ADICA Training Report - JICA WASP 2007

ADICA CONSULTING, LLC 2021 Midwest Road, Suite 200 Telephone: +1 (630) 705-3060 Oak Brook, IL 60523 USA Facsimile: +1 (630) 705-3061

Website: www.adica.com Email: [email protected]

Training Report Presented to:

Japan International Cooperation Agency (JICA), and

PT Indokoei International, Jakarta, Indonesia for:

Intensive Training on Generation Planning using WASP-IV organized at APJ PLN Bogor, Indonesia, during 22 January – 2 February 2007

2 February 2007

Submitted by:

ADICA Consulting, LLC The Ultimate in Strategic Analysis

Table of Contents

1. EXECUTIVE SUMMARY .................................................................................................3 2. SCOPE OF THE TRAINING..............................................................................................3 3. FACILITIES, WORKING CONDITIONS AND PARTICIPATION.................................6 4. TRAINING STAFF .............................................................................................................6 5. CONCLUSIONS AND RECOMMENDATIONS ..............................................................7 6. ANNEX I - TRAINING SCHEDULE...............................................................................9 7. ANNEX II - TRAINEE PRESENTATIONS OF WASP-IV REFERENCE CASES FOR

INDONESIA......................................................................................................................12

Intensive Training on Generation Planning using WASP-IV

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1. EXECUTIVE SUMMARY Nineteen staff of the national electricity company PT. PLN (Persero) were trained on how to apply the Wien Automatic System Planning (WASP) Package for determining the power generating system expansion plan that meets demand at minimum cost while satisfying user-specified constraints for the electricity system in Indonesia. The course participants were also guided through the development of a WASP Reference Case and several Sensitivity Analysis Cases using country specific data from Indonesia. The training was completed in accordance with the agreed schedule from 22 January until 2 February 2007. Upon completion of the training, the course staff provided the trainees a copy of the lectures presented, WASP cases developed during the course, as well as various support material to be further used for actual WASP studies and for energy planning activities in general. 2. SCOPE OF THE TRAINING Objectives of the Training The main objective of the assignment was to train PLN staff on the use of the WASP-IV software for conducting power generating system expansion planning in Indonesia. Presentation of WASP Methodology WASP is the most well-known and widely used optimization model for examining medium- to long-term expansion options for electrical generating systems. National electric power utilities and electricity regulation agencies in many countries, as well as The World Bank and other international institutions and organizations, regularly use WASP to help examine long-term generation expansion plans. Nowadays, over 90 countries and 12 international organizations use WASP. The most recent version of the software, WASP-IV, includes additional features compared to the previous version, namely the calculation of environmental emissions associated with electricity generation and the possibility of imposing development limitations related to the use of various types of fuels, the electricity generation and the environmental emissions by different power plants. These new features allow a very accurate modeling of particular constraints existent in various countries including Indonesia. The WASP methodology utilizes probabilistic simulation for estimating power generating system production costs, unserved energy costs, and reliability, linear programming technique for determining optimal dispatch policy satisfying the user-specified constraints on fuel availability, electricity generation, and environmental emissions by groups of plants, and the dynamic programming method of optimization for comparing the costs of alternative system expansion policies. The WASP computer program includes the following modules (Figure 1): LOADSY (Load System Description), processes information describing electric load for the power system over the study period.


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FIXSYS (Fixed System Description), processes information describing the existing generation system and any predetermined additions or retirements, as well as information on any constraints imposed by the user on environmental emissions, fuel availability or electricity generation by some plants. VARSYS (Variable System Description), processes information describing the various generating plants which are to be considered as candidates for expanding the generation system. CONGEN (Configuration Generator), calculates all possible year-to-year combinations of expansion candidate additions which satisfy certain input constraints and which in combination with the fixed system can satisfy the annual loads. CONGEN also calculates the basic economic loading order of the combined list of FIXSYS and VARSYS plants. MERSIM (Merge and Simulate), considers all configurations put forward by CONGEN and uses probabilistic simulation of system operation to calculate the electricity generation by each plant and associated production costs, energy-not-served and system reliability for each configuration. In the process, any limitations imposed on some groups of plants for their environmental emissions, fuel availability or electricity generation are also taken into account. The dispatching of plants is determined in such a way that plant availability, maintenance requirement, spinning reserve requirements and all the group-limitations are satisfied with minimum cost. DYNPRO (Dynamic Programming Optimization), determines the optimum expansion plan based on previously derived operating costs along with input information on capital costs, energy-not-served cost and economic parameters and reliability criteria.

Figure 1 Modular Structure of WASP-IV Computer Software


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REPROBAT (Report Writer of WASP in a Batched Environment), writes a report summarizing the total or partial results for the optimum or near optimum power system expansion plan and for fixed expansion schedules. The modular structure of WASP-IV permits the user to monitor intermediate results, avoiding waste of large amounts of computer time due to input data errors. The information from one module is passed to the subsequent modules through binary files. Each module also produces its own printable output, which can be viewed on display or printed by the user to detect input data errors.

Organization of a Two-week Training Course on WASP-IV ADICA Consulting, LLC partnered with PT Indokoei International in organizing a 2-week training course on the most recent version of the WASP software for 19 participants from PLN. The training schedule is provided in Annex I while the list of participants is given in Annex II. The training consisted of 18 lectures on the principles of power system expansion planning and use of the WASP-IV software, as well as work sessions to apply the software for analyzing six power generating systems in Indonesia. The course participants received assistance for the installation of the WASP-IV software on their own computers, creation/deletion/back-up/restoration of system expansion cases and on the use of all mod The following expansion cases were analyzed for the Indonesian power generating system:

1. Java Bali 2. Kalbar – West Kalimantan 3. Kaltim & Kalselteng – East, South and Central Kalimantan 4. Sumatera 5. Sulselrabar – South, Southeast and West Sulawesi 6. Suluttenggo – North and Central Sulawesi

For each expansion case, a team comprised of two to five trainees prepared a “Reference Case” to assess the least cost generation expansion plan during the period 2007-2026, using country specific data for the electric load and existing generating system description, as well as for expansion candidates (e.g., coal, combined cycle, geothermal, hydro). For additional expansion candidates (e.g., nuclear power) for which country specific data were not available, the technical and economic parameters provided as input data for WASP were assessed on the basis of international references. The trainees also performed “Sensitivity Analysis” to assess the influence on the optimal expansion plan of possible future changes in the main WASP-IV input parameters, e.g., Economic Information (fuel prices, investment cost, O&M cost), Economic Parameters (discount rates, escalation rates), and Level of Quality of Supply (reserve margins, LOLP constraints, and ENS cost.


6

During the execution of this task, the course staff advised participants on how to use the WASP software in order to find the least cost expansion plans for the above-mentioned cases, and rectify problems that were encountered while running the software. ADICA provided each participant a CD containing lectures presented at the course, the input data and results of the WASP cases developed by the course participants and additional support files to be used in the future energy and electricity planning activities. 3. FACILITIES, WORKING CONDITIONS AND PARTICIPATION The training was organized at the APJ PLN office in Bogor, Indonesia, which provided an excellent venue for the course. The administrative staff from PT Indokoei and PLN did an excellent job in preparing the training facilities; were responsive to the evolving needs during the course; and provided daily logistical oversight, support and guidance. The course staff is very impressed with the performance of the course participants. The group performed exceptionally well and exhibited:

1. Strong capability and commitment to learning, 2. High level of attention throughout the course, 3. Quick understanding of new concepts, 4. Natural ability and interest to work together in discussing generation planning

concepts, sharing experience and developing best solutions, and 5. Focus on obtaining knowledge and skills necessary to provide decision-making

support for Senior Management. The leadership and support of Senior Management from PLN and JICA also contributed greatly to the success of this training event. 4. TRAINING STAFF The training was carried out by two international consultants with extensive experience in the use of the WASP software for generation expansion planning, including: Bruce Hamilton President, ADICA Consulting LLC Mr. Hamilton has an extensive background in the development of advanced computing techniques and analysis of energy systems, including the leadership he provided for energy and environmental projects conducted, in more than twenty countries, for the World Bank, USDOE, and International Atomic Energy Agency (IAEA). Mr. Hamilton's previous position was as Head of the Energy Modeling, Databanks and Capacity Building Unit at the IAEA, where he directed multi-disciplinary teams in the development of technology databases and analytical software (including WASP-IV), and conduct of technical assistance projects focused on energy sector development and environmental assessment. Mr. Hamilton


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organized regional projects in Africa, Asia & the South Pacific, Europe, Latin America, and West Asia to address energy/electricity planning needs of developing countries. As a course director and lecturer, he trained over 500 experts from 40 countries in the areas of demand forecasting, electricity system expansion planning, energy policy analysis and strategy development, environmental assessment, and financial analysis of energy options. In recent years, he led training and analysis activities for power sector restructuring and electricity market analysis studies in Europe, Asia and the South Pacific. Mladen Zeljko Department Head, Energy Generation and Conversion Energy Institute “Hrvoje Požar” (EIHP), Zagreb, Croatia Dr. Zeljko manages a department at EIHP that is responsible for research into problems of power system expansion, deregulation in the electricity market, system development and operation planning within a competitive environment. He is among the most experienced users of the IAEA’s WASP-IV software and is regularly recruited by the IAEA to serve as an invited expert for technical assistance missions and training courses on the use of this software. In August 2002, Mr. Zeljko joined with staff from ADICA Consulting in organizing a two-week training course on WASP-IV for Tenaga Nasional Berhad, in Malaysia. 6. CONCLUSIONS AND RECOMMENDATIONS We believe that the Intensive Training on Generation Planning using WASP-IV was successfully completed. With the trainees’ strong effort, they developed a good understanding of the WASP-IV functionality and successfully produced initial model results. However, it is necessary for the course participants to gain additional experience by following-up the training with real work in applying WASP-IV for an actual study. With the above comments in mind, we offer the following recommendations for consideration by PLN:

1. The energy planning staff in Indonesia should collect and enter into WASP improved technical, economic and environmental data for existing units and expansion candidates.

2. An Indonesian WASP Users Meeting should be organized annually. If desired, the meeting could be made open to other WASP users from the region (e.g., Malaysia, Korea).

3. Additional training should be organized for energy planning staff at PLN on the following subjects: a. Energy Demand Forecasting using the MAED software, b. Electricity System Operation and Pricing using the GTMax software, c. Environmental Analysis, and d. Energy Project Finance.


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We would like to thank JICA and PLN for the opportunity to collaborate in this training event. We appreciate the strong effort by the course participants, excellent working conditions, superb logistical support from Indokoei, and gracious hospitality from all. It has been a pleasure working together. We are proud of our joint success and look forward to our continued collaboration.

Sincerely yours, Bruce P. Hamilton President, ADICA Consulting LLC


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ANNEX I

Training Schedule


10

WASP-IV TRAINING (Week 1)

Time Monday

22 January Tuesday

23 January Wednesday 24 January

Thursday 25 January

Friday 26 January

09:00 - 10:30

CCOOUURRSSEE OOPPEENNIINNGG

Welcome / Introductions and Discussion of Course

Objectives

LLEECCTTUURREE 33

Real world applications of

WASP-IV

LLEECCTTUURREE 66

VARSYS module of WASP-IV

LLEECCTTUURREE 88

CONGEN module of WASP-IV

LLEECCTTUURREE 1111

DYNPRO module of WASP-IV

10:30 - 10:45 Break

10:45 - 12:15

LLEECCTTUURREE 11

Overview of WASP-IV generation system expansion planning

model

LLEECCTTUURREE 44

LOADSY module of WASP-IV

WWOORRKK SSEESSSSIIOONN

Input data preparation and execution of VARSYS


Input data preparation and execution of

CONGEN



MERSIM & REPROBAT

12:15 - 13:45 Lunch Break

13:45 – 15:15

LLEECCTTUURREE 22

Overview of WASP-IV User Interface

LLEECCTTUURREE 55

FIXSYS module of WASP-IV

LLEECCTTUURREE 77

Developing a Fixed Expansion Case in WASP

LLEECCTTUURREE 99

Probabilistic Simulation


Review of Teams’ Fixed Expansion Results

15:15 – 15:30 Break

15:30 – 17:00

CCoouurrssee PPaarrttiicciippaanntt PPrreesseennttaattiioonn

Overview of electricity system in Indonesia

(present situation and future prospects)



LOADSY & FIXSYS


Developing a Fixed Expansion Case in WASP

LLEECCTTUURREE 1100

MERSIM module of WASP-IV


Review of Teams’ Fixed Expansion Results

(continued)


11

WASP-IV TRAINING (Week 2)

Time Monday

29 January Tuesday

30 January Wednesday 31 January

Thursday 1 February

Friday 2 February

09:00 - 10:30

LLEECCTTUURREE 1122

Pumped-Storage Representation

LLEECCTTUURREE 1144

Developing an optimal expansion strategy with

WASP-IV

LLEECCTTUURREE 1166

Special unit representation in

WASP-IV

LLEECCTTUURREE 1188

Generation Expansion Planning in an Open

Electricity Market


Preparation of Participant Teams’ Presentation of

Optimal Solution Results

10:30 - 10:45 Break

10:45 - 12:15

LLEECCTTUURREE 1133

REPROBAT module of WASP-IV


Developing an optimal expansion strategy in

WASP-IV



WASP-IV



WASP-IV

PPRREESSEENNTTAATTIIOONN

Course Participant Teams’ Presentation of

WASP-IV Optimal Solution Results

12:15 - 13:45 Lunch Break

13:45 – 15:15


Input data preparation for DYNPRO

LLEECCTTUURREE 1155

Use of group limitations for energy-limited units

and environmental constraints in WASP-IV

LLEECCTTUURREE 1177

Sensitivity analysis in WASP-IV


Review of Teams’ Optimal Solution Results

DDIISSCCUUSSSSIIOONN

Question/Answer session on WASP-IV Software

15:15 – 15:30 Break

15:30 – 17:00 WWOORRKK SSEESSSSIIOONN

Execution of DYNPRO



WASP-IV



WASP-IV


Review of Teams’ Optimal Solution Results

(continued)

CCOOUURRSSEE CCLLOOSSIINNGG

Presentation of training certificates


12

ANNEX II

Trainee Presentations of WASP-IV

Reference Cases for Indonesia

1

JAVA BALI TEAM WASP-IV TRAINING COURSE

PT. PLN (PERSERO) P3B JAWA BALIPUSAT PENYALURAN DAN PENGATUR BEBAN JAWA BALI


Unit 2007 2008 2009 2010 2011

POPULATION * 10 3̂ 137,337 139,184 141,068 142,963 144,867

CUSTOMER * 25,086,954 26,113,326 27,278,746 28,245,080 29,251,173

GROWTH OF GDP * % 6.0 6.6 7.2 5.6 5.6

ELECTRIFICATION RATIO * % 63.1 64.3 65.6 66.4 67.2

TOTAL PRODUCTION ** GWh 108,249 114,933 122,871 131,347 140,411

ENERGY SALES ** GWh 101,560 107,754 115,196 123,142 131,641

INSTALLED CAPACITY ** MW 22,286 22,286 25,286 27,536 30,271

PEAK LOAD BRUTO ** MW 16,587 17,730 18,955 20,162 21,660

*) FORUM PERENCANAAN JAWA BALI 2006**) PLANNING

GENERAL ENERGY AND ELECTRICITY PICTURE (Cont)

2


Resources of Natural Gas and CoalResources of Natural Gas and Coal

Irian Jaya

Singapore

Medan

Surabaya

Malaysia

Kalimantan 53.813.2

3.73.2

Proven and Probable Gas Reserves (2P)(in trillion cubic feet)

12.1

0.4

26.9

Pipelines Under Development

Existing Pipelines

Planned Projects

Existing MarketTarget Market

Jakarta

61.2

3.6

178 Coal Resources


Hydro PP

SURALAYACILEGON

M.TAWAR

GANDULCIBATU

CIBINONG

CIRATA

SAGULING

DEPOK

BEKASICAWANG

TASIKMALAYA

BANDUNGSELATAN

MANDIRANCAN

UNGARAN

T.JATI

PEDAN

KEDIRIPAITON

GRATI

KRIAN

GRESIK

KEMBANGAN

GLNUKPMRON

BTRTI

KAPAL

NGARA

ANTRI GNYAR

AMPLA

NSDUA

GTENG

STBDO

BWNGI

BDWSO

JMBERTNGUL

LMJNG

GNDING

PBLGO

PAKIS

WLNGIKKTES

KBAGN

BNGIL

BNGIL

SKLNG

KBAGN

BNRAN

GLTMR

BKLAN

SPANG

PMKSN

SMNEP

LNGAN

NGBNG

MKRTO

NGOROKTSNO

SBLTN

TUBAN

BABAT

DWIMA

BJGRO

NGAWI

MNRJO

RBANG

BLORA

CEPU

SRGEN

PWRDI

KDMBO

PATIJPARA

KUDUSTBROKKRPYKWLERI

KLNGU

GRUNG

DIENG

WSOBO

WALIN

PWRJO

WATES

BNTUL

SMANU

MDARIKNTUG

WNGIRI

WNSRI

PALURJAJAR

MJNGO

KBSENBRBES

KBSEN

RWALO

CLCAP

GBONG

KBMEN

MRICA

MNANGBNJARCAMIS

JTBRGHRGLS

SRAGI

SKMDIINDMY

SBANGPWKTACKPAY

PBRAN

GARUT

DRJAT

CKSKA

RCKEK

KMJNG

CGRLG

UBRNG

PDLRGDAGO

KSBRU

RGDLK

KNGAN

BBKAN

MLBNG

ARJWN

PMPEK

SMDRASNTSA

CNJUR

LBSTUPRATU

UBRUG

SALAK

BGBRUBUNAR

RKBTGMENES

TNAGA

BLRJA

P

P

PP

P

TLGNG

TLGNG

TUREN

PBIAN

UBUD

CLGONGU

GU GUMKRNG PRIOK

GU

GU

MRGEN

MSPTI

PLOSO

PCTAN

NGJUK

SMANMDLAN

SLRJO

.

Muarakarang1150 MW

Tj Priok900 MW

Cirata1000 MW

Saguling700 MW

Paiton3200 MW

Grati800 MW

Semarang1300 MW

Gresik2000 MW

TjJati B1320 MW

Cilacap600 MW

Cilegon740 MW

SPP coal-firedCC gas-firedCC oil-fired

500 kV, 39 lines, 3578 kms150 kV 664 lines, 12204 kms70 kV 199 lines, 3604 kms

ENERGY SUPPLIESON JAWA BALI SYSTEM 2006

Installed capacity thermal 19.590 MWInstalled capacity hydro 2.536 MW Installed capacity 22.126 MW

3


REALISATION AND PLANNING ON POWER PLANT KOMPOSITION 1998 - 2011

0%

20%

40%

60%

80%

100%

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

RencanaRealisasi

Air Panas Bumi Batu Bara Gas Minyak


Capacity Balance 2007 - 2011

ITEM 2007 2008 2009 2010 2011

Installed Capacity (MW) 22126 22236 22236 26736 30486

Additional Capacity (MW) 110 0 4500 3750 2735

Total Installed Capacity (MW) 22236 22236 26736 30486 33221

Beban Puncak (MW) 16587 17730 18955 20262 21660

Peak Load Growth % 4.0 6.9 6.9 6.9 6.9

Reserve Margin % 34 25 41 50 53

Load Factor % 75.3 74.5 74.0 74.0 74.0

Production (GWh) 108249 114933 122871 131346 140412

Production Growth % 2.9 6.2 6.9 6.9 6.9

1) 2) 3) 4)

Sumber : Buku PASA 2007-2011

4


1) 2007 : PLTP Drajat-3 (110 MW) Total : 110 MW

2) 2009 : PLTP Kamojang unit 4( 60 MW), PLTP Wayang Windu (110 MW), PLTU Bali Utara unit 1-2 (2x65 MW), PLTU Labuhan unit 1,2 (2x300 MW), PLTU Teluk Naga unit 1,2(2x300 MW), PLTU Jabar Selatan unit 1,2 (2x300 MW), PLTU Jabar Utara unit 1,2 (2x 300 MW), PLTU Rembang unit 1,2 (2x300 MW), PLTU Jatim Selatan unit 1,2 (2x300 MW),PLTU Tj. Awar-Awar unit 1,2 (2x300 MW) Total : 4500 MW

3) 2010 : PLTP Dieng (60 MW), PLTP Patuha (120 MW), PLTU Bali Utara unit1,2 (2x130 MW), PLTP Bedugul (10 MW), PLTU Suralaya (600 MW), PLTU Teluk Naga unit 3 (300 MW), PLTU Jabar Selatan unit 3 (300 MW), PLTU Jabar Utara unit 3 (300 MW), PLTU Paiton 600 MW, PLTU Tj. Jati Baru (600 MW, PLTU Cirebon (600 MW). Total : 3750 MW

4) 2011 : PLTP Dieng (60 MW), PLTP Patuha (60 MW), PLTU Madura (65 MW), PLTU Bali Timur(100 MW), PLTU Jawa Tengah (600 MW), PLTU Mulut Tambang (1200 MW). RepoweringPLTGU Muarakarang (500 MW), Rep. PLTGU Muaratawar (150 MW). Total : 2735 MW

Addition & Retirement Power Plant 2007-2011

Sumber : Buku PASA 2007-2011

Addition :

Retirement :

1) 2008 : PLTU Muara Karang 1-3 (300 MW). Total : 300 MW2) 2010 : PLTU Perak 1 (96 MW), PLTD Bali (50 MW). Total : 146 MW3) 2011 : PLTU Muara Karang 4-5 (400 MW), PLTU Perak 3 (40 MW), PLTG Sunyaragi 1 (36 MW),

PLTG Sunyaragi 2 (40 MW), PLTU Tambak Lorok 2 (82 MW), PLTG Cilacap (44 MW)PLTU Gersik 3 (170 MW). Total : 812 MW


27786 29705 31754 3394636288

3882841546

4445447566

5089654458

5827062349

6671471384

0

10000

20000

30000

40000

50000

60000

70000

80000

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

YEAR

MW

Demand GrowthPlant Capacity

DEMAND GROWTH AND PLANT CAPACITY (INCLUDED RETIREMENT)

5


Future Options for Electricity Supply

MW MW Base LoadAverage

Incremental

Domestic Foreign

1 C6H 0 300 600 2510 2389 667 0 0 5 7 422 LNG 0 375 750 1911 1744 0 1984 2 7 7 423 N10H 0 1000 1000 2606 2606 0 239 6 0 7 284 G150 0 75 150 3150 2625 2743 0 4 10 7 285 PUMP 0 250 500

Days Schedule

Maintenance MW

CapacityHeat Rates Fuel Costs

Spinning Reserveas

FORKcal/kWh Cents/Million Kcal Fuel Type

No. NameNo. of

Sets

Min. Load

Scenario Assumption1. Variable Expansion (Pump Storage 2 X 500 MW Fixed in 2013 and 2014)2. Variable Expansion (Pump Storage in VARSYS)3. Variable Expansion (Pump Storage in VARSYS and Coal Limitted Up To 40 Units)


Scenario Assumption1. Loads Demand in Bruto (Net Load Demand + Aux Plant+Losses)2. Load Growth 6.9% from 2007 to 20263. No Change in LDC (No Demand side management )4. Availability for Energy Resources (Coal, LNG, Oil, Nuclear)

Scenarios1. Variable Expansion (Pump Storage 2 X 500 MW Fixed in 2013 and 2014)2. Variable Expansion (Pump Storage in VARSYS)3. Variable Expansion (Pump Storage in VARSYS and Coal Limitted Up To 40 Units)

6


PU0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

PU

SCREENING CURVES

0

200

400

600

800

1000

0 20 40 60 80 100

Unit Capacity Factor [%]Leve

lized

Cos

t [$/

kW-

yr]

Nuclear Coal PS gas turbin LNG


System Reliability Criteria

Reserve Margin :Minimum = 25% Maximum = 40%

Spinning ReserveLOLP = 0.274%, Equal to 1 day/yearCost of ENS = 0.85 $/KWh

7


Dynpro Input Data

PLANT CONSTR.

LIFE TIME

DOMESTIC FOREIGN DOMESTIC FOREIGN (YEARS) (%) (YEARS)C6H 491 736 0 0 30 18.46 4LNG 233 582 0 0 25 14.13 3N10H 954 1,362 0 0 40 26.6 6G150 166 221 0 0 20 9.6 2PS 681 1,362 0 0 50 26.6 5

CAPITAL COSTS ($/kW)

DEPRECIABLE PART NON-DEPRECIABLE PART

I.D.C.PLANT

Discount Rate = 12%No of Year to be Considered for Economic Comparison = 20 years


Report about Optimal SolutionCase 1: Pump Fix

OBJ.FUN. RES. LOLP(CUMM.) % %

2007 4,510,733 - - - - 28.8 0.072 2008 8,559,760 - - - - 19.1 1.066 2009 11,406,974 - - - - 35.1 0.004 2010 13,736,353 - - - - 43.3 - 2011 16,420,704 600 - - - 40.3 - 2012 19,325,790 1,200 - - - 35.6 - 2013 22,037,206 1,200 - - - 27.9 0.001 2014 24,854,738 1,800 - - - 37.8 0.001 2015 27,687,972 2,400 - - - 33.9 0.001 2016 30,074,994 1,800 - - - 31.2 0.003 2017 32,287,344 1,800 - - - 27.9 0.013 2018 34,931,580 4,200 - - 300 28.2 0.008 2019 37,330,628 4,200 - - 900 27.7 0.005 2020 39,394,456 3,600 - - 1,350 27.4 0.003 2021 41,092,160 2,400 - - 1,500 27.3 0.002 2022 42,786,168 3,600 750 - 150 27.4 0.001 2023 44,265,996 3,000 750 - 450 27.0 0.001 2024 45,618,864 3,600 - - 1,050 27.0 - 2025 46,838,744 3,600 750 - 150 26.9 - 2026 47,920,404 3,600 - - 1,200 26.8 -

TOTAL 42,600 2,250 - 7,050 *) Objective function without Pump Storage Capital Cost

YEAR C6H LNG N10H G150

8


Case 2: Pump Var Free Optimization


2007 4,513,270 - - - - - 28.8 0.074 2008 8,559,675 - - - - - 19.1 1.077 2009 11,405,314 - - - - - 35.1 0.004 2010 13,737,286 - - - - - 43.3 - 2011 16,421,868 600 - - - - 43.1 - 2012 19,328,064 1,200 - - - - 38.2 - 2013 22,043,950 1,200 - - - - 33.2 0.003 2014 25,118,910 2,400 - - - - 32.1 0.004 2015 27,926,160 2,400 - - - - 30.7 0.004 2016 30,292,732 1,800 - - - - 28.2 0.011 2017 32,650,432 2,400 - - - - 27.0 0.014 2018 35,258,524 4,200 - - 150 - 26.5 0.012 2019 37,646,488 4,200 - - 900 - 26.5 0.007 2020 39,684,156 3,000 750 - 1,200 - 26.3 0.004 2021 41,418,972 2,400 750 - 750 - 26.2 0.003 2022 43,063,036 3,000 750 - 600 - 26.0 0.002 2023 44,559,724 3,600 - - 750 - 26.1 0.001 2024 45,865,400 2,400 - - 2,100 - 25.8 0.001 2025 47,091,860 3,600 750 - 150 - 25.8 - 2026 48,189,652 4,800 - - - - 25.8 -

TOTAL 43,200 3,000 - 6,600 -

YEAR C6H PUMPG150LNG N10H

Report about Optimal Solution (Cont)


Report about Optimal Solution (Cont)Case 3: Pump Var Coal Limit


2007 4,513,270 - - - - - 28.8 0.074 2008 8,559,675 - - - - - 19.1 1.077 2009 11,405,314 - - - - - 35.1 0.004 2010 13,737,286 - - - - - 43.3 - 2011 16,421,868 600 - - - - 43.1 - 2012 19,328,064 1,200 - - - - 38.2 - 2013 22,043,950 1,200 - - - - 33.2 0.003 2014 25,118,910 2,400 - - - - 32.1 0.004 2015 27,926,160 2,400 - - - - 30.7 0.004 2016 30,292,732 1,800 - - - - 28.2 0.011 2017 32,650,432 2,400 - - - - 27.0 0.014 2018 35,258,524 4,200 - - 150 - 26.5 0.012 2019 37,646,488 4,200 - - 900 - 26.5 0.007 2020 39,684,156 3,000 750 - 1,200 - 26.3 0.004 2021 41,336,288 600 2,250 - 1,050 - 26.2 0.003 2022 43,245,252 - 750 3,000 600 - 26.0 0.002 2023 44,750,828 - 3,000 1,000 300 - 26.0 0.002 2024 46,150,204 - 750 2,000 1,800 - 25.8 0.001 2025 47,357,132 - 3,750 - 750 - 25.8 0.001 2026 48,507,652 - 1,500 3,000 300 - 25.8 -

TOTAL 24,000 12,750 9,000 7,050 -

YEAR C6H LNG N10H G150 PUMP

9


Conclusion and Recommendations

OBJ.FUN.(CUMM.)x 1000$

1 (Pump Storage Fixed in 2013 & 2014) 49,858,404 42,600 2,250 - 7,050 - 2 (Pump Storage in VARSYS) 48,189,652 43,200 3,000 - 6,600 - 3 (Pump Storage in VARSYS and Coal Limitted) 48,507,652 24,000 12,750 9,000 7,050 -

G150 PUMPCASE C6H LNG N10H

1. Case 1 is the highest cost than case 2 & 32. Case 2 is the least cost than other cases but the level of polution is higher than cases 33. Case 3 is the medium cost than case 1 & 2, but we can minimize the level of polution from

coal power plant


Plan for The Future Activities on The WASP StudyModelling the hydro condition more accurateCompletting the data for WASP model such as emission, environmental data, etcStudy other different cases for PLN Java Bali System

10


*) FORUM PERENCANAAN JAWA BALI 2006**) REALISASI

Unit 2002 2003 2004 2005 2006

POPULATION * 10 3̂ 126,580 129,207 131,783 133,618 135,519

CUSTOMER * 21,086,702 21,840,468 22,531,579 23,369,514 24,187,332

GROWTH OF GDP * % 2.7 3.8 4.5 5.0 5.5

ELECTRIFICATION RATIO * % 60.6 61.4 62.2 63.2 62.2

TOTAL PRODUCTION ** GWh 86,608 89,976 95,993 101,552 105,222

ENERGY SALES ** GWh 69,960 72,190 79,333 85,492 98,720

INSTALLED CAPACITY ** MW 18,096 18,608 19,466 19,466 22,126

PEAK LOAD BRUTO ** MW 13,780 14,172 14,920 15,352 15,954

GENERAL ENERGY AND ELECTRICITY PICTURE


1

www.plnkalbar.co.idwww.pln.co.id

Electricity For A Better Life

Electricity for Better Life

GENERATION EXPANSION GENERATION EXPANSION PLANNING OF WEST PLANNING OF WEST

KALIMANTANKALIMANTAN

By Team 3 :

IRA SAVITRI

ISMAIL DEU

PURWANTO

FINAL PRESENTATION OF WASP IV

WEST KALIMANTANTEAM 3

Electricity For

A Better LifeGeneral Energy & Electricity Picture-(1)

Data

Population : 4.424.910 (end of 2006)

Number of cust. : 506.385 (end of Nov 2006)

Size : 282,22 MW

Production Energy : 1.069,4 MWH

Sales Energy : 809 MWH

Power Contracted : 512 MVA

Resources : Peat Land, Biofuel (CPO), Uranium

(still be used for research by

National Atomic Energy Association)

Electricity Consumption Trend : 9,5%-10%

2


Electricity For

A Better LifeGeneral Energy & Electricity Picture-(2)

System


Electricity For

A Better Life

Main assumption regarding to demand growth :

GDP Growth rate : 6,5% -8,0%

Population Growth : 1,1%-1,63%

Electrification Ratio : 52,13 (end 2006),

expectation 65% (end of 2010)

Projections of Future Electricity Requirements

3


Electricity For

A Better Life

Description of Existing System-(1)

No.

A SEKTOR KAPUAS1 PLTD SIANTAN Diesel 6 24,600 35,000 20092 PLTD SEI RAYA Diesel 6 33,500 50,400 20083 PLTG SIANTAN Gas 1 31,000 34,0004 PT.COGINDO Diesel 5 8,000 8,000 20105 PT. SEWATAMA I Diesel 10 10,000 10,000 20076 PT. SEWATAMA II Diesel 10 10,000 10,000 2007

Total 38 117,100 147,400

B SISTEM SINGKAWANG1 PLTD SUDIRMAN Diesel 4 5,500 6,285 20072 PLTD SEI WIE Diesel 7 13,000 18,400 20073 PT.SEWATAMA SINGKAWANG Diesel 6 5,000 5,000 2010

Total 17 23,500 29,685

C SISTEM SAMBAS1 PLTD RANTING SAMBAS Diesel 11 5,180 8,119 20072 PT.SEWATAMA SAMBAS Diesel 5 5,000 5,000 2010

Total 16 10,180 13,119

D SISTEM TAYANPLTD KANTOR JAGA T A Y A N Diesel 2 575 750

E SISTEM SANGGAU1 PLTD SEMBOJA SANGGAU Diesel 9 5,620 7,4202 PT.SEWATAMA SGU Diesel 4 2,000 2,000 2010

Total 13 7,620 9,420

F SISTEM SINTANG1 PLTD TELUK M. SINTANG Diesel 10 5,300 10,7022 PT.SEWATAMA STG Diesel 4 2,000 2,000 2010

Total 14 7,300 12,702Total of PLN Plants 54 123,700 170,326Total of Rental Plants 44 42,000 42,000Total 98 165,700 212,326

Year of RetirementType Number

of UnitInstalled

Cap. (kW)Available Cap. (kW)Name of Plants


Electricity For

A Better Life

Addition Plants :

Description of Existing System-(2)

CapacityPlantCode

Steam Coal PP Pontianak BBR1 2010 55 2Steam Coal PP Pontianak BBR8 2010 50 2Steam Coal PP Parit Baru BBPB 2008 25 1Biomass Sanggau BIO1 2012/2017 3 2/3Biomass Sanggau BIO2 2012 2 1Biomass Sintang BIO3 2017 2.5 2Steam Coal PP Mulut Tambang MTB 2012 / 2017 7 1/3Sesco Singkawang Sesc 2010/2011 50 1/1

Plants

LocationNames MWYear of Addition Number of Unit

4


Electricity For

A Better Life

Future Options for Electricity Supply-(1)

TECHNICAL AND ECONOMICAL DATA

CPP(BBR3)

CPP(BBR2)

CPP(GAM1)

GTPW(GAS)

NUCL(NUCL)

Capacity MW 50 100 30 35 200Bahan bakar COAL COAL COAL LNG NUCLHarga BB US$/10^6 kCal 4.72 4.72 4.72 11.90 2.39Efisiesi Thermal 32% 35% 30% 30% 33%Tara Kalor 2688 2457 2867 2867 2600Variabel O&M $/MWh 0.60 0.60 0.60 1.50 0.18Fixed O&M $/KW.year 54 50 58 60 37.8Investment Cost $/KW 900 900 1000 450 2000Pembangunan Tahun 4 4 3 3 5Umur Ekonomis Tahun 27 27 27 26 30

Discount rate 12.00% 12.00% 12.00% 12.00% 12.00%CRF 12.59% 12.59% 12.59% 12.67% 12.41%IDC 22.64% 22.64% 16.45% 16.45% 29.23%

Annual Investment cost $/KW.year 138.97 138.97 146.62 66.37 320.86Annual Fixed Cost $/KW.year 192.97 189.37 204.22 126.37 358.66

Annual Fuel Cost $/KW.year 94.39 86.30 100.68 254.11 46.27Annual Variable O&M $/KW.year 5.26 5.26 5.26 13.14 1.58Annual Variable Cost $/KW.year 99.65 91.56 105.94 267.25 47.85

Total $/KW.year 292.62 280.93 310.16 393.62 406.51


Electricity For

A Better Life

Future Options for Electricity Supply-(2)

SCREENING CURVE

0

50

100

150

200

250

300

350

400

450

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

CF (%)

CO

ST

($/k

W-y

r)

BBR3BBR2GAM1GASNUCL

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

0.7000

0.8000

0.9000

1.0000

0.0000 0.1000 0.2000 0.3000 0.4000 0.5000 0.6000 0.7000 0.8000 0.9000 1.0000

0.4820.397

0.358

5


Electricity For

A Better Life


Feasible year of operation candidate unit is

2015

No limit due to fuel constraints

Maximum acceptable unit size is 200 MW

Reserve margin : 30% – 40%

LOLP limit : 1 day/year

ENS Cost : 0.85 US$/kWh


Electricity For

A Better LifeDynpro Input

BBR3 BBR2 GAM1 GAS NUCLInvest Cost $/kW 1226.40 1103.76 1226.40 524.025 2584.60IDC % 18.46 18.46 18.46 14.13 22.62Plant Life Years 27 27 27 25 30Construction Time Years 4 4 4 3 5Discount rate 12% (based year 2007)

Data for Dynpro Input

6


Electricity For

A Better LifeReport About Optimal

Solution

These are the comparison of optimal and non optimal solution :

Non-Optimal solution

Optimal solution


Electricity For

A Better LifeSensitivity Analysis

For Sensitivity analysis, economic parameter that is used is escalation rates. The escalation assumed to be happened in coal, gas and oil cost (fuel prices). It is assumed that in year 2010, 2014,2018, 2022 and 2026, the escalation rates for coal is 5% while for gas and oil are 2.5%.

Opt solution without esc.

Opt solution with esc.

7


Electricity For

A Better LifeConclusion (1)

By using WASP IV for Expansion Planning,with many configurations of 5 candidates plant, finally found the optimum solution that gave least cost is :

Optimal solution

Nuclear candidate can’t be included in the system because its investment cost is too high and can’t compete with the other candidates

By 5% escalation for coal cost and 2.5% for gas and oil cost, it’s found that the operation cost higher 54.7% than without escalation


Electricity For

A Better LifeRecomendations

For nuclear generation, should be a continuation study because in big size, it can be an efficient generation.

8


Electricity For

A Better Life

Kashiwazaki-Kariwa8,212 MW (Steam) Japan

Plan For the Future Activities

We expect WASP IV program can be used for long

term planning generation in West Kalimantan


Electricity For

A Better Life

9


Electricity For

A Better LifeNon Optimal Solution

BackGo to Optimal solution

SOLUTION # 1 VARIABLE ALTERNATIVES BY YEAROBJ.FUN. LOLP

CONCST SALVAL OPCOST ENSCST TOTAL (CUMM.) %

2026 14945 12894 21238 4 23294 913951 0.023 2 7+ 1 7+ 02025 16738 12444 21549 5 25849 890658 0.023 2 6+ 1 6+ 02024 8014 5088 22132 8 25066 864809 0.032 2 5+ 1 5+ 02023 18005 9917 22041 12 30142 839743 0.038 2 5+ 1 2+ 02022 20165 9535 23164 12 33806 809601 0.035 2 4+ 1 2+ 02021 22585 9154 24448 10 37889 775796 0.031 2+ 3+ 1 2+ 02020 25295 8772 26462 13 42998 737906 0.037 2+ 2 1 2+ 02019 15739 4662 27422 17 38517 694908 0.049 2 1 1 2+ 02018 17628 4450 28264 8 41450 656392 0.025 1 1 1 2+ 02017 35538 7628 29138 6 57053 614942 0.018 0 1 1 2+ 02016 6614 1148 29347 8 34821 557889 0.025 0 0 1 2+ 02015 22267 3368 28704 4 47607 523068 0.015 0 0 1+ 1+ 02014 0 0 28328 21 28349 475462 0.048 0 0 0 0 02013 0 0 28428 2 28430 447113 0.007 0 0 0 0 02012 0 0 27663 0 27663 418683 0 0 0 0 0 02011 0 0 26407 0 26407 391020 0 0 0 0 0 02010 0 0 27146 0 27146 364613 0.001 0 0 0 0 02009 0 0 25748 753 26501 337467 0.985 0 0 0 0 02008 0 0 117209 0 117209 310965 0.001 0 0 0 0 02007 0 0 193738 18 193756 193756 0.06 0 0 0 0 0

NUCLBBR3 BBR2 GAM1 GASPRESENT WORTH COST OF THE YEAR ( K$ )YEAR


Electricity For

A Better LifeOptimal Solution

Go to Non Optimal solution

OPTIMAL SOLUTIONOBJ.FUN. LOLP

CONCST SALVAL OPCOST ENSCST TOTAL (CUMM.) %

2026 14945 12894 21238 4 23294 910954 0.023 2 7 1 7 02025 16738 12444 21549 5 25849 887660 0.023 2 6 1 6 02024 8014 5088 22132 8 25066 861812 0.032 2 5 1 5 02023 18005 9917 22041 12 30142 836746 0.038 2 5 1 2 02022 20165 9535 23164 12 33806 806604 0.035 2 4 1 2 02021 22585 9154 24448 10 37889 772798 0.031 2 3 1 2 02020 25295 8772 26462 13 42998 734909 0.037 2 2 1 2 02019 9415 2707 27422 17 34147 691911 0.049 2 1 1 2 02018 10577 2670 26440 27 34374 657765 0.065 2 1 1 0 02017 35538 7628 26975 9 54894 623391 0.025 2 1 0 0 02016 22113 4026 26606 16 44708 568497 0.04 2 0 0 0 02015 24766 3814 27360 16 48327 523789 0.039 1 0 0 0 02014 0 0 28328 21 28349 475462 0.048 0 0 0 0 02013 0 0 28428 2 28430 447113 0.007 0 0 0 0 02012 0 0 27663 0 27663 418683 0 0 0 0 0 02011 0 0 26407 0 26407 391020 0 0 0 0 0 02010 0 0 27146 0 27146 364613 0.001 0 0 0 0 02009 0 0 25748 753 26501 337467 0.985 0 0 0 0 02008 0 0 117209 0 117209 310965 0.001 0 0 0 0 02007 0 0 193738 18 193756 193756 0.06 0 0 0 0 0

Note : the difference price of cummulative objective function is 2,997

GAM1 GAS NUCLBBR3 BBR2YEAR PRESENT WORTH COST OF THE YEAR ( K$ )

BackTo ConcTo sens

10


Electricity For

A Better Life Sensitivity AnalysisESKALASI COAL 5%, GAS & OIL 2.5%

OBJ.FUN. LOLPCONCST SALVAL OPCOST ENSCST TOTAL (CUMM.) %

2026 14945 12894 24162 4 26217 938491 0.023 2 7 1 7 02025 16738 12444 23882 5 28181 912273 0.023 2 6 1 6 02024 8014 5088 24536 8 27471 884092 0.032 2 5 1 5 02023 18005 9917 24539 12 32639 856622 0.038 2 5 1 2 02022 20165 9535 25734 12 36376 823982 0.035 2 4 1 2 02021 22585 9154 26356 10 39797 787607 0.031 2 3 1 2 02020 25295 8772 28358 13 44894 747809 0.037 2 2 1 2 02019 9415 2707 29283 17 36008 702916 0.049 2 1 1 2 02018 10577 2670 28348 27 36282 666908 0.065 2 1 1 0 02017 35538 7628 28275 9 56194 630626 0.025 2 1 0 0 02016 22113 4026 27746 16 45848 574432 0.04 2 0 0 0 02015 24766 3814 28490 16 49458 528584 0.039 1 0 0 0 02014 0 0 29433 21 29454 479126 0.048 0 0 0 0 02013 0 0 29019 2 29021 449673 0.007 0 0 0 0 02012 0 0 28301 0 28301 420652 0 0 0 0 0 02011 0 0 27051 0 27051 392350 0 0 0 0 0 02010 0 0 27832 0 27833 365299 0.001 0 0 0 0 02009 0 0 25748 753 26501 337467 0.985 0 0 0 0 02008 0 0 117209 0 117209 310965 0.001 0 0 0 0 02007 0 0 193738 18 193756 193756 0.06 0 0 0 0 0

Note : the difference price of cummulative objective function is 27,537 The escalation of fuel cost give a significant impact to the operationan cost

BBR3 NUCLGASGAM1BBR2PRESENT WORTH COST OF THE YEAR ( K$ )YEAR

Back

1

Company

LOGO

Optimizing KaltimseltengGeneration System Planning

Optimizing KaltimseltengGeneration System Planning

WASP TrainingBogor, 2007

PLTA PLTA SebakungSebakung

PLTA PLTA SesayapSesayap

Batakan

S.EmpatS.EmpatBatuBatu LicinLicin

PLTA PLTA KayanKayan

PLTA PLTA KelaiKelai

GI.T.SelorGI.T.Selor

PLTA PLTA BohBoh II

PLTA PLTA BohBoh IIII

GI. GI. TJ.RedepTJ.Redep

GI.SanggattaGI.Sanggatta

GI.PurukCahuGI.PurukCahu

GI.BuntokGI.Buntok

GI.M.TewehGI.M.TewehGI.KualaKurunGI.KualaKurun

MantuilMantuil

SamarindaSamarinda

BarasBaras

BalikpapanG. Malang

Electricity MapElectricity Map

Mahakam

195 / 168 MW

Barito

256 / 265 MW

Population : 8 106 821 people

Electrification ratio : 55.2 %

2

Energy ResourcesEnergy Resources

66%

30%

3%1%

Hydro HSD Coal Gas

Electricity Consumption TrendElectricity Consumption Trend

Production

0.0

500.0

1 000.0

1 500.0

2 000.0

2 500.0

3 000.0

2002 2003 2004 2005 2006

Year

GW

h

Peak Load

340.0350.0360.0370.0380.0390.0400.0410.0420.0430.0440.0450.0

2002 2003 2004 2005 2006

Year

MW

3

Future Electricity RequirementsFuture Electricity RequirementsGDP Growth rate : 7.03 % Population Growth rate : 1.21 %

Production

02 0004 0006 0008 000

10 00012 00014 00016 00018 00020 000

07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Year

GW

h

Peak Load

0

500

1 000

1 500

2 000

2 500

3 000

3 500

07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

YearM

W

Production Growth rate : 10.13 % Peak Load Growth rate : 9.85 %

Fix SystemFix SystemKalsel Installed CapacityPlant Type Operation Unit Max Min FoR O&M O&M Fuel

Year Load Load Minimum Avg Inc Fixed Var. costMW MW kcal/kWh kcal/kWh % US$/kW-month US$/MWh cent/10 6̂ kcal

Riam Kanan PLTA 1973 3.0 10.0 0 0.55Trisakti TRS1 PLTD 1983 1.0 4.0 1.2 3909 1845 5 0.5 2.0 6735Trisakti TRS2 PLTD 1990 2.0 5.0 1.5 3909 1475 5 0.5 2.0 6735Trisakti TRS3 PLTD 1987 2.0 6.5 2.0 3909 1475 5 0.5 2.0 6735 TRS4 PLTD 1992 4.0 10.0 3.0 3909 1475 5 0.5 2.0 6735Trisakti TRS5 PLTG 1986 1.0 17.0 5.1 4300 3742 7 0.5 2.0 6735Amuntai AMT1 PLTD 1996 2.0 2.5 0.8 3909 1835 5 0.5 2.0 6735Amuntai AMT2 PLTD 1988 2.0 1.0 0.3 3909 1835 5 0.5 2.0 6735Barabai BRBI PLTD 1989 2.0 2.2 0.7 3909 1835 5 0.5 2.0 6735K. Kapuas KKPS PLTD 1992 2.0 2.2 0.7 3909 1835 5 0.5 2.0 6735Palangkaraya PLKR1 PLTD 1986 3.0 1.8 0.5 3909 1835 5 0.5 2.0 6735Palangkaraya PLKR2 PLTD 1995 1.0 2.2 0.7 3909 1835 5 0.5 2.0 6735Asam-Asam ASAM PLTU 2000 2.0 64.0 38.4 3583 768 7 2.1 1.8 472Rent Diesel SKLS PLTD 2000 1.0 12.0 11.0 2867 2867 3 0.0 19.9 6735

Kaltim Installed CapacityPlant Type Operation Unit Max Min FoR O&M O&M Fuel


Batakan BTKA PLTD 1988 3 3.0 1.0 3909 2420 5 0.5 2.0 6524Gn Malang GNML PLTD 1976 6 3.0 1.0 3909 2420 5 0.5 2.0 6524K. Asem KRA1 PLTD 1978 6 3.0 1.0 3909 2420 5 0.5 2.0 6524K. Asem KRA2 PLTD 1993 2 6.0 2.0 3909 2420 5 0.5 2.0 6524Sei Kledang SKL1 PLTD 1987 4 4.0 1.0 3909 2420 5 0.5 2.0 6524Sei Kledang SKL2 PLTD 1990 3 5.0 2.0 3909 2420 5 0.5 2.0 6524T. Batu TJBT PLTGU 1997 1 48.0 10.0 3583 1643 7 1.2 0.5 1190Kaltimex TIME PLTD 2003 1 12.0 11.0 2867 2867 1 0.0 19.9 6524Pemkot Bpp PBPP PLTD 2003 1 2.0 1.0 2867 2867 1 0.0 19.9 6524Menamas MNMS PLTD 2003 1 20.0 19.0 2867 2867 3 0.0 24.0 1190Pemkot Kukar KKAR PLTD 2005 1 8.0 7.0 2867 2867 3 0.0 19.9 6524

Heat Rate

Heat Rate

4

Committed PlantCommitted PlantKalsel Committed PlantPlant Type Operation Unit Max Min FoR O&M O&M Fuel


Sampit SMPC PLTU 2010 2.0 6.0 5 2688 2688 7 2.1 1.8 472Pagkln Bun PBNC PLTU 2012 2.0 6.0 5.0 2688 2688 7 2.1 1.8 472Tanjung TJGC PLTU 2010 2.0 65.0 60.0 2688 2688 7 2.1 1.8 472Kalteng KTGC PLTU 2010 2.0 60.0 35.0 3583 768 7 2.1 1.8 472Rent Diesel SDES PLTD 2008 3.0 10.0 9.0 2867 2867 3 0.0 19.9 4565

Kaltim Installed CapacityPlant Type Operation Unit Max Min FoR O&M O&M Fuel


Menamas MNMS PLTG 2008 1 20.0 19.0 2867 2867 3 0.0 24.0 1190Embalut STPR PLTU 2008 2 22.0 21.0 2688 2688 7 2.1 1.8 472CC Menamas CCMN PLTGU 2009 1 56.0 55.0 2048 2048 3 0.0 24.0 1190Rent Diesel SDET PLTD 2007 8 10.0 9.0 2867 2867 3 0.0 19.9 6524Semboja PSBJ PLTU 2010 2 22.0 21.0 2688 2688 7 2.1 1.8 472Kaltim PKLT PLTU 2011 2 60.0 59.0 2688 2688 7 2.1 1.8 472Balikpapan GTBP PLTG 2009 2 40.0 39.0 2867 2867 3 1.2 0.5 1190Tanah Grogot STGR PLTU 2010 2 6.0 5.0 2688 2688 7 2.1 1.8 472Bontang GBTG PLTG 2010 1 10.0 9.0 2048 2048 3 1.2 0.5 1190

Heat Rate

Heat Rate

Stop in 2010

Stop in 2011/12

Retirements/Fuel ChangingRetirements/Fuel ChangingKalsel RetirementPlant 2007 2008 2009 2010 2011 2012 NoticeRiam Kanan Trisakti TRS1 -1 old plantTrisakti TRS2 -2 change fuel to MFOTrisakti TRS3 -2 old plant TRS4 -4 change fuel to MFOTrisakti TRS5 -1 old plantAmuntai AMT1 -2 change fuel to MFOAmuntai AMT2 -2 old plantBarabai BRBI -2 change fuel to MFOK. Kapuas KKPS -2 change fuel to MFOPalangkaraya PLKR1 -3 old plantPalangkaraya PLKR2 -1 change fuel to MFOAsam-Asam ASAMRent Diesel SKLS -1 stop rented machine

Kaltim RetirementPlant 2007 2008 2009 2010 2011 2012 NoticeBatakan BTKA -3 old plantGn Malang GNML -6 old plantK. Asem KRA1 -6 old plantK. Asem KRA2 -2 old plantSei Kledang SKL1 -4 old plantSei Kledang SKL2 -3 old plantT. Batu TJBTKaltimex TIME -1 stop rented machinePemkot Bpp PBPP -1 stop rented machineMenamas MNMS -1 change to CCPemkot Kukar KKAR -1 stop rented machine

5

RetirementsRetirementsKalsel RetirementPlant 2007 2008 2009 2010 2011 2012 NoticeRiam Kanan Trisakti TRS1 -1 old plantTrisakti TRS2 -2 change fuel to MFOTrisakti TRS3 -2 old plant TRS4 -4 change fuel to MFOTrisakti TRS5 -1 old plantAmuntai AMT1 -2 change fuel to MFOAmuntai AMT2 -2 old plantBarabai BRBI -2 change fuel to MFOK. Kapuas KKPS -2 change fuel to MFOPalangkaraya PLKR1 -3 old plantPalangkaraya PLKR2 -1 change fuel to MFOAsam-Asam ASAMRent Diesel SKLS -1 stop rented machine

Kaltim RetirementPlant 2007 2008 2009 2010 2011 2012 NoticeBatakan BTKA -3 old plantGn Malang GNML -6 old plantK. Asem KRA1 -6 old plantK. Asem KRA2 -2 old plantSei Kledang SKL1 -4 old plantSei Kledang SKL2 -3 old plantT. Batu TJBTKaltimex TIME -1 stop rented machinePemkot Bpp PBPP -1 stop rented machineMenamas MNMS -1 change to CCPemkot Kukar KKAR -1 stop rented machine

CandidatesCandidatesPlant Max Min FoR O&M O&M Fuel

Load Load Minimum Avg Inc Fixed Var. costMW MW kcal/kWh kcal/kWh % US$/kW-month US$/MWh cent/10 6̂ kcal

Coal ST C65 65 33 3440 1772 10 1.9 3.3 472Coal ST C200 200 100 3308 1751 11 1.9 3.3 472Gas CC CC1G 150 50 2867 1433 8 1.3 0.5 1984Oil CC CCO 150 50 2867 1433 8 1.3 0.5 6524Oil CT G50 50 25 3909 1639 6 0.5 0.1 6524

Heat Rate

Scenario AssumptionScenario Assumption

Only 3 Gas Combine Cycle Plant can be added until 2026

Gas Supply Limitation :13.7 MMBTU/d up to 201227.4 MMBTU/d up to 201554.8 MMBTU/d up to 2020

6

Screening CurveScreening CurveLDC Curve

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

0.7000

0.8000

0.9000

1.0000

0.0000 0.1000 0.2000 0.3000 0.4000 0.5000 0.6000 0.7000 0.8000 0.9000 1.0000

Time

Load

0.00

200.00

400.00

600.00

800.00

1000.00

1200.00

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

Capacity Factor

Total G

eneration Cos

t ($/kW

-year)

PLTU 65PLTU 200CC Gas 150CC Oil 150PLTG 50

System Reliability Criteria System Reliability Criteria

Reserve margin 15 – 40 %

Spinning Reserve Option 1 x largest unit

LOLP 1 day/year in 2009

ENS Cost 85 cents / kwh

7

Dynpro Input DataDynpro Input DataPlant Const Plant

Time life Domestic Foreigntime $/kw $/kw

Coal ST C65 4 30 202.36 1146.68Coal ST C200 4 30 183.96 1042.44Gas CC CC1G 3 20 87.34 494.91Oil CC CCO 3 25 87.34 494.91Oil CT G50 2 20 58.08 329.12

Const Cost

Discount rate 12 %

Optimal SolutionOptimal SolutionYear

ST 65 MW

ST 200 MW

CC Gas150 MW

CC Oil150 MW

GT Oil50 MW

2026 6 9 3 1 22025 5 8 3 1 12024 5 7 3 1 12023 5 6 2 1 12022 5 5 2 1 12021 5 4 2 1 12020 5 3 2 1 12019 5 2 2 1 12018 5 1 2 1 12017 5 0 2 1 12016 4 0 2 0 12015 4 0 1 0 12014 4 0 1 0 02013 2 0 1 0 02012 2 0 0 0 02011 0 0 0 0 02010 0 0 0 0 02009 0 0 0 0 02008 0 0 0 0 02007 0 0 0 0 0

8

Optimal SolutionOptimal Solution

Optimization Result

2 676

2 4582 412

2 372 2 349

2 100

2 200

2 300

2 400

2 500

2 600

2 700

2 800

Fix Expans 1st iteration 2nd iteration 3rd iteration 4th iteration

M U

SD

Energy Resources (2026)Energy Resources (2026)

11.3%

0.3%0.8%

0.8%

86.8%

Coal Gas MFO HSD Hydro

9

Sensitivity Analysis Sensitivity Analysis

High Load Forecasting (9.85 % Peak Load Growth rate) VS

Medium Load Forecasting (8.58 % Peak Load Growth rate)

Coal Price Escalation

Scenario 1 :5 % in 2010, 10 % in 2015, 10 % in 2020

Scenario 2:10 % in 2010, 20 % in 2015, 20 % in 2020

Sensitivity AnalysysSensitivity AnalysysObjc Cumm

( M USD)LOLP(%)

Objc Cumm ( M USD)

LOLP(%)

2026 2 349 0.245 2 187 0.181 7.4%2025 2 297 0.258 2 139 0.197 7.4%2024 2 240 0.131 2 086 0.137 7.4%2023 2 172 0.248 2 025 0.102 7.3%2022 2 099 0.166 1 949 0.169 7.7%2021 2 018 0.121 1 871 0.188 7.9%2020 1 929 0.098 1 782 0.225 8.2%2019 1 831 0.089 1 713 0.271 6.9%2018 1 720 0.082 1 649 0.051 4.3%2017 1 596 0.068 1 553 0.061 2.8%2016 1 484 0.182 1 467 0.101 1.2%2015 1 394 0.201 1 381 0.172 0.9%2014 1 329 0.078 1 315 0.102 1.0%2013 1 205 0.143 1 220 0.220 -1.3%2012 1 104 0.240 1 126 0.184 -2.0%2011 955 0.242 978 0.254 -2.4%2010 895 0.052 918 0.084 -2.5%2009 823 0.263 842 0.852 -2.3%2008 580 0.750 580 0.798 -0.1%2007 319 1.459 319 1.459 0.0%

YearHigh Load Forecasting Medium Load Forecasting

%

10

Sensitivity AnalysysSensitivity AnalysysYear Ref case

M USD M USD % M USD %2026 2 349 2 489 6.0% 2 705 15.1%2025 2 297 2 410 4.9% 2 571 12.0%2024 2 240 2 330 4.0% 2 450 9.4%2023 2 172 2 242 3.3% 2 330 7.3%2022 2 099 2 154 2.6% 2 218 5.7%2021 2 018 2 060 2.1% 2 099 4.0%2020 1 929 1 962 1.7% 1 988 3.1%2019 1 831 1 858 1.5% 1 875 2.4%2018 1 720 1 744 1.3% 1 754 1.9%2017 1 596 1 615 1.2% 1 619 1.4%2016 1 484 1 499 1.0% 1 515 2.1%2015 1 394 1 406 0.8% 1 417 1.7%2014 1 329 1 336 0.6% 1 343 1.1%2013 1 205 1 211 0.5% 1 216 1.0%2012 1 104 1 108 0.4% 1 113 0.8%2011 955 958 0.3% 961 0.6%2010 895 896 0.1% 897 0.3%2009 823 823 0.0% 823 0.0%2008 580 580 0.0% 580 0.0%2007 319 319 0.0% 319 0.0%

Objective Cummulative Functionscenario 1 ( 5 10 10) scenario 2 (10 20 20)

Sensitivity ConclusionSensitivity Conclusion

Because the difference of High Forecasting Total Cost to Medium Forecasting is 7.4 %, High Forecasting WASP Result is Recommended (when there is sufficient fund)

Increasing of total cost with coal price escalation is lower than escalation ratio

11

ConclusionsConclusions

Installed Capacity in 2026 is : 2 812 MW Coal Steam Turbin644 MW Gas Combine Cycle150 MW Oil Combine Cycle100 MW Oil Gas Turbine

Total Candidate Plant added until 2026 (6 Coal Steam Turbin 65 MW; 9 Coal Steam Turbin 200 MW; 3 Gas Combine Cycle 150 MW; 1 Oil Combine Cycle 150 MW; 2 Oil Gas Turbine 50 MW)

Total Cummulative Cost until 2026 is 2 349 M USD and total Energy is 161 151 GWh. {Rp. 136 /kwh (2007’s value)}

Because flexibility operation is needed, Combine Cycle and Gas Turbine should be built by ourselves.

Plan after WASP StudiesPlan after WASP Studies

Determine Plant Location by Load Flow, Short Circuit and Stability Analysis

Calculate new transmission lines, substations and distribution network needed.

Make Financial, and Risk Management Analysis.

12

Company

LOGO

THANK YOUTHANK YOU

1

Study Generation Expansion Planning ofMinahasa SystemBy Ikhsan & Marlon

PT PLN PERSEROWILAYAH SULUTTENGGO

WORKING AREA PLN WIL. SULUTTENGGO

SULUTAREA : 15.271,19 Km2

Population : 2.043.241Customer : 365.556 Plg

GORONTALOArea : 12.215,19 Km2

Population : 888.555Customer : 102.997 Plg

SULTENGArea : 68.033,01 Km2


TOTAL SULUTTENGGOArea : 95.519,39 Km2


SULUTHYDRO : 80 MWGEO THERMAL : 500 MW

GORONTALOHYDRO : 30 MWGEO THERMAL : 9 MW

SULTENGHYDRO : 780 MWGAS : 20 MW

TOTAL SULUTTENGGOHYDRO : 890 MWGEO THERMAL : 509 MWGAS : 20 MW

2

HISTORICAL LOAD CURVE

020406080

100120140

1 10 19 28 37 46 55 64 73 82 91 100 109 118 127 136 145 154 163

HOURS

LOAD

(MW

)

LOAD CURVE

0.00

0.20

0.40

0.60

0.80

1.00

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Time (hours)

Load

(fra

ctio

n of

pea

k)

ENERGY AND LOAD DEMAND FORECAST (SKENARIO DSM)PT PLN (Persero) WILAYAH SULUTENGGO======================== =========== =========== =========== ============ ============ ============ ============ ============ ============ ============

Calendar Year 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025======================== =========== =========== =========== ============ ============ ============ ============ ============ ============ ============

Number of Households (10^3) 1,494.0 1,585.9 1,671.7 1,749.8 1,818.8 1,877.1 1,923.5 1,957.0 1,976.7 1,982.3 - Growth Rate (%) 3.3 2.9 2.6 2.2 1.9 1.5 1.1 0.8 0.4 0.1 Growth of Total GDP (%) 7.7 8.9 8.3 7.3 7.2 7.2 7.2 7.2 7.2 7.2 Electrification Ratio (%) 49.8 52.1 54.6 57.0 60.0 63.6 68.1 73.4 79.8 87.4

Energy Sales (GWh) 1,163.8 1,391.7 1,694.4 2,016.3 2,400.3 2,858.6 3,409.2 4,093.8 5,119.6 6,426.7 - Growth Rate (%) 7.8 10.0 10.3 9.1 9.1 9.1 9.3 9.6 11.9 12.1 -- Residential 730.2 892.1 1,082.6 1,284.2 1,523.1 1,806.6 2,143.3 2,543.3 3,018.7 3,583.8 -- Commercial 216.5 275.5 347.3 425.2 520.1 635.7 799.5 992.8 1,233.9 1,534.8 -- Public 136.2 166.9 203.2 240.8 285.4 338.3 387.9 483.4 605.9 764.1 -- Industrial 98.6 112.3 128.3 145.8 166.6 191.1 212.9 235.6 261.4 290.9

Power Contracted (MVA) 757.0 820.1 896.3 975.0 1,063.9 1,163.3 1,275.5 1,397.4 1,532.9 1,683.4 -- Residential 505.2 557.0 613.4 668.6 729.7 797.2 872.0 955.0 1,047.1 1,149.4 -- Commercial 125.0 140.2 156.9 173.4 191.7 212.1 238.1 265.2 295.5 329.4 -- Public 76.6 80.5 84.7 89.2 94.0 99.1 104.5 110.3 116.4 123.0 -- Industrial 50.2 42.4 41.3 43.8 48.5 54.9 60.8 66.9 73.8 81.7

Number of Customer 796,543.7 882,304.2 975,002.5 1,065,687.8 1,165,610.1 1,276,011.9 1,398,750.3 1,534,197.3 1,684,445.2 1,851,296.3 -- Residential 744,764 825,452 912,543 997,539 1,091,181 1,194,650 1,309,181 1,436,096 1,576,895 1,733,275 -- Commercial 27,867 31,731 35,963 40,145 44,799 49,986 56,355 62,938 70,310 78,568 -- Public 23,244 24,537 25,909 27,364 28,910 30,551 32,294 34,146 36,115 38,207 -- Industrial 669 584 588 639 719 825 920 1,016 1,125 1,247

Total Production (GWh) 3 1,349.0 1,601.7 1,937.3 2,290.7 2,717.3 3,224.8 3,832.5 4,585.4 5,712.4 7,143.0 Energy Requirement (GWh) 1,295.7 1,538.4 1,860.9 2,200.4 2,610.3 3,098.0 3,682.2 4,406.3 5,491.7 6,869.8 Station Use (%) 2) 3.8 3.8 3.8 3.9 3.9 3.9 3.9 3.9 3.9 3.8 T & D Losses (%) 1) 10.2 9.5 8.9 8.4 8.0 7.7 7.4 7.1 6.8 6.4 Load Factor (%) 56.2 57.5 57.6 57.7 57.8 57.9 58.0 58.1 158.1 166.5 Peak Load (MW) 274 318 384 453 537 636 754 900 413 490 ======================== =========== =========== =========== ============ ============ ============ ============ ============ ============ ============


3

ENERGYPEAK LOAD

LOAD FAKTOR

2007 738.3 144.2 58.52008 810.3 158.1 58.52009 1067.6 210.7 57.82010 1176.4 232.1 57.92011 1296.6 255.7 57.92012 1412.0 278.2 57.92013 1538.0 302.8 58.02014 1678.4 330.1 58.02015 1831.6 359.9 58.12016 1998.8 392.4 58.12017 2182.6 428.2 58.22018 2383.6 467.3 58.22019 2618.4 512.8 58.32020 2879.3 563.5 58.32021 3168.0 619.6 58.4

0.0

500.0

1000.0

1500.0

2000.0

2500.0

3000.0

3500.0

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 20210.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

900.0

1000.0

ENERGY PEAK LOAD


EXISTING INSTALL CAPACITY

HYDRO PLANT25.7%

DIESEL OIL RENT9.4%GEOTHERM AL

PP9.4%

DIESEL OIL PP55.5%

DIESEL OIL PP

83.7%

DIESEL OIL RENT16.3%

MINAHASA SYSTEM

GORONTALO SYSTEM

4

FIXSYS & VARSYS INPUT

SEQ. PLANT FUEL CAP. HR BASE HR INCR SPR FOR MAINT. O&M(FIX) O&M(VAR)NO. NAME TYPE MW KCAL/KWH KCAL/KWH % % DAYS $/KWM $/MWH

EXISTING1 BTG1 PLTD HSD 12.0 3160 2180 10 5 30 2.0 8.82 BTG2 PLTD HSD 5.0 3160 2180 10 5 30 2.0 8.83 BTG3 PLTD HSD 10.0 3160 2180 10 5 30 2.0 8.84 BTG4 PLTD HSD 18.0 3160 2180 10 5 30 2.0 8.85 BTG5 PLTD HSD 11.0 3160 2180 10 5 30 2.0 8.86 MDO1 PLTD HSD 1.0 3165 2180 10 5 30 2.0 8.87 MDO2 PLTD HSD 6.0 3160 2180 10 5 30 2.0 8.88 LPA PLTD HSD 10.0 3160 2180 10 5 30 2.0 8.89 KTM1 PLTD HSD 4.0 3160 2180 10 5 30 2.0 8.810 KTM2 PLTD HSD 4.0 3160 2180 10 5 30 2.0 8.811 KTM3 PLTD HSD 3.0 3160 2180 10 5 30 2.0 8.812 INO PLTD HSD 2.0 3160 2180 10 5 30 2.0 8.813 BTN PLTD HSD 2.0 3160 2180 10 5 30 2.0 8.814 SEWA PLTD SEWA 20.0 3150 2180 10 5 30 2.0 8.815 LHD PLTP 40.0 8600 8600 0 8.8 45 3.8 0.9

FIXED ADDITION PLAN16 GE PLTU 12.0 3583 2078 10 8 45 3.3 0.917 TLG PLTU 20.0 3583 2078 10 8 45 3.3 0.9

SEQ. PLANT FUEL CAP. HR BASE HR INCR SPR FOR MAINT. O&M(FIX) O&M(VAR)NO. NAME TYPE MW KCAL/KWH KCAL/KWH % % DAYS $/KWM $/MWH

1 GE20 PLTP 20.0 8600 8600 10 8.8 45 3.8 0.92 ST25 PLTU 25.0 3583 2078 10 12 45 3.3 0.93 ST55 PLTU 55.0 3583 2078 10 12 45 3.0 0.94 GT35 PLTG 35.0 4300 3909 10 5 28 1.0 6.65 FCPP FUEL CELL 10.0 0 0 0 0 0 0.0 175.0

SREENING CURVE ANALYSIS

0

200

400

600

0 10 20 30 40 50 60 70 80 90 100Capacity Factor (%)

Tota

l Ann

ualiz

ed C

ost (

$ / k

W-y

r)

55.6317.99

PLTP (20 MW)

PLTU (25 MW)

PLTU (55 MW)

PLTG (35 MW)

FUEL CELL (10 MW)

5


• Reserve Margin of PLN Standard is 30 % Reserve Margin input of WASP IV range in 20 – 40 %.

• LOLP of Sistem Sumatera is moving to 0.5 % after 2010.

• Cost of Energy Not Served is 0.85 $/kWh.

• Spinning Reserve = Largest Unit in System.

• Discount Rate is 12 % for both local and foreign (capital cost)

• Construction cost of candidates :– (GE20)

• LC : 454 $/KW ; FC : 1060 $/KW– (GT35)

• LC : 89 $/KW ; FC : 354 $/KW– (ST25)

• LC : 478 $/KW ; FC : 1116 $/KW– (ST55)

• LC : 442 $/KW ; FC : 1030 $/KW

DYNPRO INPUT

6

REPORT ABOUT OPTIMAL SOLUTION

SOLUTION VARIABLE ALTERNATIVES BY YEAR

OBJ.FUN. LOLPCONCST SALVAL OPCOST ENSCST TOTAL (CUMM.) %

2026 18796 16223 18030 108 20711 873589 0.461 18 7 8 0 102025 20932 15574 18141 98 23596 852878 0.406 18 7 6 0 102024 16198 10377 18463 135 24419 829282 0.498 14 6 6 0 102023 26407 14544 18704 90 30656 804862 0.322 13 6 5 0 102022 22070 10436 18863 137 30634 774207 0.486 13 6 3 0 102021 22758 9224 18891 133 32558 743573 0.471 13 5 2 0 102020 23012 7980 18892 104 34028 711015 0.391 12 5 1 0 102019 21290 6306 19008 112 34104 676987 0.39 10 4 1 0 102018 21090 5324 18853 115 34735 642883 0.375 9 3 1 0 92017 17997 3863 19026 143 33302 608148 0.424 7 3 1 0 82016 10918 1988 19022 160 28113 574846 0.434 6 3 1 0 62015 32691 5035 19316 66 47039 546733 0.184 5 3 1 0 62014 13696 1779 18734 34 30685 499694 0.107 5 3 0 0 62013 12979 1416 19785 44 31393 469009 0.129 4 3 0 0 62012 17180 1569 21122 168 36901 437616 0.412 4 3 0 0 42011 0 0 21466 110 21577 400716 0.247 3 3 0 0 42010 52219 3296 24146 232 73300 379139 0.451 3 3 0 0 42009 139884 7276 36246 290 169144 305839 0.538 1 3 0 0 32008 11437 487 62093 323 73366 136695 0.831 0 0 0 0 12007 0 0 63318 12 63329 63329 0.012 0 0 0 0 0

ST55 GT35 FCPPPRESENT WORTH COST OF THE YEAR ( K$ )

YEAR GE20 ST25

REPORT ABOUT OPTIMAL SOLUTION

SUMMARY OFFIXED SYSTEM PLUS OPTIMUM SOLUTION

Total Cap. Res. Margin ENERGY Generation CostMW % (GWH) (k$)

2007 203 40.9 902.5 73598.42008 185 17.2 1205.4 48118.12009 269 27.7 1325.5 35900.72010 301 29.6 1462.8 35747.12011 331 29.2 1588.4 39394.32012 351 26.2 1731.6 41329.02013 388 28.1 1885.9 43829.32014 422 28.0 2057.2 50613.72015 477 32.6 2239.7 55824.52016 497 26.9 2445.5 62535.42017 537 25.5 2668.4 69405.62018 587 25.8 2931.3 78372.42019 642 25.2 3222.7 87242.92020 707 25.4 3542.5 97702.42021 782 26.2 3873.9 109270.12022 862 27.2 4239.9 121344.82023 972 31.0 4633.7 134158.22024 1047 29.1 5074.0 147635.72025 1152 29.8 5548.1 164343.5

YEAR

7

Evolution Obj. FunctionDuring the Optimization Proces

873000

873500

874000

874500

875000

875500

876000

876500

1st 2nd 3th 4th 5th 6th 7th

Iteration (Var. Expansion)

Obj

. Fun

c. (M

illio

n)

Plan for future activities on WASP study

• We should update information and technology of power plant because result of WASP depands on accuraty data.

• To get more detail explanation for the participant needs more amount of time and experience.

• Try to find plants that have characteristics low cost, renewable energy, reliable, environmental friendly.

8

pakatuan pakalawiren

1

1electricity For a better life

Generation Expansion Plan of Generation Expansion Plan of

South, South East & West SulawesiSouth, South East & West Sulawesi

Bogor, February 2 2007Bogor, February 2 2007


General Energy and Electricity PictureGeneral Energy and Electricity Picture

2


9876

.68

1023

6.68

1035

9.59

1048

3.91

1060

9.71

1073

7.03

1086

5.87

1099

6.26

1112

8.22

1126

1.76

1153

3.66

1167

2.07

1181

2.13

1195

3.88

1209

7.32

1224

2.49

1238

9.40

1253

8.07

1268

8.53

1284

0.79

1299

4.88

1315

0.82

9577

.97

1013

3.14

9707

.34 11

396.

90

1.35

3.16

1.361.20

1.20

1.871.74

0.00

2000.00

4000.00

6000.00

8000.00

10000.00

12000.00

14000.00

16000.00

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

Popu

latio

n (p

erso

n)

in th

ousa

nds

0.00

1.00

2.00

3.00

4.00

5.00

6.00

Gro

wth

(%)

RealForecastGrowth

P o p u l a t i o nP o p u l a t i o n


-

5,000.0

10,000.0

15,000.0

20,000.0

25,000.0

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

Year

Ener

gy C

onsu

mpt

ion

(GW

h)

Percentage of Energy Consumption in 2006

16%

50%25%

9%

ResidentialCommercialPublicIndustrial

Energy ConsumptionEnergy Consumption

3


Hydro Energy Resources in South & Sout East SulawesiHydro Energy Resources in South & Sout East Sulawesi

Kendari

PLTM Winning( 1,6 MW)

Selayar

MAKASSARPLTA Bilibili (18,7 MW)

PLTA Malea (180MW)

PLTA Bakaru (126 MW)

Raha

Bau-Bau

Maksan/Rensis/Biren

U

PLTM Sawitto (1,62 MW)

Pare Pare

Palopo

Watampone

Bulukumba

Sengkang

KETERANGAN

Potensi PLTA

Potensi PLTM

PLTA Rencana

PLTA/M Existing

PLTA Budong Budong (124MW)

Mamuju

Kolaka

PLTA Kalumpang (11.7MW)

PLTA Mapili (174MW)

PLTA Karama (114.8MW)

PLTA Masuni (110MW)

PLTA Salomongan (81MW)PLTA Masupu (130MW)

PLTA Pokko (53MW)PLTA Bajo (10.8MW)

PLTA Pautu (216MW)PLTA Alla (33MW)

PLTA Bonto Batu (100 MW)PLTA Jalilekko (315 MW)

PLTA Paleleng (113MW)

PLTA Walanae (227 MW)

PLTA Maros (17.3 MW)

PLTA Lalindu (100MW)

PLTA Lasolo (90MW)

PLTA Konaweha (50MW)


Kendari

PLTM Winning( 1,6 MW)

Selayar

PLTM Kadundung (1,6MW)

MAKASSARPLTA Bilibili (18,7 MW)

PLTA Bakaru (126 MW)

Raha

Bau-Bau

Maksan/Rensis/Biren

U

PLTM Campagaya (1 MW)

PLTM Pongbatik (2,6MW)PLTM Kondongan (1,5MW)

PLTM Batu Sitanduk (2,2 MW)

PLTM Ranteballa (2,69MW)

PLTM Usu Malili (4,69MW)PLTM Anoa (3,4 MW)

PLTM Bilalang (2,5MW)

PLTM Mataring (4,4MW)PLTM Tontonan (4,6MW)

PLTM Bilajeng (2,65MW)

PLTM Lewaja (0,44MW)

PLTM Manipi (6,17MW)PLTM Palangka (1,93MW)

PLTM Mikuasi (2,40MW)

PLTM Sabilambo(2,2MW)PLTM Sawitto (1,62 MW)

Pare Pare

Palopo

Watampone

Bulukumba

Sengkang

KETERANGAN

Potensi PLTA

Potensi PLTM

PLTA Rencana

PLTA/M Existing

PLTM Ratelimbong (2,2 MW)

PLTM Rongi (0,8 MW)

PLTM Budong Budong (6.4MW)

Mamuju

Kolaka

PLTM Kalumpang (10.9MW) PLTM Malana (3.5MW)

PLTM Mandar (12.8MW)PLTM Manyaba (3.7MW)

PLTM Siwa (2,7MW)

PLTM Labele (1,09MW)PLTM Camba (6 MW)

PLTM Tombolo (0,92MW)

PLTM Kelara (8,7 MW)

PLTM Kaluku (10.7MW)

PLTM Kembang Subur(5,2MW)PLTM Ulurina (0,75MW)

PLTM Toaha (1,2MW)

PLTM Riorita(1,6MW)PLTM Lapai(9,0MW)

Mini Hydro Energy Resources in South & Sout East Sulawesi

Mini Hydro Energy Resources in South & Sout East Sulawesi

4


NO SITE

NATURAL GAS

1 KAMPUNG BARU, WAJO

2 SAMPI - SAMPI, WAJO

3 WALANGA, WAJO

COAL

1 MAROS

2 BONE

3 PANGKEP

4 BARRU

5 SOPPENG

-

6100000

CADANGAN

TERUKUR

( BSCF )

225,00

31,10

CADANGAN

TERUNJUK

( BSCF )

4500000

-525,000

-

121,20

105,90

2,.50

63,00

7165000

-

-

4,680,000

Natural Gas & Coal Energy Resources in South Sulawesi

Natural Gas & Coal Energy Resources in South Sulawesi


CAPACITY( MW )

SOUTH SULAWESI

1 LUWU 100 - 2002 MAJENE 100 - 2503 POLMAS 100 - 2504 TANA TORAJA 100 - 2505 PINRANG 100 - 2506 SIDRAP 100 - 2507 WAJO 100 - 2508 SINJAI 100 - 2509 BANTAENG 500

SOUTH EAST SULAWESI

1 SENEA KONAWE 102 LAMPEAPI KONAWE 103 WUNGKOLO KONAWE 54 ABUKI KONAWE 205 KEANDI - 1 KONAWE 156 KEANDI - 2 KONAWE 157 LANDAI KONAWE 208 PUUNGKOLO KONAWE 159 LAINEA A SOUTH KONAWE 3010 LAINEA B SOUTH KONAWE 3011 PEMBUINGA KONAWE 1012 OSUNTONDOBU KONAWE 10

NO SITE

Geothermal Energy Resources in South, South East Sulawesi

Geothermal Energy Resources in South, South East Sulawesi

5


Projections of Future Electricity RequirementsProjections of Future Electricity Requirements


0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

High Scenario 7.41% 7.90% 8.50% 9.10% 8.47% 9.46% 7.44% 7.43% 7.42% 7.41% 7.41% 7.41% 7.41% 7.41% 7.41% 7.41%

Low Scenario 7.41% 7.90% 8.50% 9.10% 7.46% 7.45% 6.43% 6.42% 6.41% 6.40% 6.39% 6.39% 6.39% 6.39% 6.39% 6.39%

Average 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01% 5.01%

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Assumption Of GDP Growth(PLN Head Office)

6


-

25,000,000

50,000,000

75,000,000

100,000,000

125,000,000

150,000,000

175,000,000

200,000,000

225,000,000

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024

Agriculture (Real) Agriculture (Forecasting)Mining&Quarrying (Real) Mining&Quarrying (Forecasting)Manufacturing Industries (Real) Manufacturing Industries (Forecasting)Eletric, Gas &Water Supply (Real) Eletric, Gas &Water Supply (Forecasting)Construction (Real) Construction (Forecasting)Trade, Restauran&Hotel (Real) Trade, Restauran&Hotel (Forecasting)Transportation & Communication (Real) Transportation & Communication (Forecasting)Finance, Rent Of Build.&Business Service (Real) Finance, Rent Of Build.&Business Service (Forecasting)Services (Real) Services (Forecasting)Total Include Oil&Gas & Its Product

Growth

4.5%

9.1%

4.9%

7.4%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

2022

2024

Gross Domestic ProductGross Domestic Product


Description of The Existing System & Future Description of The Existing System & Future Options for Electricity SupplyOptions for Electricity Supply

7


Existing Thermal Power PlantExisting Thermal Power Plant

3909390939092400Heat Rate At Minimum Load (kcal/kWh)

1

1.5

9000

2.4

4.8

0

5170

15

30

9

10

2393.6

3

12.5

3.8

2

1

1.5

10000

8.8

1.7

0

7757

15

30

5

10

1757.5

1

14.5

4.3

1

11Pollutant II (%w of fuel)

1.51.5Pollutant I (% w of fuel)

1000010000Heat Value of the Fuel Used

8.88.8Variable O & M Cost (US$/MWh)

1.71.7Fixed O & M Cost (US$/kW-month)

00Foreign Fuel Cost (c/MkCal)

77577757Domestic Fuel Cost (c/MkCal)

3520Maintenance Class (MW)

4040Scheduled Maintenance Day

55Forced Outage Rate (%)

1010Spinning Reserve (%)

2128.42123.4Average Incremental Heat Rate (kcal/kWh)

11Fuel Type

3521Max. Generating Capacity in Each Year (MW)

10.56.4Min. Operating Level in Each Year (MW)

22Number of Unit

Jugo TurbinaTEL 1

WESTCANTEL 2

GETEL 4

ALSTOMTEL 3




1

1.5

10000

8.6

3.1

0

5170

15

30

5

10

2781.7

7

12.6

3.8

4

1

1.5

5300

2.3

2.9

0

493

100

45

7

10

1807.4

5

100

32

0












2292.51231Average Incremental Heat Rate (kcal/kWh)

80Fuel Type

12.550Max. Generating Capacity in Each Year (MW)

615Min. Operating Level in Each Year (MW)

60Number of Unit

MITS & SWDTEL 5

TLAMATEL 6

PLTD RENTTEL 4

CCPPTEL 3

8




1

1.5

11124

0.9

3.1

0

1190

135

60

16

10

1886.4

6

135

40.5

1

1

1.5

11124

1.4

3.1

0

1190

50

45

5

10

1207.8

2

65

45

0













82Fuel Type


4.510Min. Operating Level in Each Year (MW)

41Number of Unit

ALSTOMSKG

ALSTOMSKG1

WARTSILAPARE

INTERIMSKG2




1

1.5

5300

0.9

4.2

0

493

50

45

12

10

1525.3

0

50

20

0

1

1.5

5300

0.9

4.2

0

493

100

45

12

10

1388.1

0

100

50

0


1.5Pollutant I (% w of fuel)


0.9Variable O & M Cost (US$/MWh)

4.2Fixed O & M Cost (US$/kW-month)







1388.1Average Incremental Heat Rate (kcal/kWh)

0Fuel Type



0Number of Unit

PLTU KFFLAKT

PLTU PLNJEN1

PLTU BSWJEN2

9


Existing Hydro Power PlantExisting Hydro Power Plant

CodeUnit Name Operation Retired

Milik PLN HYD1PLTA Bakaru BKR1 126.0 1990 14.8 1 257.5 253.8 126 0.6

2 257.5 253.8 1263 257.5 253.8 1264 257.5 253.8 126

PLTA Bili Bili BILI 20.0 2006 20 13.2 9.6 14 0.618.8 13.7 20.018.8 13.7 20.013.2 9.6 14

PLTA Poso POSO 234.0 2010 55.2 150.0 136.2 100 0.818.8 13.7 2018.8 13.7 2013.16 9.59 14

Installed Capacity

(MW)

Storage Capacity (GWh)

O&M Cost ($/kW-month)

Year

PeriodeInflow

Energy (GWh)

Min. Generation

(GWh)

Avg. Capacity

(MW)


Additions & RetirementsAdditions & Retirements

UNIT 2007 2008 2009 2010 2011 2012 2013 2015

TEL1 -2

TEL2 -1

TEL3 -2

TEL4 -2

TEL5 -4

TEL6

TEL7 +1 -1

TEL8 -6

SKG

SKG1 +1

SKG2 -1

PARE -4

LAKT +2

JEN1 +1 +1

JEN2 +1 +1

BKR1

BILI

POSO +1

YEAR

10


VarsysVarsys Thermal Power PlantThermal Power Plant


1

1.5

11124

3.0

0.66

0

1190

35

22

5

10

1580.6

2

30

15

0

1

1.5

5300

2

3

0

493

20

42

10

10

1525.3

0

25

15

0













00Fuel Type



00Number of Unit

G30 C25 C100C50


VarsysVarsys Hydro Power PlantHydro Power Plant

CodeUnit Name Operation Retired

HYD1PLTA Poko POKO 234.0 2014 55.2 1 150.0 136.2 100 0.6

2 150.0 136.2 1003 150.0 136.2 1004 150.0 136.2 100

HYD2PLTA Bonto Batu BBATU 180.0 2017 1 369.3 326.9 180 0.8

2 369.3 326.9 1803 369.3 326.9 1804 369.3 326.9 180

PLTA Malea MLEA 234.0 2010 55.2 1 150.0 136.2 100 0.82 18.8 13.7 203 18.8 13.7 204 13.16 9.59 14

Installed Capacity

(MW)

Storage Capacity (GWh)

O&M Cost ($/kW-month)

Year

PeriodeInflow Energy (GWh)

Min. Generation

(GWh)

Avg. Capacity

(MW)

11


Scenario AssumptionsScenario Assumptions

1. The fuel of the candidate power plant must be “green energy”.

2. The 2nd priority is the least O & M cost.

3. Diversification energy


System Reliability CriteriaSystem Reliability Criteria

12


System Reliability CriteriaSystem Reliability Criteria

Reserve Margin & Reliability ConstraintsReserve Margin & Reliability Constraints

-

5,000.0

10,000.0

15,000.0

20,000.0

25,000.0

30,000.0

35,000.0

40,000.0

2000 2003 2006 2009 2012 2015 2018 2021 2024

Peak Load + M ax. ReserveM argin (40 %)LOLP Limit (0.274 %)

Peak Load + M in ReseveM argin (15 %)Annual Peak Load


System Reliability Criteria System Reliability Criteria -- ContCont

Spinning ReserveSpinning Reserve

SR = Largest Capacity Block Already

Cost of Cost of EEnergy nergy NNot ot SServederved

Cost = 0.5 US$/kWh

13


Generation Expansion Plan with Generation Expansion Plan with WASP WASP IVIV


DynproDynpro InputInput

14


DynproDynpro Input Input -- ContCont


Optimal SolutionOptimal Solution

15


Sensitivity AnalysesSensitivity Analyses

Sensitivity Analysis demands on the external and internal factor

For Example :

1. Government Policy about fuel price, interest rate, GDP Growt & escalation

2. Hydrology3. Technology4. Diversification Energy5. Least Cost Model

Case :

The management of the utility makes a rule that the minimum capacity of the power plant is more than 10 % of the peak load in a system. The peak Load of South Sulawesi is 445 MW in 2006. So, it is analysed if the 25 MW Coal Power Plant wouldn’t be in the system.


Sensitivity Analyses Sensitivity Analyses -- ContCont

Dynpro report of the case without 25 MW Coal Power Plant

16


Conclusion & RecommendationsConclusion & Recommendations

Conclusions :

1. WASP could help the management for making decision.2. The Objectif Function Cummulative of the case is US$ 2749472. While the

objective function system with 25 MW is US$ 2674720 .

Recommedations :

1. WASP should be aplicated in the sistem planning of all PLN’s region.

2. It is recommendated to the decision maker to consider operating25 MW Coal Power Plant because the cost of operating 25 MW Coal Power Plant is cheaper than “without” 25 MW Coal Power Plant.


Plan for the Future Activities Plan for the Future Activities on the WASP Studyon the WASP Study

1. All participants need a forum for changing information about WASP problem.

2. We want to make standart of some parameter which is used in WASP

17


Terima Kasih

Losari Beach 2006

1

Generation Expansion Planning of SumateraElectricity for a better life

PT PLN (PERSERO)P3B SUMATERA

Sumatera Interconnection System

Malaysia

JAWA

PLTG

BENGKULU

KULIM

PIP

S.EMPAT

SUMBAR

N A D

SUMUT

RIAU

P. Selincah

Aur Duri

JAMBI

PLTG

BETUNG

TL.KELAPA

BORANG

L.LINGGAU

KERAMASANMARIANA

PRABUMULIH

SP.TIGA

BK.ASAMLAHAT

BATURAJAP.ALAM

SUMSEL

LAMPUNG

BANGKO

MUARO BUNGO

2006Peak Load Sumbagut : 1.051,1 MW Peak Load Sumbagsel : 1.372,8 MWInstalled Capacity : 3.480,2 MW

PLN Pembangkitan Sumbagut : 1.579,55 MWPLN Pembangjkitan Sumbagsel : 1.638,36 MWPT Inalum : 50,00 MWIPP : 150,00 MWRental : 110,14 MW

Energy Production (until TW III 2006 ) : 10.896,48 GWhGeneration Mix 2006 (until TW III) :

Coal : 18,42 %Gas : 22,14 %Oil Fuel : 39,86 %Hydro : 19,58 %

Transformer Cap. : 4.949 MVATrans. Lenght : 8.809,87 kms ( Length of Sumatera : 1.800 km )

U

2007

Notes :Notes :EksistingEksisting 70 kV70 kVEksistingEksisting 150 kV150 kVEksistingEksisting 275 kV (275 kV (OperasiOperasi 150 kV)150 kV)PlaningPlaning 150 kV150 kV

2

Fuel Mix of Sumatera

PLTG

KULIM

PIP

S.EMPAT

P. Selincah

Aur Duri

PLTG

BETUNG

TL.KELAPA

BORANG

L.LINGGAU

KERAMASANMARIANA

PRABUMULIH

SP.TIGA

BK.ASAMLAHAT

BATURAJAP.ALAM

BANGKO

MUARO BUNGO

Oil Fuel7.10%

Gas29.30%

Coal33.40%

Hydro30.20%

Oil Fuel80.00%

Hydro6.60%Gas

13.40%

PLTG HSD2.60%

PLTU Gas1.30%PLTG Gas

11.60%PLTD IDO0.80%

PLTD HSD3.00%

PLTD MFO0.70%

PLTGU Gas16.30%

PLTU Bbara33.40%

PLTA30.20%

PLTD HSD3.50%

PLTU MFO13.40%PLTG HSD

4.60%

PLTA6.60%

PLTGU HSD, 58.50%

PLTU Gas0.04%

PLTGU Gas, 13.30%

SumbagselSumbagselSumbagutSumbagut

Fuel Mix of Sumatera

PLTG

KULIM

PIP

S.EMPAT

P. Selincah

Aur Duri

PLTG

BETUNG

TL.KELAPA

BORANG

L.LINGGAU

KERAMASANMARIANA

PRABUMULIH

SP.TIGA

BK.ASAMLAHAT

BATURAJAP.ALAM

BANGKO

MUARO BUNGO

Coal18.42%

Gas22.14%

Oil Fuel39.86%

Hydro19.58%

3

PROVINCE CUSTOMER 2007

NAD 749,240 Sumut 2,322,209 Sumbar 827,268 Riau 640,354 S2JB 1,318,407 Lampung 832,364

P3B Sumatera 6,689,842

Sumatera in Number

PROVINCE POPULATION 2007

NAD 3,955,122 Sumut 12,599,356 Sumbar 4,735,085 Riau 5,334,530 S2JB 11,003,162 Lampung 7,145,990

SUMATERA 44,773,244

Number of population

Polulation Growth : 5 %

Number of customer

Customer Growth : 5 %PEAK DEMAND 2007-2026

Growth : 9.9 %

6,516.8

2,724.9

16,234

-

2,000.0

4,000.0

6,000.0

8,000.0

10,000.0

12,000.0

14,000.0

16,000.0

18,000.0

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026

MW

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.00 0.17 0.35 0.52 0.70 0.87

Import : 45 MW, 6 hoursPeak Periode

Load Duration Curve

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.00 0.17 0.35 0.52 0.70 0.87

Export : 15 MW, 18 hoursOff-Peak Periode

0.00

0.50

1.00

0.0000 0.1812 0.3625 0.5437 0.7250 0.9062

Original LDC

0.0

0.5

1.0

0.0000 0.1812 0.3625 0.5437 0.7250 0.9062

Final LDC

4

Existing System

7% 1%13%

4%

24%6%

9%

10%

26%

STO STG STC CCG CCO GTG GTO DIE HYD

Sumbagut Sumbagsel TOTALSteam Coal PP 0 - 460.0 460.0 Steam Turbine Oil PP 1 260.0 - 260.0 Steam Turbine Gas PP 2 - 25.0 25.0 Gas Turbine Oil PP 3 123.2 203.0 326.2 Gas Turbine Gas PP 4 - 223.5 223.5 Combined Cycle Oil PP 5 817.8 - 817.8 Combined Cycle Gas PP 6 - 150.0 150.0 Diesel Oil PP 7 119.8 231.6 351.4 Hydro PP 139.5 726.9 866.4

TOTAL 1,460.3 1,559.9 3,020.2

Type Of Power Plant Installed Capacity (MW)No. (WASP)

Additions and Retirements of Power PlantsNO. OF PLANT NAME 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026

3 BLW1 -44 BLW2 -15 BLW3 -16 GLG1 -47 GLG2 -38 TTKN -69 LBTA -110 RNT1 -114 OMBL -215 PLMO -316 JMB1 -221 KRS1 -222 KRS2 -223 KRS3 -130 BKSM -2 -1 -134 TRH1 -143 TRHN 1 1 144 LBAG 1 145 MLBH 246 RANC 247 CRTI 1 149 GMGN 250 SGTI 151 KRS5 253 KRS4 154 PLT2 155 SMBR 1 156 SUMT 3 357 BJSR 1 158 BTRJ 1 159 MENM 160 ULUB 2 261 SARL 2 1

5

Energy Resources of Sumatera

POTENSI GAS ALAM

BATU BARA

1. Sumut ( 2.016,841 BSCF )2. Riau ( 300 juta SCF ) ==> ( 300 MMSCF )3. Jambi ( 1.011BSCF )4. Grisik - Sumsel ( 1.479,62 BSCF )5. Prabumulih - Sumsel ( 1.421,69 BSCF )

1. Cerenti - Riau ( 1.675,6 juta ton )2. Sawah Lunto - Sumbar ( 205,9 juta Ton )3. Muara Enim - Sumsel ( 9.538 juta Ton )4. Musi Banyu Asin - Sumsel ( 3.313 juta Ton )5. Jambi ( 367 juta Ton )6. Bengkulu Selatan ( 13,867 juta Ton )7. Bengkulu Utara ( 30,22 juta Ton )8. Blambangan Umpu - Lampung ( 131,27 juta Ton )9. Kec. Aceh Barat - NAD ( 1.074,543 juta Ton )

PANAS BUMI

POTENSI HIDRO

1. Sarulla - Sumut ( 1200 MWe )2. Kab. Pasunan- Sumbar ( 365 MWe )3. Kab. Solok - Sumbar ( 325 MWe )4. Kerinci - Jambi ( 100 MWe )5. Lahat - Sumsel ( 470 MWe )6. OKU - Sumsel (47 MWe )7. Bukit Daun - Bengkulu ( 250 MWe )8. Gedang Hululais -Bengkulu ( 500 MWe )9. Desa Tambang Sawah - Bengkulu ( 400 MWe )10. Ulu Belu - Lampung ( 400 MWe )11. Suoh - Lampung ( 300 MWe )12. Sekincau - Lampung ( 130 MWe )

14. Sibayak - Sumut ( 100 MWe )15. Kab. Aceh Besar - NAD ( 50 MWe )16. Sabang - NAD ( 25 MWe )

1. Sumut ( 690MW )2. Riau ( 763 MW )3. Batang Maninjau - Jambi ( 300 MW )4. Muara Enim ( 319,8 MW )5. Ketahun ( 84 MW )6. Musi ( 210 MW )7. Peusangan - NAD ( 86,4 MW )8. Tampur - NAD ( 428 MW )

13. G. Raja Basa - Lampung ( 40MWe )

1

14

1

1

2

2

3

2

2

1

5

3

3

4

4

4

4

5

53

6

5 6

6

7

7

9

8

8

712

10

11 138

7

15

16

8

9

-

200.00

400.00

600.00

800.00

1,000.00

1,200.00

0 10 20 30 40 50 60 70 80 90 100

COAL200 CC150 GT100 COAL600

VARSYS of WASP IV (Sumatera)

The Candidate of plants- (STC2) Steam Turbine 200 MW- (GT10) Gas Turbine 100 MW- (CC15) Combined Cycle 150 MW- (STC6) Steam Turbine 600 MW- (ASH3) Hydro Plant 154 MW- (MRGN) Hydro Plant 350 MW

Scenario assumption of varsys(ASH3) available year in 2013(MRGN) available year in 2013

-

200.00

400.00

0 10 20 30 40

6


Reserve Margin input of WASP IV range in 15 – 45 %

LOLP of Sistem Sumatera is moving to 1 day/year (0.274%) after 2009.

Assumption Cost of Energy Not Served is 0.85 $/kWh

Spinning Reserve = Largest Unit in system

DYNPRO Input Data

Base year for discounting and escalation calculation is 2007

Discount Rate is 12 % for both local and foreign capital cost.

Construction cost of candidates :(STC2)

• LC : 175 $/KW ; FC : 932 $/KW(GT10)

• LC : 89 $/KW ; FC : 354 $/KW(CC15)

• LC : 245 $/KW ; FC : 571 $/KW(STC6)

• LC : 233 $/KW ; FC : 640 $/KW

7

Sensitivity Analyses

LOLP

1 day/year in 2009 - 2026, because it takes at least 2 years for power plant candidates to construct from the beginning of the study.

Reserve Margin

2007 – 2010 range in 15 – 45 %

ongoing & committed power plant already operate in this periode.

2011 – 2026 range in 15 – 40 %.

Optimal Solution Report

1st Plant required of the system is GT10 in 2009.The LOLP of 2009 – 2026 less then 1 day / year (0.274%). (Reliable)2013 only takes 1 Hydro Plant

(ASH3) to fit the energy required even 2013 has 2 candidates of Hydro PlantsObjective Function Cumulative on 2026 is 9.870 Billion $US

NAME STC2 GT10 CC15 STC6 HYD1SIZE (MW) 200 100 150 600 0

YEAR %LOLP RESM CAP2007 0.611 19.8 02008 0.436 20.6 02009 0.181 26.8 100 12010 0.002 43.7 02011 0.103 27.3 02012 0.249 23.7 150 12013 0.128 26.3 154 12014 0.212 21.8 750 2 12015 0.265 21.9 600 32016 0.244 22.7 700 3 12017 0.215 23.5 950 3 2 12018 0.259 23.6 800 42019 0.196 24.8 1000 1 62020 0.242 26.6 1200 22021 0.274 27.9 1200 22022 0.128 32.6 1800 32023 0.264 30.5 1200 22024 0.255 31.6 1800 32025 0.262 30.2 1600 10 12026 0.260 30.1 2100 10 1

TOTALS 16104 15 15 18 14 2

SEE ALSO FIXED SYSTEM REPORT FOR OTHER ADDITIONS OR RETIREMENTSFOR DETAILS OF INDIVIDUAL UNITS OR PROJECTS SEE VARIABLE SYSTEM REPORT

ANNUAL ADDITIONS: CAPACITY(MW) AND NUMBER OF UNITS OR PROJECTSOPTIMUM SOLUTION

8

Conclusions and Recomendations

WASP is one of reliable tools to analyze and optimize generationexpansion planning.

To get a good result required accurate data and sensitive analysis (What if question).

To get more detail explanation for the participant needs more amount of time and experience.

Plan for future activities on WASP study

Try to find plants that have characteristics low cost, renewableenergy, reliable, environmental friendly.

Make a forum of WASP study to discuss techniques, updateinformation and technology of generation power planning.

9

THANK YOU

Presented by :

1. Taufiq Fahrudin2. Aris Sofian H.3. Nurul Hidayat4. Ainanto Nindyo

ADICA Training Report - JICA WASP 2007

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