palu, PLTA Poso, PLTMG Morowali, PLTU NTT-2 Kupang, PLTU Ketapang (FTP2), PLTG/MG Pontianak Peaker, PLTU Bengkayang, Parit Baru, Pulau Pisau, PLTA Konawe, PLTA/MH Morowali, Bantaeng dan PLTGU Tangguh, dll. Bandara: Pengembangan Bandara Mutiara Palu, Eltari Kupang, Pengembangan, Halu Oleo Kendari. Sam Ratulangi Manado dan Bandara Syamsuddin NoorBanjarmasin

MALUKU 12. Buli, Halmahera Timur-MaluT PAPUA 13. Teluk Bintuni, Papua Barat

SULAWESI 7. Palu – Sulteng 8. Morowali - Sulteng 9. Bantaeng - Sulsel 10. Bitung – Sulut 11. Konawe – Sultra

13

PEMBANGUNAN INFRASTRUKTUR MENDUKUNG KAWASAN EKONOMI KHUSUS 1 7

14

8

5 6 2

3 4 1. KEK SEI MANGKEI

3. KEK TANJUNG LESUNG

• Pelabuhan Kuala Tanjung • Bandara Kualanamu • Akses Jalan • Akses Jalur KA • Pembangkit Listrik

• Pelabuhan Tanjung Priuk • Bandara Banten Selatan • Akses Jalan • Akses ASDP • Akses Jalur KA • Pembangkit Listrik

2. KEK TANJUNG API-API

• Bandara Sultan Mahmud Badaruddin II • Akses Jalan • Akses Jalur KA • Pembangkit Listrik

5. KEK MALOY BATUTA TRANS KALIMANTAN

7. KEK BITUNG

• Pelabuhan Maloy • Akses Jalan • Pembangkit Listrik

• Pelabuhan Hub Int. Bitung • Bandara Samratulangi • Akses Jalan • Akses Penyeberangan • Akses Kereta Api • Pembangkit Listrik

4. KEK MANDALIKA

6. KEK PALU

8. KEK MOROTAI

• Bandara Int. Lombok • Pelabuhan Lembar Baru • Integrasi Moda • Akses Jalan • Akses Ferry • Pembangkit Listrik

• Bandara Mutiara Sis Aljufri Palu • Pelabuhan Pantoloan • Akses Jala • Akses Penyeberangan • Pembangkit Listrik

• Pelabuhan Ternate • Bandara Pitu Morotai • Akses Jalan • Akses Penyeberangan • Pembangkit Listrik

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7

Pembangunan Infrastruktur Mendukung Kawasan Strategis Pariwisata Nasional dalam Destinasi Pariwisata Nasional

16 KSPN Prioritas

DUKUNGAN LANJUTAN TERHADAP 16 KSPN PRIORITAS

Proyek Strategis • Rantauprapat - Gunung Tua - Padang Sidempuan- Sibolga • Jalan Tol Medan-Kualanamu-Tebing Tinggi

Sumatera

Danau Toba, dskt

Jawa

Kep. Seribu, dskt Kota Tua – Sunda Kelapa, dskt Borobudur, dskt Bromo – Tengger – Semeru, dskt

Kalimantan

Tanjung Puting, dskt

Sulawesi

Toraja, dskt Bunaken, dskt Wakatobi, dskt

• Pelebaran Jalan Sp. Meluang - Pelabuhan Derawan • pelebaran jalan Lingkar Luar Kota Labuhan Bajo • pembangunan jalan Toraja • Pembangunan jalur KA antara Manado - Bitung

Kintamani-Danau Batur, dskt Menjangan-Pemuteran, dskt Kuta-Sanur-Nusa Dua, dskt Rinjani, dskt Pulau Komodo, dskt Ende-Kelimutu, dskt

Bali-Nusa Tenggara

Papua-Kep. Maluku

Raja Ampat, dskt

• Reaktivasi jalur KA antara Yogyakarta – Magelang & Magelang – Ambarawa • Pembangunan Bandara Internasional di DI Yogyakarta • Pembangunan Jalan Lingkar Probolinggo

• • • • • •

Bandara Internasional Lombok Pembangunan dermaga kapal pesiar di Labuan Bajo, Pelabuhan Laut Pulau Komodo Pengembangan Dermaga Wisata di Rinca, Pengembangan Dermaga Wisata di Maumere Pengembangan Dermaga Wisata di Ende

Pengembangan Pelabuhan di Sorong dan Faspel Laut Arar

15

LOKASI 33 PEMBANGUNAN PLTA (Program 49 Waduk)

• Peusangan 1 – 2, 88 Mw, Peusangan-4, 400 Mw (NAD)

• Wampu, 45 Mw,-Asahan III (FTP 2), 174 Mw, Hasang (FTP 2, 40 Mw, Simonggo-2, 86 MW, Batang Toru (Tapsel), 510 Mw, Masang-2, 55 Mw (Sumut)

• Karama Peaking (Unsolicited) 150 Mw, Karama Baseload (Unsolicited), 300 Mw (Sulbar) • Duminanga, 1 Mw,Sawangan, 12 Mw (Sulut)

• PLTA Tersebar Maluku Utara, 4.5 Mw, (Malut)

• Bontobatu (FTP2), 110 Mw, Malea, 90 Mw (Sulsel)

• Isal 3 , 4 Mw, Nua (Masohi), 6 Mw, Wai Tala 13.5 Mw, Wai Tala 40.5 Mw, Isal, 6 Mw, PLTA Tersebar Maluku , 18.5 Mw(Maluku)

• Simpang Aur (FTP2), 23 Mw, Ketahun-3, 61 Mw (Bengkulu)

• Warsamson, 46,5 Mw(Papua Barat)

• Merangin, 350 Mw(Jambi)

• Semangka (FTP2), 56 Mw(Lampung)

• Kusan, 65 Mw(Kalsel) • Brang Beh 1, 8 Mw, Brang Beh 2, 4.1 Mw NTB)

• Konawe, 50 Mw, Watunohu 1, 20 Mw (Sultra)

• Maubesi ,1 Mw, Kudungawa, 2 Mw, Ubungawu III, 0.2 Mw (NTT)

• Orya 2, 10 Mw, Kalibumi-2, 5 Mw, Mariarotu II 1.3 Mw, Baliem, 10 Mw, Kalibumi III Cascade, 5 Mw, Baliem, 40 Mw, Tatui, 4 Mw, Amai, 1.4 Mw (Papua)

16

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8

gxÜ|Åt ^tá|{ 17

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9

TARGET DAN PENCAPAIAN RASIO ELEKTRIFIKASI INDONESIA Disampaikan pada acara Lokakarya Peningkatan Akses Energi Listrik Perdesaan Berbasis EBT di Indonesia Direktorat Pembinaan Program Ketenagalistrikan Jakarta, 19 Maret 2015

DAFTAR ISI:

I. GAMBARAN UMUM KONDISI KETENAGALISTRIKAN II. PRAKIRAN KEBUTUHAN TENAGA LISTRIK (DRAFT RUKN 2015 – 2034) III. REALISASI RE S.D 2014 DAN RENCANA PROGRAM LISDES 2015

2

Page 330 of 396

1

I. GAMBARAN UMUM KONDISI KETENAGALISTRIKAN NASIONAL

Gambaran Umum Kondisi Ketenagalistrikan Nasional Persentase Kapasitas Pembangkit

Total Kapasitas Terpasang Pembangkit (2014)

53.585 MW

(PLN: 37.280 MW, IPP: 10.995 MW, PPU: 2.634 MW, IO Non BBM: 2.677 MW)

Persentase Pemakaian Listrik Per-golongan

Konsumsi Energi Listrik (2014)

Produksi Tenaga Listrik (2014)*)

199 TWh

228 TWh

Pangsa BBM pada Energi Mix untuk Pembangkit Tenaga Listrik

Persentase Energy Mix Air Lain‐Lain 0.4% BBM Panas 6.5% 11.7% Bumi Gas 4.4% 24.2% Batubara 52.8%

*)

11,65 % Rasio Elektrifikasi Nasional (2014)

84,35%

Hanya PLN dan IPP

4

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2

Realisasi Pembangkit PLN dan IPP (2010 – 2014) (MW)

Tambahan Kapasitas per Jenis Pembangkit

Per‐ Jenis Pembangkit

Realisasi COD per Tahun

PLTA, PLTM, 89 424 PS, ‐ PLTG/MG, 1,516

PLT Lain, 41

PLTD, 2,960

PLTU, 10,516

PLTGU, 1,733

PLTP, 216

Kapasitas pembangkit PLN & IPP akhir tahun 2009 sekitar 30 GW meningkat menjadi sekitar 48 GW pada akhir tahun 2014 Sumber: DJK & RUPTL PLN 2015-2024

5

Rasio Elektrifikasi 2014 Category :

Aceh

92,75%

> 70 %

Sumut

91,17%

Kaltim&Kaltara

50 - 70 %

88,28%

< 50 %

Riau

Sulut

Kalbar

84,28%

Gorontalo

79,78%

Kepri

85,31%

73,60%

80,53%

Malut

90,21%

Papua Barat

77,16% Sumbar

Sumsel

79,82%

76,87%

Kalteng

66,60%

Sulteng

75,26% Jambi

80,17%

Babel

Sulbar

95,48%

71,55%

Papua

43,17%

Sultra Bengkulu

Jakarta

Jateng

99%

87,11%

83,49%

66,87%

Kalsel

Lampung

80,91%

Maluku

82,22%

83,03%

Banten

Bali

Sulsel

85,30%

85,10%

92,57% Jabar

85,95%

DIY

Jatim

NTB

NTT

81,84%

83,30%

67,57%

59,52%

REALISASI 2010

2011

2012

2013

(67,15%) 67.15%

(70,40 %) 72.95%

(73,60 %) 76.56%

(76,80 %) 80.51%

TARGET SESUAI DRAFT RUKN 2015-2034 2014 (81.51%)

84.35%

2015

2016

2017

2018

2019

87.35%

90.15%

92.75%

95.15%

97.35%

6

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3

II. PRAKIRAAN KEBUTUHAN TENAGA LISTRIK (DRRAFT RUKN 2015 – 2034)

ASUMSI DAN PROYEKSI DRAFT RUKN 2015 - 2034

No.

Uraian

2015 – 2019

2020 – 2034

1.

Asumsi Pertumbuhan Ekonomi

5,7% - 7,0%

6,5% - 7,0%

2.

Asumsi Inflasi

5,0% - 3,8%

rata-rata 3,6%

3.

4.

Asumsi Pertumbuhan Penduduk per-tahun (rata-rata) *) - Jawa - Bali - Luar Jawa - Bali - Indonesia Prakiraan Pertumbuhan Kebutuhan Energi Listrik per-tahun (rata-rata) - Jawa - Bali - Luar Jawa - Bali - Indonesia

0,75 % 1,19 % 0,94 %

7,5 % 9,2 % 8,0 %

*) Sumber: proyeksi penduduk Indonesia 2010-2035 (Bappenas-BPS-UNPF), 2013

Page 333 of 396

4

PRAKIRAAN INDONESIA

TWh 1,000

250

900 800

200

700

GW

600

150

500 400

100

300 200

50

100 0

2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034

Kebutuhan tambahan daya (GW) **)

11

17

23

29

36

45

53

62

Kapasitas exsisting (GW) *)

41

40

39

38

37

36

35

34

33

32

32

31

30

29

28

28

27

26

26

25

Kapasitas tahun berjalan (rencana) (GW)

52

56

61

67

73

80

87

96

104

114

125

134

143

153

163

174

185

197

210

224

72

83

95

105

115

125

137

161

174

188

0

203

Beban Puncak (GW)

38

41

45

49

54

59

64

70

76

84

92

98

105

112

119

127

135

144

154

164

Kebutuhan Energi Listrik (TWh)

214

233

254

277

303

331

362

395

432

472

517

553

591

630

671

714

760

809

862

919

*) Kapasitas tahun 2014 **) Akumulasi

Kapasitas merupakan Daya Mampu Netto

No. Uraian 1. Pertumbuhan ekonomi 2.

148

Inflasi

2015 - 2019 5,7% - 7,0%

2020 - 2034 6,5% - 7,0%

5,0% - 3,8%

rata-rata 3,6%

3.

Pertumbuhan penduduk per-tahun (rata-rata )

4.

Pertumbuhan kebutuhan listrik per-tahun rata-rata

0,19 %

5.

Kebutuhan tambahan daya rata-rata per-tahun (20 thn)

10.048 MW

6.

Kebutuhan tambahan daya rata-rata per-tahun (10 thn)

8.097 MW

8,0 %

Potensi Energi Primer: • • • • • •

Batubara Gas Bumi Minyak Bumi Panas Bumi Air CBM

: 148.356,06 Juta Ton : 153,38 TSCF : 7.732,28 MMSTB : 29.215,00 MWe : 12.411,20 MW : 453,30 TCF

PETA TAPAK PEMBANGKIT PROGRAM 35,5 GW DAN 7,4 GW Sumatera: PLN : 2.79 GW (23 unit) IPP : 5.96 GW (49 unit) Total : 8.75 GW (72 unit) Sumatera: PLN : 1.43 GW (14 unit) IPP : 1.14 GW (18 unit) Total : 2.57 GW (32 unit)

Kalimantan: PLN : 0,92 GW (18 unit) IPP : 0,96 GW (12 unit) Total : 1,87 GW (30 unit) Kalimantan: PLN : 0.88 GW (28 unit) IPP : 0.09 GW ( 7 unit) Total : 0.97 GW (35 unit)

Sulawesi: PLN : 2,02 GW (28 unit) IPP : 0,68 GW (40 unit) Total : 2,70 GW (68 unit)

Maluku: PLN : 0,26 GW (18 unit) IPP : 0,02 GW ( 4 unit) Total : 0,28 GW (22 unit)

Sulawesi: PLN : 0.33 GW (15 unit) IPP : 0.14 GW (10 unit) Total : 0.47 GW (25 unit)

Maluku: PLN : 0.05 GW (5 unit) IPP : ‐ Total : 0.05 GW (5 unit)

Sulawesi

Java‐Bali Jawa‐Bali: PLN : 7,38 GW (19 unit) IPP : 13,53 GW (76 unit) Total : 20,91 GW (95 unit) Jawa‐Bali: PLN : 1.21 GW ( 6 unit) IPP : 1.75 GW (12 unit) Total : 2.96 GW (18 unit) Sumber: RUPTL PLN 2015-2024

Papua: PLN : 0.07 GW (8 unit) IPP : ‐ Total : 0.07 GW (8 unit)

Maluku

Kalimantan

Sumatera

Papua: PLN : 0,22 GW (19 unit) IPP : 0,12 GW (17 unit) Total : 0,34 GW (36 unit)

Papua

Nusa Tenggara

Nusa Tenggara: PLN : 0,66 GW (16 unit) IPP : 0,05 GW ( 9 unit) Total : 0,70 GW (25 unit) Nusa Tenggara: PLN : 0.19 GW (15 unit) IPP : 0.08 GW ( 6 unit) Total : 0.27 GW (21 unit)

Indonesia: PLN : 18,42 GW (232 unit) IPP : 24,51 GW (260 unit) Total : 42,93 GW (492 unit)

Program: 35,56 GW On Going: 7,37 GW

Page 334 of 396

5

PETA TRANSMISI PROGRAM 35,5 GW DAN 7,4 GW Sumatera: 70 kV 150 kV 275 kV 500 kV 500 kVDC TOTAL

: 611 kms : 11.239 kms : 5.082 kms : 1.130 kms : 1.243 kms : 19.305 kms

Kalimantan: 150 kV : 7.703 kms 275 kV : 180 kms TOTAL : 7.883 kms

Sulawesi: 70 kV 150 kV TOTAL

: 86 kms : 4.900 kms : 4.986 kms

: 237 kms : 416 kms : 653 kms

Papua: 70 kV 150 kV TOTAL

Sulawesi

Java‐Bali Jawa‐Bali: 70 kV 150 kV 500 kV 500 kVDC TOTAL

: 304 kms : 60 kms : 364 kms

Maluku

Kalimantan

Sumatera

Maluku: 70 kV 150 kV TOTAL

Papua

Nusa Tenggara

: 44 kms : 8.431 kms : 2.411 kms : 300 kms : 11.185 kms

Nusra: 70 kV 150 kV TOTAL

INDONESIA: 70 kV : 2.689 kms 150 kV : 33.562 kms 275 kV : 5.262 kms 500 kV : 3.541 kms 500 kVDC : 1.543 kms TOTAL : 46.597 kms

: 1.408 kms : 813 kms : 2.221 kms

Sumber: RUPTL PLN 2015-2024

KEBUTUHAN FASILITAS DISTRIBUSI DI INDONESIA satuan

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

Jumlah

Jaringan TM

Uraian

ribu kms

15,6

16,5

16,5

16,5

17,0

16,9

16,4

16,4

16,8

17,1

165,8

Jaringan TR

ribu kms

13,2

13,3

13,5

13,8

14,3

14,3

13,9

13,8

14,1

14,2

138,4

Trafo Distribusi

ribu MVA

3,9

4,1

4,2

4,3

4,3

4,4

4,4

4,4

4,6

4,7

43,4

Tambahan Pelanggan juta plgn

3,3

3,2

2,6

2,5

2,2

1,7

1,5

1,4

1,3

1,3

21,0

Sumber: RUPTL PLN 2015-2024

Page 335 of 396

6

III. REALISASI RE S.D 2014 DAN RENCANA PROGRAM LISDES 2015

Rasio Elektrifikasi 2014 Category :

Aceh

92,75%

> 70 %

Sumut

91,17%

Kaltim&Kaltara

50 - 70 %

88,28%

< 50 %

Riau

Sulut

Kalbar

84,28%

Gorontalo

79,78%

Kepri

85,31%

73,60%

80,53%

Malut

90,21%

Papua Barat

77,16% Sumbar

Sumsel

79,82%

76,87%

Kalteng

66,60%

Sulteng

75,26% Jambi

80,17%

Babel

Sulbar

95,48%

71,55%

Papua

43,17%

Sultra Bengkulu

Jakarta

Jateng

99%

87,11%

83,49%

66,87%

Kalsel

Lampung

80,91%

Maluku

82,22%

83,03%

Banten

Bali

Sulsel

85,30%

85,10%

92,57% Jabar

85,95%

DIY

Jatim

NTB

NTT

81,84%

83,30%

67,57%

59,52%

REALISASI 2010

2011

2012

2013

(67,15%) 67.15%

(70,40 %) 72.95%

(73,60 %) 76.56%

(76,80 %) 80.51%

TARGET SESUAI DRAFT RUKN 2015-2034 2014 (81.51%)

84.35%

2015

2016

2017

2018

2019

87.35%

90.15%

92.75%

95.15%

97.35%

14

Page 336 of 396

7

NATIONAL BUDGET (APBN)

No. PROJECT UNIT (SATKER) Satker Ketenagalistrikan (DGE) Main Unit of 2. Development (UIP‐PLN) 1.

Additional proposals APBN 2015

APBN 2015

Proposed APBN (APBN‐P) 2015

201.617,3

‐

201.617,3

1.172.130,8

‐

1.172.130,8

3. Rural Electricity (Lisdes)

2.563.380,3

1.300.000 **)

3.863.380,3

Total

3.937.128,4

1.300.000

5.237.128,40

LISDES PROGRAM YEAR 2015 (1) LISTRIK PERDESAAN Fisik

No.

Jaringan (Kms)

Provinsi

LISTRIK GRATIS

Biaya GD Pagu Lisdes

JTM

JTR

Total

Unit

MVA

JTM

JTR

RTS

GD

Pagu Listrik Gratis

Pagu Total

1

Nanggroe Aceh Darussalam

167.00

175.00

342.00 101

4.025

42,954,787,000

25,219,700,000

10,383,743,000

78,558,230,000

4,352

9,792,000,000

88,350,230,000

2

Sumatera Utara

142.00

125.00

267.00 100

3.000

45,820,698,000

17,988,475,000

9,183,460,000

72,992,633,000

1,241

2,792,250,000

75,784,883,000 71,953,363,000

3

Sumatera Barat

121.00

161.89

282.89

58

2.900

39,324,246,000

23,978,467,000

5,858,400,000

69,161,113,000

1,241

2,792,250,000

4

Riau

147.50

211.75

359.25 100

6.600

38,235,371,000

27,238,245,000

15,369,804,000

80,843,420,000

1,250

2,812,500,000

83,655,920,000

5

Kep. Riau

97.07

112.00

209.07

44

3.000

28,382,891,000

16,244,244,000

6,813,548,000

51,440,683,000

1,000

2,250,000,000

53,690,683,000

6

Jambi

145.14

129.17

274.31

91

6.600

52,085,201,000

16,678,186,000

13,042,528,000

81,805,915,000

1,471

3,309,750,000

85,115,665,000

7

Bangka Belitung

121.40

91.00

212.40

59

4.050

38,259,774,000

15,323,778,000

7,165,408,000

60,748,960,000

2,360

5,310,000,000

66,058,960,000

8

Bengkulu

112.00

148.00

260.00

75

4.600

32,469,683,000

26,858,152,000

15,415,289,000

74,743,124,000

2,134

4,801,500,000

79,544,624,000

9

Sumatera Selatan

154.00

169.50

323.50

92

5.600

55,611,402,000

24,946,849,000

13,301,860,000

93,860,111,000

2,422

5,449,500,000

99,309,611,000

10

Lampung

114.00

121.00

235.00

71

5.350

33,753,583,000

21,857,561,000

14,889,196,000

70,500,340,000

1,111

2,499,750,000

73,000,090,000

11

Banten

39.50

143.85

183.35

85

4.400

17,445,581,000

30,311,714,000

13,117,581,000

60,874,876,000

3,361

7,562,250,000

68,437,126,000

12

Jawa Barat

112.00

186.05

298.05

83

5.300

40,558,609,000

31,411,007,000

11,641,716,000

83,611,332,000

3,295

7,413,750,000

91,025,082,000

13

Jawa Tengah

110.00

178.00

288.00 172

8.600

22,963,390,000

30,979,476,000

11,957,096,000

65,899,962,000

3,229

7,265,250,000

73,165,212,000

14

DI Yogyakarta

15

Jawa Timur

84.00

140.00

224.00

89

8.900

32,258,839,000

29,223,656,000

12,446,212,000

73,928,707,000

2,093

4,709,250,000

78,637,957,000

16

Kalimantan Barat

111.00

90.80

201.80

56

3.600

43,858,469,000

16,780,362,000

8,053,629,000

68,692,460,000

1,376

3,096,000,000

71,788,460,000

Page 337 of 396

8

LISDES PROGRAM YEAR 2015 (2) LISTRIK PERDESAAN Fisik

No.

Jaringan (Kms)

Provinsi

LISTRIK GRATIS

Biaya GD Pagu Lisdes

JTM

JTR

Total

Unit

MVA

JTM

JTR

RTS

GD

Pagu Listrik Gratis

Pagu Total

99.99

99.99

2022

99.35

100.00

2021

TARGET RE DRAFT RUKN 2015-2034 99.99 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

97.35 95.15

95.00 92.75 90.15

90.00 87.35

85.00

Luar Jawa‐Bali

Jawa‐Bali

2034

2033

2032

2031

2030

2029

2028

2027

2026

2025

2024

2023

2020

2019

2018

2017

2016

2015

80.00 INDONESIA

• Kebutuhan penambahan penyambungan baru 2015-2019 rata-rata sekitar 2,47 juta sambungan per tahun. • Kebutuhan penambahan penyambungan baru 2015-2021 rata-rata sekitar 2,24 juta sambungan per tahun. • Sebaran target RE per provinsi tahun 2015-2021 dibreakdown berdasarkan taget Nasional dengan mempertimbangkan provinsi yang memiliki banyak pulau kecil; • Target RE Jakarta 100% pada tahun 2018; • RE Banten mencapai 100% lebih lambat (pada tahun 2025) dibanding provinsi lainnya di Jawa, diestimasikan pada tahun 2025 Suku Badui baru mau menerima sambungan listrik.

Page 338 of 396

9

TARGET RE DRAFT RUKN 2015-2034

• Dengan asumsi dan kondisi saat ini target sesuai draft RUKN dan RUPTL sampai dengan 2020 sebesar 99,35% dapat tercapai. • Pada periode sejak tahun 2021 dimana pada tahun 2024 target RE sebesar 100% diharapkan tercapai maka diperlukan terobosan dan kebijakan yg mendukung dalam pengembangan usaha listrik perdesaan yang melibatkan pihak swasta. • Saat ini DJK sedang memikirkan wacana regulasi tentang micro grid dan micro IPP dalam pengembangan usaha listrik perdesaan atau daerah terpencil.

www.esdm.go.id

Page 339 of 396

10

7.

BIOMASS ASSESSMENT FOR BALI AND PAPUA


December 2015

Page 340 of 396

Assessment of Biomass Resource in Bali and Papua Province of Indonesia

Prepared for ADB

i Page 341 of 396

Abbreviations and Acronyms Acronym

Extension

BOD

Biochemical oxygen demand

BDT

Biomass Dry Tonnes

CH4

Methane (chemical formula)

CO2

Carbon dioxide (chemical formula)

COD

Chemical oxygen demand

CPO

Crude palm oil

EFB

Empty fruit bunches

FFB

Fresh fruit bunches

GDP

Gross domestic product

GHG

Greenhouse gas

IPCC

Intergovernmental Panel on Climate Change

LHV

Low heating value

MC

Moisture content

MCF

Methane conversion factor

MF

Mesocarp fiber

MSW

Municipal solid waste

MTCO2e

Metric ton of carbon dioxide equivalent

OPF

Oil palm fronds

OPT

Oil palm trunk

PKS

Palm Kernel Shell

POME

Palm oil mill effluent

SBR

Sequencing batch reactor

t

Tonne

TSS

Total suspended solids

UASB

Up-flow anaerobic sludge blanket reactor

ii Page 342 of 396

Units of Measure boe – barrel oil equivalent GWh – Gigawatt hour ha – hectare kg -kilogram kWh – kilowatt hour (103 Wh) L – liter M3-cubic meter Mt – Megatonne (103 tonnes) MWh – Megawatt hour (106 Wh) MWe – Megawatt electric TJ – Terajoule (1012 J) Tonne -metric ton

iii Page 343 of 396

Glossary of Plant Names Acacia (Acacia mangium) Cacao (Theobroma cacao) Cassava (Manihot esculenta) Coconut Palm (Cocos nucifera) Coffee (Rubiaceae family) Candlenut (Aleurites moluccanus) Groundnut (Peanut/ Arachishypogaea) King Grass (Pennisetum purpureum) Maize (Zea mays) Oil Palm (Elaeis guineensis) Rubber Tree (Hevea brasiliensis) Sugarcane (Poaceae sp.)

iv Page 344 of 396

Table of Contents Abbreviations and Acronyms .................................................................................................... ii Units of Measure ........................................................................................................................ iii Glossary of Plant Names ........................................................................................................... iv List of Tables ............................................................................................................................. vii List of Figures ........................................................................................................................... vii EXECUTIVE SUMMARY ........................................................................................................... viii 1.

INTRODUCTION.................................................................................................................. 1 1.1 BIOMASS ....................................................................................................................................... 1 1.2 PROJECT OBJECTIVE AND APPROACH .......................................................................................... 1 1.3 ORGANIZATION OF THIS REPORT ................................................................................................. 2

2.

BIOMASS AGRICULTURE RESOURCES, FOREST RESOURCES, URBAN RESOURCES ...................................................................................................................... 3 2.1 BIOMASS AGRICULTURE RESOURCES ................................................................................... 3 2.1.1 Paddy ..................................................................................................................................... 3 2.1.2 Groundnuts ........................................................................................................................... 3 2.1.3 Cassava .................................................................................................................................. 4 2.1.4 Maize ..................................................................................................................................... 5 2.1.5

Coconut ................................................................................................................................ 7

2.1.6

Coffee ................................................................................................................................... 8

2.1.7

Cocoa .................................................................................................................................... 9

2.1.8

Candlenuts (Aleurites moluccana (L.) Wild) ....................................................................... 10

2.1.9

Sugarcane ........................................................................................................................... 11

2.1.10 Oil Palm wastes .................................................................................................................. 13 2.2

BIOMASS FOREST RESOURCES ........................................................................................... 14

2.2.1

Rubber wood ...................................................................................................................... 14

2.2.2

Forest residues ................................................................................................................... 16

2.2.5

Logging residue of Acacia Mangium .................................................................................. 19

2.2.6

Elephant Grass (Rumput Gajah/Pennisetum purpureum) .................................................. 20

2.3

BIOMASS URBAN RESOURCES ............................................................................................ 20

2.3.1

Municipal Solid Waste ........................................................................................................ 20

APPENDIX A: FRESH AND DRY WEIGHT RATIO OF BIOMASS ...................................................... 22 APPENDIX B: YIELD AND HEATING VALUE OF BIOMASS ............................................................. 25 APPENDIX C: TYPES OF BIOMASS GENERATORS PLANTS ......................................................... 28 APPENDIX D: TERMS OF REFERENCE .............................................................................................. 31

v Page 345 of 396

APPENDIX E: BIOMASS WASTE GENERATION FROM BALI PROVINCE AND PAPUA PROVINCE ...................................................................................................................................... 32

vi Page 346 of 396

List of Tables Table 2-1. Biomass generated from paddy harvesting (source: APPENDIX E) .............................. 3 Table 2-2. Biomass generated from groundnuts harvesting (source: APPENDIX E) ..................... 4 Table 2-3. Solid biomass production from cassava (source: APPENDIX E) ................................... 5 Table 2-4. Biomass production from maize in Bali and Papua provinces (source:APPENDIX E) 6 Table 2-5. Biomass production from coconut harvesting fruit in Bali and Papua provinces (source: APPENDIX E) .................................................................................................................... 7 Table 2-6. Generation of coffee hulls as biomass waste in Bali and Papua provinces (source: APPENDIX E) .................................................................................................................................... 8 Table 2-7. Cocoa husk production in Bali and Papua provinces (source: APPENDIX E) .............. 9 Table 2-8. Biomass productivity generated from candlenuts harvesting (source: APPENDIX E) .......................................................................................................................................................... 11 Table 2-9. Biomass generated from sugarcane harvesting and processing (source: APPENDIX E) ...................................................................................................................................................... 12 Table 2-10. Biomass from Oil Palm plantation (source: APPENDIX E) .......................................... 14 Table 22-11 Biomass production from rubber tree (source: APPENDIX E) ................................... 15 Table 22-12 Waste potential from various categories of forests (source: Limbah Pemanenan Dan Faktor Eksploitasi Pada Pengusahaan Hutan Tanaman Industri) .................................. 17 Table 22-13 Waste potential from various categories of forests (source: APPENDIX E) ............ 18 Table 22-14 Waste potential from various categories of forests (source: APPENDIX E) ............ 19 Table 22-15 Estimated waste potential from acacia replanting activity ......................................... 20 Table 22-16 Biomass from elephant grass (source: APPENDIX E) ................................................ 20

List of Figures Figure 2-1. Mass balance of tapioca (source: PT Wira Kedaton) ...................................................... 5 Figure 2-2. Types of waste generated from maize (corn) cultivation (source: calculation) .......... 6 Figure 2-3. Wastes from coffee fruit (source: Peluang mendayagunakan Kulit Kopi) ................... 8 Figure 2-4. Parts of candlenuts (source: B.H.Tambunan et.al) ....................................................... 10 Figure 2-5. Schematic sugarcane processing (based on national data), (source: Case Study Indonesian sugar industry) .......................................................................................................... 12 Figure 2-6. Distribution of Oil Palm Biomass (source: Sabri Ahmad et.al 2009) .......................... 13

vii Page 347 of 396

EXECUTIVE SUMMARY The objective of this assignment is to assist Infrastructure Specialist (GIS) for ongoing work on “Geo-enabled Decision Support System (DSS) for National Electrification Program”. The specific tasks of the Assignment are •

Collect Fresh and Dry weight ratio data for broad categories of biomass in Indonesian context

•

Collect yield and heating value of all land use types and categories (agriculture, plantation crops/tree, natural forest tree, etc.) in Indonesia

•

Brief description of types of biomass generator plants available in South and Southeast Asia and one example of each type installed in Indonesia along with their main features.

Study Area is Bali and Papua provinces of Indonesia. The methodological approach is to focus on those residues, which are most dominant in terms of volume in Indonesia. Bali and Papua biomass assessment has been updated using 2014 year data, the most recent available data. The biomass data of Bali province was collected and calculated according to district and village inventories level, while that of Papua was only available at regency level. Resource estimates were derived from Kecamatan Dalam Angka / District in Figure (Bali Province data), and from Kabupaten Dalam Angka /Regency in Figure (Papua Province Data) and Tree Crop Estate Statistics of Indonesia 2013-2015 (Directorate General of Estate Crops, Ministry of Agriculture, 2013-2015 data). The total biomass in the Bali Province is estimated to be about 1.29 million tonnes/year (fresh), while that in the Papua province is around 49.36 million tonnes/year. The biomass considered to be available on a technically sustainable basis is estimated to be 35 million BDTs/year. Of the gross resource, 25 million tonnes are from agriculture, 27 millions from forest resources, and 26 million tonnes from municipal wastes, exclusive of waste in place in landfills and biomass in sewage. The current technical potential includes more than 12 million BDTs/year in agriculture, 14 million BDT/year in forestry, and 9 million BDTs/year in municipal wastes. Dedicated crops are being grown mostly on an experimental basis at present and are not included in the total.

viii Page 348 of 396

Gross electrical generation potential from biomass is currently near 9,900 MWe with more than 2,300 MWe from agriculture, 3,500 MWe from forestry, and 3,900 MWe from municipal solid wastes including landfill and sewage digester gas. The technical resource generating potential is some 4,600 MWe. Biogas potential from animal manures, landfill gas, anaerobic digestion of food, leaves and grass from the current MSW disposal stream, and from waste water treatment plants is estimated to be about 93 billion cubic feet of methane per year.

ix Page 349 of 396

1.

INTRODUCTION

1.1 BIOMASS Biomass is a collective term used for all materials that are biogenic in origin, which is derived from the product of photosynthesis1. Biomass can be of various types, it can have plant origin or animal‐ origin. Classification of biomass resources on the basis of their origin is presented in Figure 2‐1. Mass balance of tapioca. Biomass energy is derived from plant-based material and residues where solar energy has been converted into organic matter. Biomass resources can be broadly classified into the following categories: •

Agricultural crops and residues (rice, corn etc);

•

Plantation crops and residues (sugarcane, oil palm etc.);

•

Dedicated energy crops (herbaceous and tree species);

•

Forestry products and residues;

•

Residues and by products from food, feed, fiber, wood, and materials processing plants [CPO mills, sawdust from sawmills, black liquor (a by product of paper making), and animal manure];

•

Post-consumer residues and wastes, such as fats, greases, oils, construction and demolition wood debris and other urban wood wastes, municipal solid wastes and wastewater, and landfill gases.

1.2 PROJECT OBJECTIVE AND APPROACH This report informs biomass resources potentially available in Bali province and Papua province. The biomass resource estimates are based on either references or assumptions. The results are presented in a tabular for the respective province. For practical reasons this report does not cover all possible biomass types. For instance, aquatic biomass (algae, seaweed, etc.) is not covered in this report, because the potential of this type of biomass is highly uncertain and data availability is scarce. Residues from the food industry are also not covered because they consist of a large variety of different biomass types, for which hardly any national or international resource assessment has been carried out so far. Peat is also excluded, since peat is not a renewable type of biomass within the timeframes relevant for climate and energy policies.

1

http://recap.apctt.org/Docs/Biomass.pdf

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Use of units, conversion factors, etc The biomass potentials will be expressed as its total mass including moisture (tonnes) and as its total net calorific content (kcal or kJ). -

Along with the mass, the average moisture content of the biomass will be expressed on a wet basis.

-

The lower heating value of the biomass resource will be used to calculate the total net calorific content.

1.3 ORGANIZATION OF THIS REPORT This report briefly describes biomass wastes generation from agricultural resources, forest resources and urban resources in Bali province and Papua province. The report is organized as follows: Chapter 1 “Introduction” describes the background, objectives and overall approach to the assignment. Chapter 2 “ Biomass agriculture resources, forest resources and urban resources” Appendix A presents fresh and dry weight ratio of biomass Appendix B presents yield and heating value of biomass Appendix C presents types of biomass generation plants Appendix D presents the terms of reference for this assignment Appendix E biomass waste generation from Bali and Papua provinces

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2.

BIOMASS AGRICULTURE RESOURCES, FOREST RESOURCES, URBAN RESOURCES

2.1

BIOMASS AGRICULTURE RESOURCES

2.1.1 Paddy In 2014, there were totally 13,797,307 ha of land used for rice cultivation in the country, producing 70,846,465 tonnes of rice. The cultivation leaves straw and rice husk as biomass residues. Straw residue is generated at ratio per product of 1 and generation of rice husk is at 25%. These figures are based on the practice of rice harvesting in Indonesia. With a total national production as above, there would be 17,711,616 tonnes rice husk and 35,423,233 tonnes rice straw generated from paddy cultivation. Table below shows estimated rice husk and straw generation in Bali and Papua provinces. Table 2-1. Biomass generated from paddy harvesting (source: APPENDIX E) Biomass Productivity Production Husk Straw Province Area (ha) (tonnes/ha) (tonnes) (tonnes) (tonnes) Husk Straw Bali 874,005 160,127 218,501 874,005 1.36 5.46 Papua 240,527 45,713 23,587 93,755 1.32 5.26 Rice straw is usually left in the rice field and burnt or used as fodder or fertilizer. Rice husk with heating value of 14 MJ/kg (dry basis)2 has been commonly used as fuel for making such as bricks. Taking the total residues from the cultivation, approximately, 2.15 millions GJ energy is generated from the biomass. 2.1.2

Groundnuts

It was reported in the national statistic that the production of groundnuts in the country has reached 638,896 tonnes in 2014, averaging 1.28 tonnes/ha. Three crops could be grown annually (three times groundnut harvest). Of the total production, 20% (127,779 tonnes) is nuts shells at moisture content of 50%. With a calorific value of 16.42 MJ/kg3 this makes up a potential energy of 30.884 GJ from the nuts shells.

2 3

http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf https://www.ecn.nl/phyllis2/Biomass/View/2789

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Table 2-2. Biomass generated from groundnuts harvesting (source: APPENDIX E) Biomass Production Biomass Productivity Province Area (ha) shell (tonnes) (tonnes/ha) (tonnes) Bali 10,221 8,043 1,609 0.25 Papua 2,815 3,656 563 0.15 2.1.3

Cassava

Cassava is not included as solid biomass because the tube is used for producing liquid fuel (bioethanol) while most of the stem is used for establishing new plantation, and the leaves are used as animal fodder4.1 tonne cassava roots will produce around 38% stem and leaves and cassava peels (5%). According to the survey conducted by CDMI consulting,5 the ratio of utilization of cassava by industries to the total national production in 2014 has reached 35%. The following is the mass balance of tapioca starch industry of PT Wira Kedaton; with cassava wastes consisting of solid waste (32 kg cassava pulp 6 per 500 kg cassava processed), and liquid waste with COD of around 15,000 mg/liter (producing 2,867 kg liquid waste per 500 kg processed into tapioca). Distance between plants depends on the varieties to be cultivated and the soil fertility. In monoculture cultivation, 100x100 cm is the common distance with 10,000 plants/ha and is harvested in 8-11 months depending on variety.7

4

https://biomassourlastresource.files.wordpress.com/2012/03/d1‐03‐biomass‐resource‐in‐indonesia‐2011‐itb‐final‐pdf‐bambang‐ prastowo.pdf (Paper is presented in the German‐Indonesia Workshop on Biomass: Our Last Resource, Defining Sustainable Policies and Management of Indonesia s Biomass Utilization, 26 September 2011 Institute Technology of Bandung, Biomass Resource in Indonesia:Indonesia s Solid Biomass Energy Potential, Bambang Prastowo, Indonesian Center for Estate Crops Research and Development) 5 http://www.cdmione.com/source/Tapioka2015.pdf 6 7

Traditionally known as onggok http://tanamanpangan.pertanian.go.id/files/PednisUbik_2012.pdf

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Table 2-3. Solid biomass production from cassava (source: APPENDIX E) Biomass Cassava Total biomass Peels Province Production Area (ha) Stem & leaves productivity (tonnes) (tonnes/ha) (tonnes) (tonnes) 130,281 32,777

Bali Papua

8,357 4,466

49,507 12,455

6,514 1,639

6.72 3.16

Figure 2-1. Mass balance of tapioca (source: PT Wira Kedaton)8

2.1.4

Maize

Indonesia accounted for a production of maize (corn) of 19 million tonnes in 2014 (Badan Pusat Statistik/Statistics Indonesia, 2014).9 The mass balance of solid wastes generated from producing maize grain is given in , showing amount of husk of 15/20 tonne maize grain produced, and so as for the cobs as other waste generated. Table 2-4 shows biomass production per ha in both provinces. 8 9

Data from PT Wirakencana Kedaton Factory and Tulangbawang Factory (Lampung Province) http://www.bps.go.id/Brs/view/id/1122 (www.bps.go.id/website/brs_ind/brsInd‐20150302130203.pdf)

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Table 2-4. Biomass production from maize in Bali and Papua provinces (source:APPENDIX E) Province Production (tonnes) Bali Papua

30,960 8,590

Area (ha) 17,474 4,480

Cobs Husk Stalk Leaves (tonnes) (tonnes) (tonnes) (tonnes) 23,220 6,443

23,220 6,443

46.440 12,885

30,960 8,590

Total biomass productivity (tonnes/ha) 7.09 7.67

Although there is a high energy potential from maize cob, the utilization of maize residue for electricity generation would still face some barriers such as its scattered production area and the low bulk density of corn. As a result, the transportation cost to collect the product may be expensive. For the purpose of biomass assessment, technical and economic potential of maize cob and stove will not be further discussed. Figure 2-2. Types of waste generated from maize (corn) cultivation (source: calculation)10

10

Calculation

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2.1.5

Coconut

Coconut cultivation in Indonesia was reported to have tree population between 130 – 180 trees/ha.11 Wood, fronds, husks and shells are common types of residues generated from coconut cultivation and consumption. Assumed that 12 fronds are shed per tree/year throughout the year with 1.5 kg dry woody biomass/frond, this results in 2.34 tonnes dry biomass/ha (based on tree population of 130 trees/ha.12 Fronds are left in the field or used as a domestic fuel by smallholder farmers. Tall coconut starts to produce fruit at age 6 – 7 years. Dwarf coconut at 3-4 years, and hybrid at 4-5 years. A hybrid coconut produces 120 fruits/tree/ha in average. The average productive life of coconuts in Indonesia varies up to 50 years depending of the coconut variant. Replanting is reported through gradual annual cutting of 20% old coconut tree as the most recommended option. Replanting is suggested for coconut plant of older than 50 years.13 Tree trunks are commonly used as fuel and as timber. Taking the assumption as given in the reference that an average coconut tree trunk is 590 kg/tree (12 m tall with diameter of 30 cm), there would be 76.7 tonnes tree trunk biomass /ha. Biomass wastes from coconuts fruit are husks (fiber) 28% and shell 15%. This indicates that 21,757 tonnes husks and 11,655 tonnes dry shells were generated in Bali province in 2014, as seen in the following table. Table 2-5. Biomass production from coconut harvesting fruit in Bali and Papua provinces (source: APPENDIX E) Biomass production Production Area Fiber Shell (tonnes/ha) Province (tonnes) (ha) (tonnes) (tonnes) Fiber Shell Bali 77,703 73,012 21,757 11,655 0.3 0.16 Papua 10,959 20,572 3,068 1,644 0.15 0.08 Husks are used such as domestic fuel, for coconut processing or filling of mattresses. Meanwhile, the shells are being used as domestic fuel and preparation of activated carbon. From those biomass, 26,222 TJ and 93,341 TJ energy is potentially generated from coconut cultivation in Papua and Bali province respectively.

11 12

http://Hutanb2011.blogspot.co.id/2013/06/agribisnis‐komoditi‐tanaman‐kelapa.html

http://www.fao.org/deocrep/006/AD576E/ad576e00.pdf 13 http://www.ejournal.litbang.pertanian.go.id/index.php/psp/article/download/2929/2556

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2.1.6

Coffee

Coffee processing will generate waste in the form of coffee hulls. The following figure shows the percentage of waste generation from coffee processing.

Figure 2-3. Wastes from coffee fruit (source: Peluang mendayagunakan Kulit Kopi)14

Fresh coffee fruit consists of 54.5% coffee bean, 28.7% coffee pulp, 11.9% coffee hulls and 4.9% mucilage. Based on the statistic data, biomass wastes generated in these provinces are given in the next table. Table 2-6. Generation of coffee hulls as biomass waste in Bali and Papua provinces (source: APPENDIX E) Production Hulls Biomass Productivity Province Area (ha) (tonnes) (tonnes) (tonnes/ha) Bali 12,364 28,970 2,699.7 0.09 Papua 1,604 9,138 350.2 0.04 Coffee husk have a calorific value of 18.34 MJ/kg (Moisture Content 6.7%)15. The productive life of coffee tree varies in the range of 30-40 years and it starts to bear fruits (mature plant) after around 2.5-3 years.

14

Peluang Mendayagunakan Kulit Kopi Sebagai Bahan Pakan Dalam Sistem Integrasi Tanaman ternak Ruminansia 15 http://www.hindawi.com/journals/isrn/2014/196103/tab3/

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There are a number of coffee varieties of Arabica and Robusta cultivated in the country, varies in an average productivity of 800 – 1,700 kg/ha/year and population variation of 1,600 – 2,000 trees/ha, depending on the varieties.16 It is suggested from a reference that cultivation of coffee with a tree population of 1,600 per hectare, and thus this figure is adopted in this report.17 No information is available on the actual residues generated during pruning activities in the country. An estimate of 1-5 MT/ha/year biomass residues, based on a reference value, was made for the biomass resulted due to pruning activity.18

2.1.7 Cocoa According to the Indonesian statistic, the cacao production in Bali and Papua provinces is presented in Table 2-7. Table 2-7. Cocoa husk production in Bali and Papua provinces (source: APPENDIX E) Pod Pruning Replanting Biomass Production Area Province husk (tonnes) (tonnes) Productivity (tonnes) (ha) (tonnes) (tonnes/ha) Bali 356,454 3,259 6,891 14,145 6,361 0.45 Papua 438,908 4,013 6,826 17,417 6,301 0.36 Cacao cultivation would generate wastes due to fruit harvesting, pruning activity and replanting. Harvesting cocoa beans from cocoa fruits will produce cocoa pod husk of approximately 48%of the total fruit harvested, which is normally disposed at the plantation for fertilizer. The average productive life of cacao tree is 20-25 years during which regular pruning is required. Cocoa plantation generates wastes from pruning process, replanting and fruit harvesting. 1. Pruning (throughout the year): Trees have to be pruned regularly to keep them at acceptable size, cutting cocoa trees through pruning activity is assumed to result in 25.2 tonne dry biomass/ha/year (generating branches, twigs, leaves).19 2. Replanting:20 16 17

http://Iccri.net/bahan‐tanam‐kopi/

http://web.ipb.ac.id/‐tepfteta/elearning/media/Teknik%20Pasca%Panen/tep440_files/Pengolahankopi.htm (web.ipb.ac.id/~usmanahmad/Pengolahankopi.htm) 18 https://www.hort.purdue.edu/newcrop/duke_energy/Coffea_arabica.html#Energy 19 https://cdm.unfccc.int/filestorage/E/9/B/E9BNZ5TOP4QWJVKC3X0S72D6LFYU1A/Biomass%20Assessment_supporting%20Appn.7?t=TX B8bzBoZW40fDBc9AZMy5kEyf‐qK77BWwzr

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Replanting involves replacing non-productive or old trees after 25 years. As there is no official value on biomass generation from this activity, it is estimated as 45.76 dry tonnes/ha of biomass generated from replanting. It is assumed that the tree trunk has calorific value of 18 MJ/kg. 3. Harvesting: dry cocoa pod husk (calorific value 17 MJ/kg) 21 is generated at 48% while cocoa bean is produced at 52% of the fruit.

2.1.8

Candlenuts (Aleurites moluccana (L.) Wild)

Based on the national statistic 2015, candlenut production in the country was 107,300 tonnes22. A dry nut could have weight in the range of 8-14 gram/nut. Each kilogram of candlenuts seed will produce 30% hazelnut core and 70% shell.23 Figure 2-4. Parts of candlenuts (source: B.H.Tambunan et.al)24

Candlenut tree could have reached a height between 15 -25 m.25 It is reported that the trees at age of 24.5 years could have an average diameter of 46.9 and 25.2 m height.26 Candlenut tree has high productivity between 11-35 years. A 15 years old candlenut tree is reported able to produce 1,000 - 2,000 nuts or in average 20 kg/tree/year27. Tree could still

20 21 22

assumed occurs every 25 years, producing 48 kg dry biomass

http://www.jpe‐ces.ugm.ac.id/ojs/index.php/JML/article/view/246/182 http://www.bps.go.id/linkTabelStatis/view/id/1670

23

http://isomase.org/JOMAse/Vol.9%20Jul%202014/9‐3.pdf

24


25 26 27

www.jurnalasia.com/2014/02/19/15803/ https://www.cifor.org/publications/pdf_files/Books?BKrisnawati1107.pdf http://balittro.litbang.pertanian.go.id/ind/images/file/Perkembangan%20TRO/edsusvol18no2/1KEMIRI.pdf

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produce nuts at 70 years, but only producing 8 kg peeled nuts/year. At this age a candlenut tree could have reached a diameter of 110 cm.28 In Hawai, candlenuts trees are cultivated with a population in the range of 200 – 300 trees/ha. In Indonesia it is cultivated in various tree spacing, depending on the objective of the cultivation; for multi culture / agroforestry (spacing 6 x 6 m or 8 x 8 m), monoculture (spacing 3 x 3 m or 4 x 4 m), for pulp wood production (4 x 4 m), for candlenut oil production (10 x 10 m). Biomass from candlenuts cultivation could be obtained from the shells and tree trunk from replanting activity. Taking the residue to product ratio of 2.33, biomass from shell of approximately 0.71 tonnes/ha and 2.33 tonnes/ha could be produced in Papua province and Bali province respectively. The tree of 30 years were reported to have an average volume 432 m3/ha (assuming average tree density of 310 kg/m3, moisture content 15%). For high nuts productivity, replanting period of 20 years could be assumed for the tree.29 Table 2-8. Biomass productivity generated from candlenuts harvesting (source: APPENDIX E) Replanting Production Area Shell Biomass Productivity Province Trunk (tonnes) (ha) (tonnes) (tonnes/ha) (tonnes) Bali 5,892 1 44 2.33 0.05 Papua 27,721 63 207 147 0.71 2.1.9

Sugarcane

Sugarcane cultivation generates wastes in the form of cane tops (leaves) and bagasse and sugar molasses from the processing of sugarcane. Residue generated from harvesting sugarcane is sugarcane tops and leaves (average value 12.6 MJ/kg, moisture content 30%).30

28


29 30

https://www.cifor.org/publications/pdf_files/Books?BKrisnawati1107.pdf

http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf

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About 30-33% wt of sugarcane processed would be land at the end of the process as solid residue (fresh bagasse, Moisture content 50%, calorific value 7.7 MJ/kg).31 The sugarcane processing yield in the country is approximately 7%-8%. Table 2-9. Biomass generated from sugarcane harvesting and processing (source: APPENDIX E) Biomass Productivity Tops & National/ Production Area Bagasse (tonnes/ha/year) leaves Province (tonnes) (ha) (tonnes/ha) Bagasse (tonnes/ha) Cane tops & leaves Indonesia 2,728,393 487,095 23.6 1.19 24.55 (National) Bali 0 0 Papua 2 56 0.012 0.001 0.012 At sugarcane production of 2 tonnes in 2014, Papua produced only 0.66 tonnes baggase/year. This corresponds to potential energy of approximately 3 GJ. Currently, bagasse has been used by most sugar mills as fuel for sugarcane processing. Considering the residues above, sugarcane cultivation has generated a potential energy of 15 GJ in that year from bagasse and sugarcane top and leaves.

Figure 2-5. Schematic sugarcane processing (based on national data), (source: Case Study Indonesian sugar industry)32 1 ha area of sugar plantation Haytop (1.34 t/y)

Imbibition water 80 t/y Sugar cane

Chemicals

Mill station

Purification station

Bagasse 2400 Kg of Bagasse

Cooking White and Evaporation Sugar Centrifuge station station 4800-5600 Kg Sugar

Filter Cake (Blotong)

Molasses

8000 kWh

31 32

http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf Case Study Indonesian sugar industry

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2.1.10 Oil Palm wastes As shown in Figure 2-6, every hectare of oil palm plantation shall result in approximately 74.48 tonnes (dw) of oil palm trunks, 14.47 tonnes (dw)33 of oil palm fronds during replanting, 10.40 tonnes/ha on annual pruning, 10.59 tonnes (dw) of empty fruit bunch (EFB) waste, 1,626 kg (dw) of mesocarp fiber, and 938 kg (dw) of palm kernel shells. All of these solid wastes contain energy that can be recovered by combustion in a boiler. In addition, each tonne of FFB processed results in around 0.6 m3 of palm oil mill effluent (POME). Total number of trees planted per hectare varies for each oil palm plantation company. A range of 125–135 trees planted per hectare is the most utilized, based on feedback given by PTPN III. One hectare of oil palm plantation will yield the following biomass after felling: 1) Oil Palm Trunk: Dry weight approx. 75 tonnes/ha, with a tree density of 125-- 135 palms /ha 2) Oil Palm Fronds: a. Felling: 14.47 tonnes/ha (dry weight) b. Annual pruning during productive life: 10.4 tonnes/ha (dry weight) Figure 2-6. Distribution of Oil Palm Biomass (source: Sabri Ahmad et.al 2009)34

33 34

dw=dry weight

Sabri Ahmad and Choo Yuen May, “Next Generation Biofuels:Malaysian Experience”, International Conference on Green Industry in Asia, Manila, Philippines, 9‐11 September 2009 (http://www.unido.org/fileadmin/user_media/UNIDO_Header_Site/Subsites/Green_Industry_Asia_Conference_Manila_/Biofuel_Malayis a.ppt)

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Table 2-10. Biomass from Oil Palm plantation (source: APPENDIX E) National/ Province

CPO Production (tonnes)

Area (ha)

National Bali Papua

30,948,931 0 76,857

11,444,808 0 55,944

Biomass waste from processing (ton/ha) 4.43 2.40

Biomass waste from plantation area (tonnes) 143,407,865 701,000

Biomass Production (tonnes/ha) 17.25 14.93

2.2 BIOMASS FOREST RESOURCES 2.2.1

Rubber wood

Indonesia has becoming the second-largest rubber producer worldwide, which supplies a substantial amount of rubber to the international market. According to data from the Ministry of Agriculture (Directorate General of Estate Crops), the total natural rubber production in 2015 amounted to 3.2 million tonnes, which produced from 3.6 million ha plantations scattered across Indonesia.35 The product from such plantation is in the form of latex. About 85% of the total production is exported (Indonesia Investment).36 Rubber wood has a calorific value of about 15 MJ/kg at moisture content of 20%, with estimated wood density of 0.6 tonne/m3. Rubber plantations in the country are managed by small holders (farmers), private companies or the state company (Badan Usaha Milik Negara/BUMN, The Government owned State Company). About 80% of Indonesia’s rubber production is accounted for by small holders (farmers). Rubber plantations managed by smallholders are mostly located in Sumatera and Kalimantan islands, while that managed by private company are in Sumatera and Java (totally 488 companies). The average period of effective yield of rubber trees in Indonesia is 25 years (around 20-30 years). As a result, 3-4% of the rubber plantation area must be replanted every year after cutting the trees due to aging. For this purpose, old trees must be felled. Wood residue is sourced from replanting of rubber trees after the trees 30 years. In this report, it is assumed that the waste generation is 3% of the total area of rubber plantation.

35 36

http://ditjenbun.pertanian.go.id/tinymcpuk/gambar/file/statistik/2015/KARET%202013%20‐2015.pdf http://www.indonesia‐investments.com/id/bisnis/komoditas/karet/item185

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Biomass production from rubber plantation is shown in Figure 4. Per hectare of rubber plantation area will produce about 180 m3. Based on the research from two rubber plantations in Subang (West Java) and Cilacap (Central Java), it followed that for every hectare of rubber plantation will produce dry rubber wood (ready for fire wood) of at least 100 tonne/ha. The total wood product from the rubber plantation above, therefore, is around 10 million tonnes/year. Wood resulted from rubber tree cutting composes of 40% large wood log (diameter of over 10 cm) and 60% smaller wood log (or 108 m3). Large wood log has a good economical value, used for building material or commercial firewood. The remaining 60% wood log is in the form of pieces of tree branches, which are generally less or not utilized, thereby they are technically potential for use as energy source. Other potential waste is from sawmill, with totally 70% of the processed rubber wood log (70% x 40% x 180 m3/ha = 50.4 m3/ha). The total waste from rubber trees processing is thus 158.4 m3/ha or 95 tonne/ha. Replanting process that takes place every 25 years, further contributes 0.91 tonnes /ha and 1.94 tonnes/ha from sawmilling wastes and branches (including twigs etc.) respectively in Bali province. Calculating the 25 years between replanting, the potential of energy is 24,571 GJ/year and 434,209 GJ/year in Bali province and Papua province respectively. Table 22-11 Biomass production from rubber tree (source: APPENDIX E) Province Bali Papua

Area (ha) 551 9,737

Total biomass sawmilling (tonnes) 499.6 8,829

Total branches, twigs etc. (tonnes) 1,070.6 18,919

Biomass Productivity (tonnes/ha) 2.85 2.85

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Figure 2.2- 1 Balance of rubber wood waste (source: Production Potential of Rubberwood in Malaysia)37

2.2.2 Forest residues Waste generated from forest logging is distinguished in timber cutting waste, skidding or yarding waste, hauling waste and transportation waste. Timber waste is divided in two sources: a. Logging waste in forest, that is waste generated due to logging b. Processing wood waste, that is waste generated due to wood industry activities such as sawmill, furniture processing etc.

Forest logging Timber logging consists of a series of activities including transferring wood from forest to a processing plant through timber cutting activities, skidding or yarding (transferring logs from timber cutting area (cutting lot) to a temporary wood collecting area at the road side, transportation and grading.

37

Production Potential of Rubberwood in Malaysia: Its Economic Challenges

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Logging wastes, according to the Government Regulation of Indonesia No.59 of 1998, are timber wastes generated from allowed felling, that are not or has not yet been utilized in the form of trimming of stems, stumps, twigs, shoots with a diameter of less than 30 cm or a length of less than 1.30 m. The result of research on waste potential to some exploitation of natural forest and industrial plantation forest in Indonesia is as in the following table. Table 22-12 Waste potential from various categories of forests (source: Limbah Pemanenan Dan Faktor Eksploitasi Pada Pengusahaan Hutan Tanaman Industri)38 Kind of forest Location; Researcher; Year Waste potential Natural forest 23 HPH in 9 provinces; Simarmata & 23,6% Sastrodimedjo; 1980 South Kalimantan; Sugiri; 1981 East Kalimantan; Widiananto; 1981 Laut Island, South Kalimantanl; Sianturi 1982 PT Medang Kerang Jaya, West Kalimantan; Thaib; 1990 8 areal HPH di Central Kalimantan and South Kalimantan; Dulsalam; 1990 PT Austral Byna MuaraTeweh, Central Kalimantan; Butarbutar; 1991 PT Narkata Rimba, East Kalimantan; Sukanda; 1995 PT Suka Jaya Makmur, West Kalimantan; Muhdi; 2001

HutanTanaman Industri/ Forest plantation

HutanTanaman Industri/ Forest plantation

HPH PT Sumalindo Lestari Jaya II; Sasmita; 2003 South Kalimantan; Hidayat; 2000 HPHTI Kayu Pertukangan BKPH Cikeusik, KPH Banten; Gustian; 2004 HPHTI Kayu Pertukangan BKPH Gunung Kencana, KPH Banten; Safitri; 2004 PT INHUTANI II, Pulau Laut, South Kalimantan; Rawenda; 2004 PT INHUTANI II, Pulau Laut, South Kalimantan; Kartika; 2004 HPHTI PT Musi Hutan Persada, South Sumatera; Rishadi; 2004

51% 39,9% 20,4% 1,55 m3/tree 5,61 m3/tree for conventional logging techniques 4,51 m3/tree for low-impact logging techniques 114,304 m3/ha 86.46 m3/ha 13,704 m3/ha for conventional logging techniques 11,059 m3/ha for low-impact logging techniques 3.80% (26.28 m3/ha ) 17.6% 16,8% (60.12 m3/ha) 21% 10,583% (27,456 m3/ha) 23.268% 29.32 m3/ha

38 Limbah Pemanenan Dan Faktor Eksploitasi Pada Pengusahaan Hutan Tanaman Industri 17 Page 366 of 396

In this report, it is assumed that timber waste comes from production forest which is periodically harvested every 5 year. The amount of timber waste is calculated as follow: Timber waste = 29.32 m3/ha x 0.866 t/m3 x production forest area (ha): 5. When the production of log is known, logging waste is calculated as follow: Logging waste is 21% of that processed logs, while the log production is 79%. Therefore, logging waste = 21/79 x log production x 0.866 tonne/m3. Table 22-13 Waste potential from various categories of forests (source: APPENDIX E) Biomass biomass timber logging Biomass Productivity Province Area (ha) felling waste waste (tonnes/ha) (tonnes) (tonnes) Bali Papua 32,429,487 8,829 18,919 2.85

Sawmilling industry The average rendement (yield) from sawmilling is 50%, available in various types and sizes of planks and wood beam. Based on processed logs, for example, from 1 million m3/year, around 0.5 million m3/year of waste will be generated in the form of pieces of planks, tree bark, beam discharged, small pieces and sawdust (estimated to be about 15% of the total waste). Utilization of wood waste generated by sawmill differ from one place to another. But in general, not all waste can be utilized appropriately. Each sawmill always leaves about 50% of the waste or about 0.25 million m3/year, which has to be destroyed by incineration or landfilling. Wood waste from sawmilling industry is calculating as follow: 50% x sawn timber (m3) x 0.866 tonnes/m3. Therefore, the total logging waste and processing of wood waste: [(21/79 x logs production (log) x 0.866 tonnes/m3) + (50% x sawn timber (m3) x 0.866 tonnes/m3)] tonnes/year.

18 Page 367 of 396

Table 22-14 Waste potential from various categories of forests (source: APPENDIX E) Total biomass Biomass Productivity Province Area (ha) sawmilling (tonnes/ha) (tonnes) Bali Papua 32,429,487 8,829 2.85 2.2.5

Logging residue of Acacia Mangium (Case at PT. Tanjung Enim Lestari)

Acacia mangium is a fast-growing plant with a yield of about 200-250 m3/ha in year five. Such plants can be harvested at the age of 5 years. Using the conversion from tonne to m3, where 1 m3 = 0.866 tonnes (PT. Musi Hutan Persada). Harvesting waste generated at HTI Pulp is 24.09 m3/ha which consists of felling waste of 3.47 m3/ha, skidding waste of 2.59 m3/ha, loading/landings waste of 1.48 m3/ha and transportation waste of 16.56 m3/ha. The percentage of waste harvesting activities at HTI Pulp is 10.5 % of the total potential utilized which consists of felling waste 1.7 %, 1.3 % skidding waste, waste of landings 0.9 % and the transportation waste 6.6 %. Acacia mangium residues are generated from felling residue in the form of stems, stumps, twigs and branches that are mostly left in the forest. In the industrial processing, common wastes available are in the form of logs and pieces and dominated by sawdust. The average weight of acacia wood at age 5 is 133.1 tonnes/ha or 178.66 kg/tree (the number of trees at age 5 is 745 trees/ha). Approximately 30 % will be in the form of waste. Waste of timber harvesting in the Government Regulation of the Republic of Indonesia No. 59 of 1998 is a timber that is not or has not been utilized on activities that involves allowed tree cutting (felling), in the form of stems trimming, stumps, twigs, shoots which have a diameter of less than 30 cm or length less than 1.3 m. Thus, calculated acacia felling residue: 178.66 kg / tree x 30 % x number of trees : 5

19 Page 368 of 396

Table 22-15 Estimated waste potential from acacia replanting activity (source: APPENDIX E) Province

Number trees

Biomass production39 (tonnes/year)

Biomass Productivity (tonnes/ha/year)

534 4,728

5.72 50.68

7.99 7.99

Bali Papua

2.2.6

Elephant Grass (Rumput Gajah/Pennisetum purpureum)

The growth and production of Elephant grass are greatly varies in Indonesia, depending on fertilization, location, rainfall and other factors. High productivity of the grass could produce various weight of fresh elephant grass weight, in the range of 21.4 tonnes/ha - 525 tonnes/ha. In this report, the elephant grass productivity is assumed to be 21.4 tonnes (fresh)/ha/year. Typical yield in the range 25-35 oven dry tonnes per hectare annually (equals to 100 boe/ha). The grass could be harvested up to four times within a year. Elephant grass has an average moisture content of 75% with a calorific value of 18.1 MJ/kg. Therefore, the biomass produced from elephant grass is estimated equals to 491.6 TJ. Table 22-16 Biomass from elephant grass (source: APPENDIX E) Province

Forest area (ha)

Biomass waste production (tonnes/year)

Biomass Production (tonnes/ha/year)

Papua

5,138

109,953

21.40

2.3 BIOMASS URBAN RESOURCES 2.3.1

Municipal Solid Waste

MSW is the waste generated by sectors such as residential, commercial, industrial, and institutional. The major biomass components in MSW are food, vegetable waste and paper. There are four main types of MSW management: landfilling, incineration, composting and anaerobic digestion. On average, a waste generation rate is 0.76 kg/day/person or 3.68 liters/day/person of solid waste. Thus, with total population 4,104,90040 the waste generation of urban area of Bali is 39 40

In the form of stem trimmed, stumps, twigs, shoots, etc www.bappeda.baliprov.go.id/files/subdomain/bappeda/file/BUKU%20Bali%20MEMBANGUN%20TAHUN%202014.pdf

20 Page 369 of 396

estimated at 3,119.7 tonnes/day of MSW. Biomass fraction in the MSW is a resource that can be converted to electricity, heat gaseous and liquid fuels through thermo-chemical (incineration, pyrolisis, and gasification), and bio-chemical (anaerobic digestion and fermentation) conversion processes. Volume of MSW generation varies among cities in Bali province (2012); Denpasar (1,904 m3/day), Badung Regency (1.151 m3/day), Buleleng (322 m3/day), Gianyar (415 m3/day), Tabanan (331 m3/day), Jembrana (281 m3/day), Klungkung (150 m3/day), Karangasem (120 m3/day) and Bangli (124 m3/day)41.

41

www.bappeda.baliprov.go.id/files/subdomain/bappeda/file/RPJMD%20TAHUN%202013‐2018/BAB%20IV_RPJMD_Final.pdf

21 Page 370 of 396

APPENDIX A: FRESH AND DRY WEIGHT RATIO OF BIOMASS Bali province Biomass Types

Fresh & Dry Production Weight Ratio (t/ha) (%)

Rice Rice husk Rice Straw Corn Cobs Husk Sugarcane Bagasse Coconut Shell Fiber Cocoa Shell Candlenut Shell Cassava Stem/leaves Peanuts

1.36 5.46 1.33 1.33 23.36 0.16 0.30 0.45 0.06 5.94

Shell 0.25 Coffee Hulls 0.09 Palm Oil PKS 0.63 MF 1.27 EFB 2.53 POME 6.90 Trunks 11.92 Leaves 41.34 Rubber wood Waste wood 2.85 Production Forest

Moisture content (%)

Fresh weight

dry weight

116% 385%

14%42 74%43

100 100

86 26

1.25 2.00

20%44 50%45

100 100

80 50

2.00

50%

100

50

1.09 1.43

8% 30%

100 100

92 70

1.19

16%

100

84

1.11

10%46

100

90.5

3.31

70%47

100

30

125%

20%

100

80

107%

6.7%

100

93.3

118% 167% 286%

15% 40% 65%

100 100 100

85 60 35

400% 286%

75% 65%

100 100

25 35

188%

47%

100

53

42

https://core.ac.uk/display/11704441 (eprints.undip.ac.id/3376/1/MAKALAH_KARAKTERISTIK_PENGERINGAN_GABAH.pdf (by Ahmad MH Winata and Rachmat Prasetiyo)) 43 Balitnak.litbang.pertanian.go.id/phocadownload/JITV/litkayasa/ptek99‐18.pdf 44

http://renewables.morris.umn.edu/biomass/documents/Zych‐ViabilityOfCornCobsAsABioenergyFeedstock.pdf

45

http://renewables.morris.umn.edu/biomass/documents/Zych‐ViabilityOfCornCobsAsABioenergyFeedstock.pdf Daron Zych: Biomass Research Intern, WCROC – University of Minnesota, Viability of Corn Cobs as a Bioenergy Feedstock. 46 http://isomase.org/JOMAse/Vol.9%20Jul%202014/9‐3.pdf 47

Pelletforbundet.se/wp‐content/uploads/2015/01/RAPPORT‐2014‐Kassava‐som‐additiv‐vid‐pelletering‐av‐biobränsle.pdf (Oscar Lockneus)

22 Page 371 of 396

Biomass Types Wood waste Acacia Felling waste Grass land Elephant grass

Fresh & Dry Production Weight Ratio (t/ha) (%)


Fresh weight

dry weight

5.08

220%

55%

100

45

7.99

118%

15%

100

85

21.4

417%

76%48

100

24

Papua province Fresh & Dry Weight Ratio (%)


Fresh weight

dry weight

0.52 2.05

116% 385%

14% 74%

100 100

86 26

1.59 1.59

1.25 2.00

20% 50%

100 100

80 50

0.012 0.001

2.00 1.43

50% 30%

100 100

50 70

0.08 0.15

1.09 1.43

8% 30%

100 100

92 70

0.36

1.19

16%

100

83.9

0.71

1.11

10%

100

90.46

2.80

3.31

70%

100

30.2

0.15

125%

20%

100

80

0.04

107%

6.7%

100

93

0.38 0.93 1.51

118% 167% 286%

15% 40% 65%

100 100 100

85 60 35

Production (t/ha) Paddy Rice husk Rice straw Maize Cob Husk Sugarcane Bagasse Tops & Leaves Coconut Shell Fiber Cocoa Pod husk Candlenuts Shell Cassava Stem & leaves Groundnuts Shell Coffee Husks Palm Oil PKS MF EFB 48

Balitnak.litbang.pertanian.go.id/phocadownload/JITV/litkayasa/ptek99‐18.pdf (Lokakarya Fungsional Non Peneliti 1999: "KONVERSI DATA HASIL ANALISIS PROKSIMAT KEDALAM BAHAN SEGAR", Balai Penelitian Ternak, Po Box 221, Bogor 16002)

23 Page 372 of 396

Fresh & Dry Weight Ratio (%)


Fresh weight

dry weight

4.12 11.93 41.34

400% 286%

75% 65%

100 100

25 35

2.85

188%

47%

100

53

5.10

220%

55%

100

45

7.99

118%

15%

100

85

21.4

417%

76%

100

24

Production (t/ha) POME Trunks Leaves (Frond) Rubber wood Wood waste Production Forest Wood waste Acacia Felling waste Grass land Elephant grass

24 Page 373 of 396

APPENDIX B: YIELD AND HEATING VALUE OF BIOMASS Yield and Heating Value •

Residuals from Agriculture/Plantation Residual Content of total Production (%)

Products

Yield (t/ha)

Rice

6.82 (Bali) 6.58 (Papua)

25% (husk) 100% (straw)

14.0 (husk, at MC 12%)49 11.7 (straw, at MC 50%)50

7.09 (Bali) 7.67 (Papua)

15% (cobs) 15% (husk) 20% (leaves) 30% (stalk)

14.6 (cob, at MC 14%)51 10.5 (husk, stalk, leaves, at MC 40%)52

Maize

Sugarcane

Coconut

Cocoa

Candlenut Cassava

24.55 (National) 0.012 (Papua) 0.46 (Bali) 0.23 (Papua) 0.45(Bali) 0.36 (Papua) 0.05 (Bali) 0.71 (Papua) 6.7(Bali) 3.16 (Papua)

Heating Value (MJ/Kg)

33% (bagasse) 7.7 (bagasse, at MC 50%)53 1.68% (hay top 12.6 (hay top cane, at MC cane) 30%)54 19 (fiber, at MC 10%)55 18 (shell, at MC 13%)56 18(Fronds)57 18(trunk, at MC 11%)58 17 (cocoa pod husk, at MC 48% (cocoa pod 16.1%)59 husk) 18 (pruning, wood‐ replanting)60

15% (shell) 28% (fiber)

70% (shell)61

21.96 (shell) 62

38% (stem/leaves) 5% (peels

17.4 (stem, at MC 15%)63 4.97 (peels, at MC 70.4%)64

49

http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf 51 http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf 52 http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf 53 http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf 54 http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf 50

55 56 57 58

http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value)

http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value)

59

http://www.jpe‐ces.ugm.ac.id/ojs/index.php/JML/article/view/246/182 http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) 61 http://isomase.org/JOMAse/Vol.9%20Jul%202014/9‐3.pdf 60

62 63 64

http://www.jpe‐ces.ugm.ac.id/ojs/index.php/JML/article/view/246/182 http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) www.inderscienceonline.com/doi/abs/10.1504/IJTEM.2015.068414

25 Page 374 of 396

0.16 (Bali) 0.15 (Papua) 0.09(Bali) 0.04 (Papua)

Groundnut Coffee

4.43 (Bali) 2.25 (Papua)

Palm oil

20% (shell)

16.42 (shell, at MC 8%)65

11.9% (husk) EFB = 22% FFB67Fiber = 13.5% FFB (1.626 tons/ha) Shells= 5.5% FFB

18.34 (husk, at MC 6.7%)66 5 (EFB, at MC 45%)68 14 (Fiber, at MC 30%)69 18 (Shell, at MC 15%)70

•

Plantation Biomass Types

Annual production (t/ha)

Palm Oil (branches, dead tree, etc.)

18.2 (pruning and replanting)

Rubber (branches, twigs, etc.) Coffee (branches, twigs, etc.)

Coconut (branches, twigs, etc.)

Cocoa (branches, twigs, etc.)

Candlenut (branches, twigs, etc.) Cassava (branches, twigs, etc.)

2.85 (Bali, Papua, from sawmilling & branches, twigs etc) 2.52 (Bali, Papua, from pruning) 79.04 (Bali, trunk & fronds‐replanting) 79.04 (Papua, trunk & fronds‐replanting) 25.7 (Bali, pruning and replanting)

Heating Value (MJ/Kg) 14 (Palm fronds, MC 20%)71 15 (Palm trunks, MC 20%)72 18 (wood, replanting)73 Not available 18 (fronds)74 18 (trunk)75 18 (pruning)76

18 (trunk 25.6 (Papua, pruning and replanting, dry)77 replanting)

134 (Bali, Papua, assumed as replanting‐trunk) wood 5.92 (Bali, stem& leaves) 17.5 (stem &

65

https://www.ecn.nl/phyllis2/Biomass/View/2789 http://www.hindawi.com/journals/isrn/2014/196103/tab3/ 67 EFB=Empty Fruit Bunch, FFB=Fresh Fruit Bunch 66

68 69 70


http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf

71 72


http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf 73 http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) 74 http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) 75 http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) 76 http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value) 77 http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value)

26 Page 375 of 396

2.79 (Papua, stem & leaves)78 leaves) Acacia (branches, twigs, etc.)

20.1‐20.579

7.99 (Bali, Papua)

Biomass Types

Production at Maturity (t/ha)

Maturity (Yr.)

3 (trunk, dry weight) Palm Oil Tree

25‐30

0.4 (fronds, felling) 15 (fronds, pruning)

Rubber Tree

Acacia Tree

•

Heating Value (MJ/Kg) 14 (Palm fronds, MC 20%)80 15 (Palm trunks, MC 20%)

95 ton/ha (total wastes from logging and sawmilling) 15 (wood at MC 20‐30 180 m3/ha (108 20%) ton/ha, total wood harvested) 5‐8 ( for pulp wood ) 133.1 tonnes/ha x 81 15‐20 (for sawn 30% (Felling residues, 20.1‐20.5 after year 5) timber)

Others Land use and Biomass type

Annual production (t/ha)

Heating Value (MJ/Kg)

Agricultural waste Elephant Grass (pennisetum purpureum) Natural forest (waste – leaves, branches, etc.)

21.4

18.1 75%)82

Natural forest (timber)

1.52

Municipal solid waste

(MC

78

http://www.nrel.gov/docs/fy09osti/44808pdf (heating value is LHV /Low Heating Value)

79

http://www.cifor.org/publications/pdf_files/Books/BCIFOR1105.pdf http://www.cifor.org/publications/pdf_files/Books/BKrisnawati1101.pdf 80 http://calculator2050.esdm.go.id/assets/mini_paper/bioenergi/id/Panduan%20Pengguna%20untuk%20Sektor%20Bioenergi.pdf 81

http://www.cifor.org/publications/pdf_files/Books/BCIFOR1105.pdf http://www.cifor.org/publications/pdf_files/Books/BKrisnawati1101.pdf 82 https://www.ncsu.edu/bioresources/BioRes_10/BioRes_10_4_6457_Mohammed_AKYAC_Pyolysis_Napier_Grass_Fixed_Bed_Reactor_7 443.pdf

27 Page 376 of 396

APPENDIX C: TYPES OF BIOMASS GENERATORS PLANTS a.

Gasification – usually used for small capacity for mini-grid Until recently, there is still no gasification power plant supplying electricity to the national electricity grid..Generally, it is used for own consumption, both in industries or for local grid. Biomass consumption depends on feedstock types and moisture content. The following is an example of biomass consumption for rice husk gasification with a 400 kW in Wonosobo, Central Java, Indonesia. Biomass consumption: 1.1 ~ 2.0kg/kWh (Biomass feedstock: < 20% Moisture content in particle form)

b.

Steam – usually used for large capacity for industrial complex In Indonesia, steam generated from biomass is commonly used in Palm oil mill, sugar mill, particle board plant, dll Biomass consumption for sugar mill factory (case of PT Gunung Madu Plantation, 2005) is as in the following: Sugarcane milled Total bagasse production Steam per ton cane KWh per ton cane

Ton Ton Ton/Ton KWh/Ton

1,849,068 613,617.45 0.46 22.55

Biomass consumption at PT. Murini Samsam Palm Oil Mill: For the mill, fuel used is palm kernel shell (PK shell) and mesocarp fiber/MB. Fuel consumption is: 4.5 tonnes of steam per MWh; 0.25 tonne PK Shell per tonne steam Own Consumption of PK - Shell and Fiber for Palm Oil Mill Net Calorific Value Fiber = 2710 kcal/MT = 11.35 GJ/tonne Net Calorific Value PK Shell = 4120 kcal/MT = 17.35 GJ/tonne 1 MT Fiber is equivalent to 0.65 MT PK Shell (caloric value) Consumption of PK - Shell for Turbine 1 KWh requires 4.5 Kg Steam 1 MT Steam requires 250 Kg PK Shell Power Use for Turbine = 67,977,600 kWh/year

28 Page 377 of 396

PK Shell Use for Turbine = 67,977,600 kWh/year x 4.5 Kg/1,000 x 250 Kg/1,000 = 76,475 MT/year Consumption of PK - Shell for Steam Boiler for Oil Production 1 MT Steam = 250 Kg PK Shell 280,000 MT Steam/year x 250 Kg/1,000 = 70,000 MT/year c.

Case study of the existing EFB fired Co-generation in Pabatu Power Plant (PTPN IV), North Sumatera In Pabatu palm oil mill (POM), two factories are existed, the Pabatu POM and Pabatu PKOM (Palm Kerneil Oil Mill). The steam for electricity generation and factory processing in the Pabatu POM is generated by boiler using fiber and shell as fuel. Formerly, the electricity demand of about 2.3 MW in the PKOM was supplied by diesel generator. Since the subsidy of heavy fuel was deleted, the cost for operating the diesel generation increased. To reduce the cost, the management had decided to utilize EFB as fuel for biomass power plant to substitute the diesel power generation. Based on a common accepted material balance, solid wastes produced from a POM is as follows: EFB: 13.8 t/hr Fiber: 10.8 t/hr PKS: 4.2 t/hr Pre-treatment Before being fed into a furnace, EFB is dewatered by double press, mono press and is shredded. A heated screw conveyor is used to increase the dryness level of EFB. However, after this treatment, the moisture content is still greater than 50%. A Stoker Boiler of Takuma N-600-SA is designed for fuelled with biomass with moisture of 40%. This type of boiler is not designed for EFB fuel. Biomass Power Plant Operation In order to define energy balance in the power plant, the efficiency of boiler, turbine and generator should be defined, by reference. Actual data is not obtained, as the data is not publicly available. All solid wastes (MKF/fiber, PKS/shell and EFB) produced from CPO (Crude Palm Oil) processing is used by the boiler of the Pabatu Power Plant (PP) to generate 3 MW electricity and also used by the power generation in the Pabatu POM to generate electricity and steam processes in the POM at a capacity of 60 t-FFB/hr. All fiber is used for boiler fuel in Pabatu POM 29

Page 378 of 396

and all EFB is used for the fuel in Pabatu PP. Partly of the shells is used as in both boiler of Pabatu POM and Pabatu PP. The amount of solid waste is calculated according to the general material balance as presented in the following Figure. Flow Process in Pabatu Biomass PP

FFB Steam Capacity: 3 MW Steam Turbine PKO factory: 2.3 MW Lighting and etc.

13.8 t EFB/h 1.05 t PKS/h

3.1 t PKS/h

Feed water

10.8 t fiber/h

steam

Electricity

Pabatu Palm Oil Mill 60 t/h

Cooling Tower

Stoker Boiler Takuma N-600 SA

Condensor

Steam

Boiler Pabatu POM

Steam Turbine

In order to increase calorie value of fuel, higher calorie of shell is fed into furnace when the temperature of furnace is down. All solid waste is owned by the factory, there is no cost for fuel purchase in this case. Generated electricity is supplied to Palm Kernel Factory having demand of 2.3 MW. The remaining electricity is used to lighting etc.

30 Page 379 of 396

APPENDIX D: TERMS OF REFERENCE TERMS OF REFERENCE •

Title of the Work: Biomass Resource Assessment Consultant (Local)

•

Input/ Assignment duration: 10 person-days/ intermittent – starting from last week of Nov to 25 Dec 2015

•

Objective of the Assignment The objective of this assignment is to assist Infrastructure Specialist (GIS) for ongoing work on “Geo-enabled Decision Support System (DSS) for National Electrification Program”.

•

Study Area Bali and Papua provinces of Indonesia; Bali detailed and Papua preliminary analysis. As much detail as possible is desired, but it is understood the level of detail of the data may be limited by the ability to compile the data within the time available.

•

Specific Tasks The consultant will work under Infrastructure Specialist (GIS) supervision. The specific tasks are • • •

•

Deliverables • • •

•

Collect Fresh and Dry weight ratio data for broad categories of biomass in Indonesian context (ref Annex Table 1) Collect yield and heating value of all land use types and categories (agriculture, plantation crops/tree, natural forest tree, etc.) in Indonesia (ref Annex Table 2) Brief description of types of biomass generator plants available in South and Southeast Asia and one example of each type installed in Indonesia along with their main features.

Collected data in tabular (XLS format) and reports in Microsoft word and/or PDF format mentioned in above task Metadata of collected data and Brief report

Qualifications The Consultants should have following qualifications and expertise • University degree in Agriculture, Forestry, Natural Resource Management or related filed. • Specific training or work experience in Biomass Resource Assessment and Renewable Energy for electrification 31

Page 380 of 396

APPENDIX :

Bali Province Rice

No 1 2 3 4 5 6 7 8 9

Regency Jembrana Tabanan Badung Gianyar Klungkung Bangli Karangasem Buleleng Denpasar Bali Province

Area (Ha) GKG (t) 9,363 32,576 16,955 29,713 5,655 5,254 35,738 21,693 3,270 160,217

65,710 211,940 107,970 193,982 32,061 28,276 66,399 143,134 24,534 874,005

Maize

Rice Husk Corn grain (t) Straw (t) Area (Ha) (t) Cobs (t) Husk (t) 16,427 65,710 85 352 264 52,985 211,940 644 2,316 1,737 26,992 107,970 367 1,201 901 48,496 193,982 577 752 564 8,015 32,061 2,705 9,407 7,039 7,069 28,276 437 2,599 1,949 16,600 66,399 6,569 11,022 8,267 35,783 143,134 5,643 3,310 2,483 6,133 24,534 447 218,501 874,005 17,474 30,960 23,204

Sugarcane

264 1,737 901 564 7,039 1,949 8,267 2,483 23,204

Sugar cane Bagasse Area (Ha) (t) (t) -

Coconut

Hay top cane (t) -

Blotong (t) -

Area (Ha) Coconut (t) Shell (t) Fiber (t) 17,595 15,501 2,325 4,340 14,445 14,536 2,180 4,070 2,471 1,585 238 444 4,138 3,749 562 1,050 3,293 5,428 814 1,520 2,939 7,326 1,099 2,051 17,933 14,940 2,241 4,183 10,198 14,638 2,196 4,099 73,012 77,703 11,655 21,757

Page 381 of 396

Bali Province Cocoa

No 1 2 3 4 5 6 7 8 9


Area (Ha) Cocoa (t) Shell (t) 5,587 2,849 2,630 4,240 2,595 2,396 566 146 135 227 141 130 55 61 57 258 289 267 1,066 237 219 2,147 571 527 14,145 6,891 6,361

Candlenut

Candlenut Candlenut Cassava Stem/leav Area (Ha) (t) shell (t) Area (Ha) Roots (t) es (t) 109 2,544 970 178 1,626 620 1,325 16,403 6,254 360 6,192 2,361 44 1 2 5,750 89,444 34,100 635 14,072 5,365 44 1 2 8,357 130,281 49,669

Cassava Peanuts Cassava usage ratio of the total national production by Wastewater Cassava the industry of Onggok (COD: 15000 Peanuts Peanuts Peel (t) tapioca (t) ppm) Area (Ha) (t) shell (t) 0.35 181 249 50 0.35 38 11 2 127 0.35 57 5,106 582 901 180 81 0.35 36 3,263 96 164 28 820 0.35 367 32,919 2,084 1,678 336 310 0.35 139 12,426 493 773 155 4,472 0.35 2,004 179,505 3,800 4,143 829 704 0.35 315 28,241 769 2,303 461 0.35 6,514 0.35 2,918 261,460 8,043 10,221 2,040

Page 382 of 396

Bali Province Coffee

Area (Ha) Coffee (t) No 1 2 3 4 5 6 7 8 9


1,189 10,655 1,813 361 87 566 826 13,474 28,970

283 4,471 439 219 57 484 494 5,917 12,364

Palm Oil

Coffee hulls (t)

62 976 96 48 13 106 108 1,292 2,700

Area (Ha) FFB (t)

-

PKS (t)

-

-

Rubberwood

MF (t)

EFB (t)

-

-

POME (m3)

-

Forest

Grassland

Wood Total Total Productio waste of Acacia Total Area biomass biomass Total Area n forest production Acacia wood Forest Elephant Area (Ha) (m3) waste (t) Forest (Ha) (Ha) forest (t) (Trees) waste (t) (Ha) grass (t) 551 2,975 1,571 43,624 2,993 15,201 534 6 9,969 3,091 33 1,780 7,716 83 1,116 5,667 7,265 78 5,333 41,448 444 9,916 453 2,300 4,322 46 14,260 4,598 23,350 71,078 762 41,472 200 1,016 2,893 31 735 4 0 551 2,975 1,571 127,089 9,360 47,534 138,351 1,483 -

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Bali Province Biomass Types

Fresh & Dry Moisture Weight content (%) Ratio (%)

Production (t/ha)

Rice Rice husk Straw Corn Cobs Husk Sugarcane Bagasse Top canes Coconut Shell Fiber Cocoa Shell Candlenut Shell Cassava Stem/leaves Peanuts Shell Coffee Hulls Palm Oil PKS MF EFB POME Trunks Leaves (Frond) Rubberwood wood waste Production Forest Wood waste Acacia Felling waste Grass land Elephant grass

Fresh weight

dry weight

1.36 5.46

116% 385%

14% 74%

100 100

86 26

1.33 1.33

1.25 2.00

20% 50%

100 100

80 50

2.00 1.43

50% 30%

100 100

50 70

0.16 0.30

1.09 1.43

8% 30%

100 100

92 70

0.45

1.19

16%

100

83.9

0.06

1.11

10%

100

90.46

5.94

3.31

70%

100

30.2

0.25

125%

20%

100

80

0.09

107%

7%

100

93

118% 167% 286%

15% 40% 65%

100 100 100

85 60 35

400% 286%

75% 65%

100 100

25 35

2.85

100%

0%

100

100

5.08

100%

0%

100

100

7.99

118%

15%

100

85

385%

74%

100

26

#REF! #REF!

#REF! #REF! -

21.4

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Papua Province Rice

No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Regency Merauke Jayawijaya Jayapura Nabire Kepulauan Yapen Biak Numfor Paniai Puncak Jaya Mimika Boven Digoel Mappi Asmat Yahukimo Pegunungan Bintang Tolikara Sarmi Keerom Waropen Supiori Mamberamo Raya Nduga Lanny Jaya Mamberamo Tengah Yalimo Puncak Dogiyai Intan Jaya Deiyai Kota Jayapura Papua Province

Area (Ha) GKG (t) 39,191 205,452 392 594 859 3,379 1,532 6,321 90 120 8,968 2,537 100 50 406 1,426 29 87 321 764 321 764 59 154 2 4 20 88 1,219 4,138 45 196 0 1 1,126 5,486 45,713 240,527

Maize

Sugarcane

Rice Husk Corn grain Sugar Bagasse Hay top Blotong Straw (t) Area (Ha) (t) Cobs (t) Husk (t) Area (Ha) cane (t) (t) (t) cane (t) (t) 14,670 58,679 311 95 738 738 52 297 594 211 253 190 190 845 3,379 559 1,328 996 996 1,580 6,321 408 1,023 767 767 4 2 1 0 0 30 120 519 1,298 974 974 2,242 8,968 224 538 403 403 634 2,537 265 629 472 472 13 50 6 15 11 11 357 1,426 280 633 475 475 22 87 191 764 70 145 109 109 191 764 8 6 6 112 266 200 200 38 154 201 409 306 306 1 4 495 88 66 66 22 88 88 95 71 71 1,034 4,138 319 899 674 674 6 15 11 11 12 20 15 15 49 196 3 7 5 5 0 1 108 178 133 133 1,372 5,486 283 649 487 487 23,587 93,755 4,480 8,590 7,110 7,110 56 2 0.66 0.034 0

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Papua Province Coconut

No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29


Area (Ha) 6,651 2,213 1,025 503 3,723 1,004 456 75 40 3,631 424 810 17 20,572

Cocoa

Candlenut

Coconut Pod husk Candlenut Candlenut Shell (t) Fiber (t) Area (Ha) Cocoa (t) Area (Ha) (t) (t) (t) shell (t) 567 85 159 207 63 147 1,158 174 324 3,106 466 870 3,173 2,900 2,677 1,939 291 543 1,714 913 843 988 148 277 510 45 42 875 131 245 41 5 5 45 7 13 65 10 18 120 18 34 25 5 5 1,185 178 332 3,220 775 715 467 70 131 7,754 1,860 1,717 435 65 122 980 322 297 1 0 0 8 1 2 10,959 1,644 3,068 17,417 6,826 6,301 207 63 147

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Papua Province Cassava

No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29


Area (Ha) 312 64 140 559 234 281 4 170 22 321 135 209 1,385 50 95 114 24 249 98 4,466

Cassava Stem/leav Cassava Roots (t) es (t) Peel (t) 2,843 1,084 142 320 122 16 5,098 1,944 255 4,476 1,706 224 2,808 1,071 140 3,431 1,308 172 1,438 548 72 5 2 0 1,723 657 86 96 37 5 1,648 628 82 2,040 778 102 171 65 9 610 233 31 1,330 507 67 85 32 4 211 80 11 3,661 1,396 183 784 299 39 32,777 12,496 1,639

Peanuts Coffee Cassava usage Wastewat ratio of Area (Ha) Coffee (t) the total er (COD: Peanuts Peanuts national Onggok 15000 Area (Ha) (t) productio (t) ppm) shell (t) 0.35 10 874 56 164 33 71 16 0.35 7 642 51 43 9 2,906 200 0.35 213 222 44 0.35 114 10,231 187 202 40 0.35 100 8,982 356 421 84 188 57 0.35 63 5,635 31 27 5 150 1 0.35 77 6,886 195 203 41 1,410 152 0.35 9 78 16 0.35 32 2,886 87 105 21 31 1 0.35 0 11 18 4 1 0.35 39 3,458 28 21 4 0.35 2 193 0.35 37 3,307 180 186 37 1,610 625 0.35 46 4,094 140 499 100 725 45 0.35 4 342 1,565 81 16 386 53 0.35 14 1,224 29 31 6 0.35 30 2,669 64 77 15 20 0.35 2 171 7 8 2 427 50 0.35 5 423 2 1 0 30 2 0.35 0.35 126 17 0.35 889 375 0.35 10 0.35 10 0.35 82 7,347 358 339 68 1 0 0.35 0.35 22 0.35 127 10 0.35 18 1,573 81 105 21 0.35 680 60,949 3,656 2,815 563 9,138 1,604

Coffee hulls (t)

3 44 12 0 33 0 136 10 11 11 0 4 82 0 2 350

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Papua Province Palm Oil

Area (Ha) FFB (t) No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29


38,149 17,795 55,944

384,284 384,284

PKS (t)

21,136 21,136

MF (t)

51,878 51,878

Rubberwood

EFB (t)

84,542 84,542

POME (m3)

230,570 230,570

Area (Ha) 3,261 599 2,811 3,047 19 9,737

Total Total Production biomass biomass Total Area (m3) waste (t) Forest (Ha) forest (Ha) 17,609 9,298 4,713,842 157,084 1,537,892 647,357 1,201,456 3,234 1,708 243,275 114,796 226,126 94,876 516,494 53,592 504,305 207,958 2,262,091 969,451 15,179 8,015 2,727,799 16,454 8,688 2,661,189 1,580,534 103 54 2,314,419 959,922 1,475,332 497,025 1,659,875 520,457 604,086 113,357 1,417,611 819,084 942,160 509,999 680,892 405,411 71,380 2,671,947 1,290,318 646,840 101,278 354,738 68,410 338,954 44,411 361,118 57,794 534,014 85,169 448,388 109,451 931,093 368,519 130,508 3,277 94,579 52,580 27,762 32,429,487 9,622,446

Forest

Grassland

Wood waste Acacia Total Area of Elephant production Acacia wood Forest forest (t) (Trees) waste (t) (Ha) grass (t) 97,409 1,075 12 2,357 85 1 3,287,424 123 1 33,311 495 5 582,960 5,000 107,000 481,801 222 2 272,152 2,490 27 1,056,057 4,923,089 31,746 8,026,306 4,874,699 2,524,004 2,642,997 106 1 575,652 4,159,492 2,589,891 2,058,768 8,638 6,552,524 514,312 347,401 225,529 293,491 432,507 555,817 10 0 1,871,422 16,641 1,039 122 1 138 2,953 49,039,439 4,728 51 5,138 109,953

Page 388 of 396

Fresh & Dry Production Moisture Fresh Weight Ratio (t/ha) content (%) weight (%) Paddy rice husk rice straw Maize Cob Husk Sugarcane bagasse Tops & Leaves Coconut Shell Fiber Cocoa Pod husk Candlenuts Shell Cassava stem & leaves Groundnuts shell Coffee Hulls Palm Oil PKS MF EFB POME Trunks Leaves (Frond) Rubberwood wood waste Production Forest Wood waste Acacia Felling waste Grass land Elephant grass

dry weight

0.52 2.05

116% 385%

14% 74%

100 100

86 26

1.59 1.59

125% 200%

20% 50%

100 100

80 50

0.012 0.001

200% 143%

50% 30%

100 100

50 70

0.08 0.15

109% 143%

8% 30%

100 100

92 70

0.36

119%

16%

100

83.9

0.71

111%

10%

100

90.46

2.80

331%

70%

100

30

0.15

125%

20%

100

80

0.04

107%

6.7%

100

93

0.38 0.93 1.51 4.12 11.93 41.34

118% 167% 286% 100% 400% 286%

15% 40% 65%

100 100 100

85 60 35

75% 65%

100 100

25 35

2.85

188%

47%

100

53

5.10

220%

55%

100

45

118%

15%

100

85

417%

76%

100

24

7.99 21.4

Page 389 of 396

8.

INPUTS TO THE GEOSPATIAL DECISION SUPPORT SYSTEM OF THE CENTER OF EXCELLENCE


December 2015

Page 390 of 396

Analysis to Support Development of a National Electrification Program Objectives of this program: 1. Identify target regions for electrification efforts. 2. Provide the following inputs for electrification policy and program development: a. Selection of electrification technology by region (e.g. grid extension, off‐grid community systems, off‐grid individual household systems); and b. Estimation of investment required. This information will be used to support the development of institutional arrangements (including business models) and funding mechanisms for electrification. For example, this analysis will determine for each region the extent of and investment required in off‐grid solutions as well as PLN grid extension to achieve the Government’s electrification targets. The following timetable is proposed: Completion of Stage 1 by 9 November 2015 Completion of Stage 2 for 2 to 4 regions by 1 February 2016 Completion of Stage 2 for other regions to continue through 2016 Stage 3 to be conducted by region by parties responsible for electrification in each area (grid or off‐grid) as determined by the Stage 2 results and institutional arrangements to be developed based on Stage 2 Stage

1

Description Regional targeting. Using desa‐level data, this step will identify the portions of the country with the lowest electrification ratios and highest numbers of unserved households. These areas can then be prioritized for more detailed analysis under Stage 2.

Level

National

Data Required Base map 250.000 Population by desa Electrification ratio by desa and supply (PLN vs. non‐PLN) Desa boundaries

Source of Data BIG BPS/Kemendagri PLN

BPS

Output A map/GIS of Indonesia showing electrification and population by desa.

Page 391 of 396

2

3

Regional planning. For low‐electrification regions that have been prioritized under Stage 1, Network Planner or similar model will be used to estimate the mix of electrification technologies and investment required by technology type for each region. This entails the following steps: Identification of settlements based on BIG maps or satellite imagery; Estimation of population by settlement based on allocation of desa population; Identification of electrified areas based on PLN 20 kV line Regional corridors Estimation of demand by settlement in settlements outside of 20 kV corridors Clustering of these settlements according to proximity criteria (maximum distance of LV reticulation between settlements) and preparation of associated .shp files. Characterization of cost and performance of electrification technology options Population and economic growth forecasts Data entry into Network Planner and running of the model. Implementation Planning. This stage entails the detailed design of systems to supply electricity in the target area, including the identification of the specific households to be electrified and the location of the supply infrastructure. Examples of this analysis Settlement will be prepared as guidance for parties that will be responsible for implementation planning in each respective area, based on the institutional arrangements developed based on Stage 2 findings.

Stage 1 data Base map 25.000 20 kV line locations Potential power demand by settlement Generator Resources High resolution imagery (as available) Technology Options Technology costs & performance

Stage 1 and 2 data Base map 10.000 Demand Mobile coverage area High resolution imagery

Stage 1 BIG PLN Derived from PLN and other field 1. Estimates of data investment PLN/ESDM required by Landsat/Google technology by region to achieve PLN & market electrification PLN & market targets 2. Identification of areas for off‐grid concessions

Stages 1 and 2 BIG BPS / Survey questionnaire BTS provider Google/Ikonos/ Quick Bird

Identification of households to be electrified and specification and placement of supply infrastructure to be installed

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Figure 1. SIEP (CoE) interface. The results of the SIEP (CoE) project will be accessible online with a prototype of its interface (portal) as in the picture 1 above. There is information about analysis to Support Development of a National Electrification Program. The program will provide access to advanced technical assistance by means WebGIS as a tool for analytics and planning systems. There are 3 stages in the implementation of this program. Stage 1 to the national level covering the whole province as shown in figure 2 below. Results was completed from province until ‘Desa’ level as a smallest unit administration boundary

Page 393 of 396

Figure 2. National level as a stage 1 covering country level. Figure 3 shown as a result of Stage 2 (provincial level), which is the districts area where the pilot for this stage is the island of Bali (completed), district Wamena in Papua (on going) and the island of Sumba (completed).

Figure 3. Provincial level as a stage 2

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Stage 3 is the implementation level of the village for settlements that do not have electricity and to be conducted by region by parties responsible for electrification in each area (grid or off‐grid) as determined by the Stage 2 results and institutional arrangements to be developed based on Stage 2. Figure 4 shown results electrification by systems (grid or off grid) in particular area (Nusa penida island, Bali). Figure 5 shown WebGIS interface could be used for roof top tagging as tools for off grid PLTS planning and analysis. Sample of Desa Tawui, Sumba Timur area.

Figure 4. Implementation level, stage 3 sample results of electrification in particular area (grid or off‐ grid).

Page 395 of 396

Figure 5. Implementation level, stage 3 sample results in particular area, roof top tagging for off‐grid

Page 396 of 396

ADB TA 8287-INO: Scaling Up Renewable Energy Access in Eastern Indonesia Final Report

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