Nam Theun 2 Hydro Power Project Regional Economic …siteresources.worldbank.org/INTLAOPRD/491761-1094074854903/... · Least-Cost Analysis Draft Final Report ... NT2 Nam Theun 2 hydro

report to

The World Bank

Robert Vernstrom consulting economist Bangkok, Thailand 662 2520186 fax 662 2532176 [email protected]

Nam Theun 2 Hydro Power Project

Regional Economic Least-Cost Analysis

Draft Final Report

June 2004

The findings, interpretations and conclusions contained in this report are those of the author and do not represent the views of the IBRD/IDA or of the Executive Directors of IBRD/IDA, the Electricity Generating Authority of Thailand (EGAT), or the Nam Theun 2 Power Company Limited (NTPC).

The author wishes to thank the Electricity Generating Authority ofThailand (EGAT), M.L. Chanaphun Kridakorn (recently retired DeputyGovernor) and Mr. Narongsak Vichetpan, Deputy Governor for Policy andPlanning, for the extensive support of their experienced professional team.In particular, we wish to thank the System Planning Division for their ableassistance. Special thanks are due to Mr. Sahust Pratuknukul (now Headof the Energy Economics Division), Ms. Petchara Rompruek (Head ofPower Development Planning), and their staff (including ManopTanglakmongkol, Nimit Sujiratanavimol, Thanawadee Deetae, andYoothapong Tancharoen, among others), without whose support theStudy would not have been possible. Countless hours were spent indiscussing and refining assumptions used in the Study, and many additionalhours were expended to complete the generation expansion planningscenarios discussed in this report.

The demand forecasting sections of this report were prepared with theexpert assistance of Dr. Tienchai Chongpeerapien, President of Businessand Economic Research Associates (BERA), a Bangkok consultant withmany years of experience working on load forecasting issues for the Thaipower sector.

Special thanks are due to Mr. Mark Segal, Mr. Darayes Mehta, and Mr.Robert Mertz, World Bank supervisors and advisors to the project, fortheir professional guidance and tireless support.

TABLE OF CONTENTS

Executive Summary i

1 Introduction 7

1.1 Background 71.2 Study Objective 81.3 Organization of the Report 9

2 System Demand Assumptions 10

2.1 Overview of the Forecasting Methodology 102.2 Comparison of Forecast Results 172.3 Load Forecast Adopted for this Study 21

3 System Supply Assumptions 23

3.1 Installed and Planned System Capacity 233.2 Thermal Expansion Candidates 263.3 Fuel Price Projections 273.4 Thermal Candidate Plant Screening Analysis 293.5 NT2 – The Alternative Expansion Candidate 29

4 Methodology for the Study 33

4.1 The Least Cost Planning Methodology 334.1.1 The PROSCREEN II Model 334.1.2 How PROSCREEN is Applied in this Study 344.2 Cost-Risk Analysis Modeling Framework 35

5 Economic Evaluation 39

5.1 Economic Planning Assumptions 395.1.1 Basic Economic Assumptions 395.1.2 System Characteristics 405.1.3 NT2 Planning Assumptions for the Economic Analysis 415.2 Base Case Results 435.3 Cost-Risk Analysis 445.4 Sensitivity Analysis 485.4.1 Delay in Commercial Operation 485.4.2 Changes in the Forecasts of Key Variables 49

6 Conclusion 55

A1 Terms of Reference 57

A2 Thailand Demand Forecast 65

A3 Fuel Price Assumptions 71

A4 Detailed Plant Data (Existing System) 79

A5 How PROSCREEN Works 85

A6 Economic Base Case with NT2 – Detail 89

TABLES AND FIGURES

Table S-1. Economic Cost-Risk Analysis Results v

Table 1. Current Forecast Methods by Company and Class 12

Table 2. National GDP Growth Assumptions 13

Table 3. Integrated National Electricity Conservation Program 16

Table 4. National Conservation Program – Alternative View 17

Table 5. Historical Energy Requirements Forecasts (GWh) 18

Table 6. Historical Peak Demand Forecasts (MW) 19

Table 7. Implied Income Elasticity of Energy Requirements Forecasts 20

Table 8. Historical Forecast Accuracy 1/ 20

Table 9. Recommended Load Forecast for this Study 22

Table 10. Installed and Purchased Capacity (as of March 2003) 24

Table 11. Committed Plant Additions (after March 2003) 25

Table 12. Schedule of Retirements (FY2003-14) 26

Table 13. Candidate Power Plants for the Study (2003 Prices) 27

Table 14. Base Case Fuel Price Forecasts 28

Table 15. Screening Analysis of EGAT Candidate Plants 30

Table 16. The Cost-Risk Framework 36

Table 17. Capital Costs of NT2 (constant US$2003, 10% discount rate) 42

Table 18. Base Case “with NT2” 44

Table 19. Base Case “without NT2” 45

Table 20. Economic Cost Risk Analysis Results 47

Table 21. Sensitivity of Base Case to Delay of Commercial Operation 49

Table 22. Sensitivity of Results to the Load Forecast 50

Table 23. Sensitivity of Results to the Price of Natural Gas 51

Table 24. Sensitivity to Changes in NT2 Capital Cost 52

Table 25. Economic Cost-Risk Sensitivity Test 54

Table A2-1. EGAT Total Generation Requirement Forecast 66

Table A2-2. EGAT Total Sales Forecast 67

Table A2-3. MEA Purchases and Sales Forecast by Customer Class 68

Table A2-4. PEA Purchases and Sales Forecast by Customer Class 69

Table A3-1. Economic Fuel Price Projections (constant US$2003) 72

Table A4-1. Existing Installed Generating Capacity (as of Sep-03) 80

Table A4-2. Existing Hydro Power Plant Data 81

Table A4-3. Existing and Committed Small Power Producers (as of Sep-03) 82

Table A4-4. Schedule of Planned Plant Retirements 83

Table A6-1. Demand and Supply Balance – Economic Base Case with NT2 90

Table A6-2. System Costs by Plant Group – Economic Base Case with NT2 92

Table A6-3. Fuel Use by Type – Economic Base Case with NT2 94

Table A6-4. Fuel Type by Individual Plant – Economic Base Case with NT2 96

LIST OF ACRONYMS

AAGR average annual growth rateBOI Board of InvestmentBTU British Thermal Unit (standard measure of fuel heat content)CCGT combined cycle gas turbineCIDA Canadian International Development AgencyCOD commercial operation dateDAEDE Department of Alternative Energy Development and Efficiency (formerly

DEDP)DEDP Department of Economic Development and Promotion (now DAEDE)E&P exploration and productionEDP exploration, development, productionEGAT Electricity Generating Authority of ThailandEIA Energy Information Administration (U.S. Department of Energy)EPPO Energy Policy and Planning Office (formerly NEPO)ESI electricity supply industryGDP gross domestic productGHG greenhouse gasGMS Greater Mekong Sub-regionGOL Government of the Lao People’s Democratic RepublicGOT Government of the Kingdom of ThailandGPA gas purchase agreementGRP gross regional productGT gas turbineGWh gigawatt hour (one million kWh)HFO heavy fuel oilIBRD International Bank for Reconstruction and Development (official name

for the World Bank)IMF International Monetary FundIPP independent power producerkWh kilowatt hourLER low economic recovery (Sep-98 forecast scenario)LFCR levelized fixed charge rateLOLP loss of load probabilityMEA Metropolitan Electricity AuthorityMER medium economic recovery (Sep-98 forecast scenario)MM millionMOU memorandum of understandingMUV United Nations index of the unit value of manufactured exportsMW megawatt (one thousand kW)MWh megawatt hour (one thousand kWh)NEPO National Energy Policy Office (now EPPO)NESDB National Economic and Social Development Board

NPL non-performing loanNPV net present valueNSO National Statistics OfficeNT2 Nam Theun 2 hydro power projectNTPC Nam Theun Power CompanyPCF Prototype Carbon Fund administered by the World BankPDP power development program of EGATPE primary energy (required purchases from NT2, 6 a.m. to 10 p.m.)PEA Provincial Electricity AuthorityPPA power purchase agreementPTT Petroleum Authority of ThailandPV present valueRER rapid economic recovery (Sep-98 forecast scenario)RM reserve marginR/P reserves to production ratioSCF standard cubic foot (approximately 1000 Btu)SE1 secondary energy 1 (required purchases from NT2, 10 p.m. to 6 a.m.)SE2 secondary energy 2 (optional purchases from NT2, 10 p.m. to 6 a.m.)SPP small power producerTDRI Thailand Development Research InstituteTHB Thai Baht; in this study, US$1.00 = 42 THBTLFS Thailand Load Forecast Sub-committeeWACC weighted average cost of capitalWB World BankWCD World Commission on Dams

Executive Summary i

EXECUTIVE SUMMARY

S-1 Background and ObjectivesNam Theun 2 (NT2) is a planned hydroelectric project of a thousand megawatts inthe Lao PDR to be developed by a private company (NTPC). The Government ofLaos (GOL) is a 25 percent shareholder in NTPC. Upon anticipated commencementof commercial operation in 2009 (FY2010), NTPC will sell fixed amounts of power atpre-negotiated prices to the Electricity Generating Authority of Thailand (EGAT).

A World Bank Partial Risk Guarantee to NTPC is under consideration. This study isa component of the Bank’s on-going due diligence process. The work is a complementto an earlier study, the Thailand Power Scenario Study (TPSS),1 developed incooperation with the Electricity Authority of Thailand (EGAT), utilizing EGAT’s least-cost planning tools. That analysis was conducted from a commercial perspective.Further, the study assessed NT2 from the perspective of Thailand rather than theregion as a whole.

The World Bank carried out a detailed review of the TPSS, and concluded that theBank's evaluation policies also required an economic analysis assessing the project froma regional perspective. Therefore, the review also highlighted the need for astructured “cost-risk” analysis (see Section S-2 below). The current study reports thefindings of the analysis conducted to achieve these expanded objectives.

Chapter 2 presents the demand forecast of the regional power system which hasbeen adopted for the current study. Chapter 3 presents detailed background on theexisting power supply system, and on candidate plants for future system expansion.

S-2 Study Objective and MethodologyThe study outcome is to be determined by means of a results profile known as the“Cost-Risk Framework”. This profile – explained in detail in Chapter 4 – provides forcalculating the probability-weighted present value (PV) costs of either implementingor not implementing NT2 for commercial operation in FY2010, given the interplay ofseveral major uncertain factors – project cost, long-term demand for electricity, andlong-term economic value of natural gas as well as the suggested probabilities ofoccurrence for Base Case, Low and High estimates of these variables. The differencebetween the probability weighted PV cost of implementing the project in FY2010versus not implementing it at all is the decision criteria for this analysis. A lower netpresent value (NPV) “with NT2” would indicate that the project is an efficienteconomic investment for the regional power market.

1 Robert Vernstrom, Thailand Power Scenario Study, Bangkok, March 2003. The World Bank financedand supervised the study.

Executive Summary i i

The specific steps undertaken to complete the cost-risk analysis are summarized in thefollowing paragraphs:

Determine Base Case, Low, and High real economic values for the three keyuncertainties expected to have the most significant potential impact on theeconomic decision to develop NT2 – (i) project cost, (ii) growth rate ofelectricity demand, and (iii) the economic value of natural gas.

Define a probability of occurrence for each state (Base Case, Low, andHigh) of each variable.

Run the PROSCREEN expansion planning model under Economic BaseCase assumptions with NT2 as a candidate competing for a place in the least-cost expansion plan from its earliest expected commercial operation date ofFY2010. This initial analysis added NT2 to the system in October 2009,i.e., it specified that the least-cost expansion plan included NT2commencing operation in October 2009. This date was therefore fixed forall subsequent "with NT2" model runs to conform to the logic of thedecision matrix (the decision being whether to develop NT2 for commercialoperation in October 2009 or not to do so).

Run the PROSCREEN generation expansion planning model with NT2commencing commercial operation in FY2010 for all combinations of theabove-defined uncertainties. The PROSCREEN “objective function” (i.e.,basis for comparison of results) is the present value of future investmentand operating costs over the Study Period.

Re-run each of the defined scenarios without NT2 so that demand must beserved from alternative resources.

Calculate the probability-weighted present value of costs for the “withNT2” and “without NT2” scenario groups.

Subtract the probability-weighted result “with NT2” from the result“without NT2” to determine the Study outcome.

To complete the Cost-Risk Framework, a total of 18 scenario runs are required, 9with NT2 and 9 without NT2. These scenarios are formed from combinations of twoplanning variables – power demand and natural gas price. Three cases – Base, Low,and High – are used for each of these variables. The 9 scenarios run with NT2 wereexpanded to 27 scenarios for the economic assessment by combining manually thethree cases for the construction cost of NT2 with the results of the other scenarios.

The Base Case analysis is characterized as follows:

The Base Case load forecast is Thailand’s official Base Case of August 2002(see Chapter 2), augmented by a Lao PDR domestic load of 75 MW and300 GWh.

Executive Summary i i i

The reliability criterion is a reserve margin of 15 percent.

The existing system corresponds to the summary in Table 10.

All “committed plants” as identified in Table 11 are presumed to commencecommercial operation according to schedule.

The schedule for plant retirements follows the assumptions detailed in Table12.

NT2 (995 MW) is added to the system in FY2010 (October 2009) in the“with NT2” scenarios.

All other plants – including plants proposed for reconditioning and allgeneric expansion options (see Table 13) – are modeled as candidateswhich must compete for a place in the least cost economic plan.

Generation of existing plants and selected candidates is dispatched byPROSCREEN according to the following rules:

All non-thermal generation – notably domestic hydro plants and Laoimports – is dispatched first. With the exception of EGAT’s ownhydro capacity, each of these resources is modeled as a separatetransaction, defined from contractual purchase price and operatingconstraints.

NT2 energy is dispatched in two parts according to the monthlyvariation reported in Chapter 3, one to provide peak-period energyand a second to provide off-peak energy.

All thermal generation – the majority of the entire system – is subjectto economic dispatch, and run only when it is lowest cost.Exceptions are small power producers (SPPs), which are assumedbased on EGAT experience to run at an average 80 percent capacityfactor.

S-3 Results of the Economic AssessmentThe Base Case economic analysis tells us that NT2 should be included in the region’sleast cost generation expansion plan. The accumulated present value of real resource

Executive Summary i v

savings to the region over the entire Study Period (FY2003-14 and beyond2) totalsUS$277 million at 2003 prices.3

The project outcome is determined by a cost-risk analysis, designed to determinewhether the same decision is justified given the high probability that future events willdiverge from Base Case assumptions.

The key decision variables for this study are defined in the study TOR (see AppendixA1). They are:

Capital cost of NT2. The World Bank has specified a cost range of +30percent (High capital cost) and –30 percent (Low capital cost); thesevalues are reported in Table 17.

Regional demand forecast. The World Bank has specified a very wide range inorder to reflect the Bank's long-term experience with demand forecastperformance;4 the regional High and Low demand forecasts are summarizedin Table 9.

Natural gas price forecast. The World Bank commissioned a separatelyprepared forecast of natural gas prices taking into account region-specificpricing conventions with indexation factors based on its own worldpetroleum product price projections, with particular emphasis on the priceof natural gas since gas is the most competitive alternative fuel. The BaseCase projections are presented in Table 14; High and Low scenarios arereported in Appendix A3.

The TOR has further specified the probability of occurrence for each of the Base,High and Low case assumptions regarding demand, natural gas value and project cost.Each “expected” (i.e., Base Case) assumption value has a probability of 50 percent inthe cost-risk matrix, with the High and Low assumption values assigned a probabilityof 25 percent each.

The results of the cost-risk analysis are summarized in Table S-1. The analysisconcludes that the probability-weighted accumulated present value of real resourcesavings to the region as a result of the development of NT2 is US$269 million (i.e. veryclose to the Base Case present value of US$277 derived without incorporating

2 The Study Period includes both the planning period (FY2003-14) and an "end effects" analysis whichutilizes sophisticated programming techniques to analyze differences between alternatives (e.g., due todifferent lives and operating characteristics) beyond the planning period. Without an end-effectsanalysis, results may be biased against commissioning capital-intensive units near the end of theplanning period.

3 It should be noted that the costs and benefits being evaluated in this report are confined to thepower sector; when other studies dealing with environmental and social costs are completed they willbe combined with the results of this report to produce an overall economic statement on theproject’s economic efficiency. The US$ 277 million represents a ‘savings” since the least-cost planwithout NT2 would come at greater total cost.

4 This experience also reflects extreme and unexpected events, such as the Asian economic crisis of1997, but that is not the primary consideration for the wide range adopted.

Executive Summary v

probabilistic outcomes for key variables). In present value terms, these savings areequivalent to US$0.012 for each kWh sold from the NT2 project.

Table S-1. Economic Cost-Risk Analysis Results

A. Present Values WITH NT2:Savings by

Case Probability Case Probability Case Probability Case Present Value Probability Scenarioh 0.25 h 0.25 h 0.25 hhh 61,720 0.01563 193 h 0.25 h 0.25 m 0.50 hhm 55,621 0.03125 125 h 0.25 h 0.25 l 0.25 hhl 51,490 0.01563 63 h 0.25 m 0.50 h 0.25 hmh 48,568 0.03125 177 h 0.25 m 0.50 m 0.50 hmm 43,855 0.06250 103 h 0.25 m 0.50 l 0.25 hml 40,684 0.03125 52 h 0.25 l 0.25 h 0.25 hlh 36,631 0.01563 139 h 0.25 l 0.25 m 0.50 hlm 33,184 0.03125 23 h 0.25 l 0.25 l 0.25 hll 30,821 0.01563 (63) m 0.50 h 0.25 h 0.25 mhh 61,546 0.03125 367 m 0.50 h 0.25 m 0.50 mhm 55,447 0.06250 299 m 0.50 h 0.25 l 0.25 mhl 51,316 0.03125 237 m 0.50 m 0.50 h 0.25 mmh 48,385 0.06250 360 m 0.50 m 0.50 m 0.50 mmm 43,681 0.12500 277 m 0.50 m 0.50 l 0.25 mml 40,510 0.06250 226 m 0.50 l 0.25 h 0.25 mlh 36,457 0.03125 313 m 0.50 l 0.25 m 0.50 mlm 33,010 0.06250 197 m 0.50 l 0.25 l 0.25 mll 30,647 0.03125 111 l 0.25 h 0.25 h 0.25 lhh 61,371 0.01563 542 l 0.25 h 0.25 m 0.50 lhm 55,272 0.03125 474 l 0.25 h 0.25 l 0.25 lhl 51,141 0.01563 412 l 0.25 m 0.50 h 0.25 lmh 48,210 0.03125 535 l 0.25 m 0.50 m 0.50 lmm 43,506 0.06250 452 l 0.25 m 0.50 l 0.25 lml 40,335 0.03125 401 l 0.25 l 0.25 h 0.25 llh 36,282 0.01563 488 l 0.25 l 0.25 m 0.50 llm 32,835 0.03125 372 l 0.25 l 0.25 l 0.25 lll 30,472 0.01563 286

A. Probability-weighted Present Value WITH NT2 44,337 1.00000

B. Present Values WITHOUT NT2:

Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 hh 61,913 0.06250 h 0.25 m 0.50 hm 55,746 0.12500 h 0.25 l 0.25 hl 51,553 0.06250 m 0.50 h 0.25 mh 48,745 0.12500 m 0.50 m 0.50 mm 43,958 0.25000 m 0.50 l 0.25 ml 40,736 0.12500 l 0.25 h 0.25 lh 36,770 0.06250 l 0.25 m 0.50 lm 33,207 0.12500 l 0.25 l 0.25 ll 30,758 0.06250

B. Probability-weighted Present Value WITHOUT NT2 44,606 1.00000

Probability-weighted PV Savings (Cost) WITH NT2 269 (Result A minus Result B; 2003 USD million)

POWER DEMAND GAS PRICE

CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million)

SCENARIO RESULTS (2003 USD million)

I n t roduc t ion 7

1 INTRODUCTION

1.1 Background

Nam Theun 2 (NT2) is a planned hydroelectric project of a thousand megawatts5 inthe Lao PDR to be developed by a private company (NTPC). The Government ofLaos (GOL) is a 25 percent shareholder in NTPC. Upon anticipated commencementof commercial operation in 2009 (FY2010), NTPC will sell fixed amounts of power atpre-negotiated prices to the Electricity Generating Authority of Thailand (EGAT).While NT2 will be operated and maintained by NTPC, the facility will be under thefull dispatch control of EGAT.

The World Bank has supported the GOL in the development of the NT2 Project. Infact, a World Bank Partial Risk Guarantee to NTPC is under consideration.

This study is a component of the Bank’s on-going due diligence process. The work isa complement to an earlier study, the Thailand Power Scenario Study (TPSS),6

developed in cooperation with the Electricity Authority of Thailand (EGAT), utilizingEGAT’s least-cost planning tools. That analysis was conducted from a commercialperspective. Further, the study assessed NT2 from the perspective of Thailand ratherthan the region as a whole.

The World Bank carried out a detailed review of the TPSS, and concluded thatadditional work was needed to satisfy the Bank's operational guidelines on theeconomic evaluation of electric power projects. These guidelines stipulate that,

…for every investment project, Bank staff conducts economic analysis to determinewhether the project creates more net benefits to the economy than other mutuallyexclusive options for the use of the resources in question.

…all flows are measured in terms of opportunity costs and benefits, using 'shadowprices,' and after adjustments for inflation...

5 To avoid possible confusion, we wish to clarify the “exact” capacity of NT2. The developer (NTPC)identifies the capacity as 995 MW (plus 75 MW dedicated to Lao domestic consumption), the rating ofthe installed turbines. EGAT, however, designates the plant as 920 MW, the estimated minimummonthly delivery. The difference between the two numbers is (i) transmission losses to the purchase-point at the Thai border, and (ii) what one EGAT official calls a “margin of security” for the sake ofsystem reliability, so that EGAT can be certain of this minimum level of delivery. The contract permitsEGAT to request more than 100 percent of this capacity with permission from NTPC. For purposesof this study, which adopts a regional perspective, NT2 is defined as a 995 MW plant (i.e., 920 MWdelivered to Thailand plus 75 MW Lao domestic load). The contract is priced and largely defined interms of GWh, hence the MW accounting definition is not important for purposes of this analysis.

6 Robert Vernstrom, Thailand Power Scenario Study, Bangkok, March 2003. The World Bank financedand supervised the study.

I n t roduc t ion 8

…the Bank finances only those supply facilities and demand-management measures thathelp meet economically efficient demand at the least economic cost.

Unless the economic analysis is fully consistent with Bank policy, the review concluded,there could be lingering uncertainty as to whether the methodology adopted for theTPSS truly reflects the economic results that would occur using the Bank's ownevaluation policies and assessing the project from a regional perspective. Therefore,the review also highlighted the need for a structured “cost-risk” analysis whichconsiders alternative outlooks on demand, natural gas prices and NT2 constructioncosts, as well as pointing out some other analytical matters that warrant further work.

The current study reports the findings of the analysis conducted to achieve theseexpanded objectives. Briefly, the study includes a thorough comparison of the realresource cost to the regional7 economy of power sector development “with” and“without” NT2. Results incorporate a probabilistic “cost-risk” assessment of thiscomparison over a range of project uncertainties, including capital costs, future gasprices, and Thai load growth.

The Terms of Reference presented in Appendix A1 detail the Bank's requirements forthe analysis.

1.2 Study Objective

The study outcome is to be determined by means of a results profile known as the“Cost-Risk Framework”. This profile – explained in detail in Chapter 4 – provides forcalculating the probability-weighted present value (PV) costs of either implementingor not implementing NT2 for commercial operation in FY2010, given the interplay ofseveral major uncertain factors – project cost, long-term demand for electricity, andlong-term economic value of natural gas as well as the suggested probabilities ofoccurrence for Base Case, Low and High estimates of these variables. The differencebetween the probability weighted PV cost of implementing the project in FY2010versus not implementing it at all is the decision criteria for this analysis. A lower netpresent value (NPV) “with NT2” would indicate that the project is an acceptableeconomic investment for the regional power market.

It should be noted that the power sector costs and benefits being evaluated in thisreport include only environmental and social costs which the project sponsor iscommitted to finance, but does not include any other potential environmental costsand benefits. When other studies dealing with these factors are completed they willbe combined with the results of this report to produce an overall economic statementon the project’s economic efficiency.

7 Throughout this study, the word “regional” refers Lao PDR and Thailand.

I n t roduc t ion 9

1.3 Organization of the Report

This study is above all a careful review of anticipated electricity demand and supply inthe region, and of the role of NT2 in meeting future requirements.

The next two chapters present the basic demand and supply assumptions adoptedfor the analysis. Chapter 2 reports on the methods used to forecast the powermarket, and an analysis of results. Chapter 3 summarizes the existing supply system,as well as the cost of candidate plants which could provide future supply.

Chapter 4 presents the methodological approach for the study.

Chapter 5 presents the economic least-cost analysis and results. The chapter beginswith the Base Case evaluation of the project, and then continues with a systematic,probabilistic “cost-risk” assessment of the role of NT2 in light of a broad range offuture planning uncertainties.

Chapter 6 presents a summary of results, and the conclusion of the study.

System Demand Assumptions 1 0

2 SYSTEM DEMAND ASSUMPTIONS

Load forecasting in Thailand is a collaborative effort of the major stakeholders. TheThailand Load Forecast Sub-committee (TLFS)8 considers all methodological issues,and reviews the work of participating agencies before integrating results into anational load forecast.

The methodologies applied in forecasting have been developed and refined for over adecade, originally with international consulting assistance funded by CIDA, theCanadian development agency. In fact, methods are continuously evolving, as theTLFS strives to refine its techniques with each succeeding forecast. The most recentload forecast of the TLFS available for the current analysis was issued in August 2002;it has been used in this report.

Section 2.1 presents an overview of the forecasting methodology. Section 2.2 is areview of historical forecasting performance. Finally, Section 2.3 recommends BaseCase, High and Low demand forecasts for use in this study.

2.1 Overview of the Forecasting Methodology

The national load forecast employs at least five distinct methodologies, with theappropriate technique varying by

distribution company (MEA in greater Bangkok, and PEA in the rest of thecountry)

customer class (i.e., residential, small and large business, industrial, etc.), and

forecast horizon (i.e., short-term or long-term).

Four methods are used for energy forecasting. Two of these methods might bedescribed as “bottom up” in that they depend on detailed knowledge of end-users,while two others might be characterized as “top down,” since they depend onmacroeconomic trends. There is also an independent method for forecasting peakdemand. These methods are briefly summarized in the following paragraphs.

End-Use Model. Consumption for residential customers throughoutThailand is derived from comprehensive surveys of dwelling types byincome, and appliance utilization in each. Forecasts depend on growth in

8 The committee is comprised of representatives from EPPO (formerly NEPO), EGAT, MEA, PEA,DAEDE (formerly DEDP), NESDB, the National Statistics Office (NSO), the Federation of ThaiIndustries, the Thailand Chamber of Commerce, the Association of Thai Power Generators, and theThailand Development and Research Institute (TDRI).


number of households, appliance saturation, and expected applianceefficiency improvement.

Floor Space Model. Short-term (less than 5 years) consumption forlarge business (commercial customers > 30 kW) in the MEA service territoryis forecast based on available data on floor space by type of building. Dataon building stock is adjusted for factors such as demolition, constructiondeferral, occupancy rate, etc. Total consumption is then calculated fromsurvey data on energy use within each type of building. Again, factors areapplied to incorporate efficiency improvement into the forecast.

Energy Intensity Model. Gross domestic product (GDP) is carefullydisaggregated by region and by business sector so that energy consumptionrelationships by sector can be evaluated. Total consumption is derivedbased on historical consumption per unit of gross regional product (GRP),and the forecast growth in GRP by sector. The energy intensity model isused where “first hand” sources (e.g., Board of Expansion data, and surveysof available floor space) are unavailable, especially for longer-termforecasting.

Econometric Regression. When class consumption patterns are notattributed to clearly identifiable relationships (e.g., appliance usage, floorspace, sector energy intensity), econometric regression is used to define therelationship. The method is particularly applied to small business, and toother classes in which users have widely diverse consumptioncharacteristics.

Peak Demand Model. The TLFS has developed substantial loadresearch data by customer group over recent years through extensivesurveys, and applies this information to project demand from energyforecasts developed using the foregoing methods. The number of customerswithin each class is forecast based on regression analysis, and daily loadcurves derived from the load research data are used to forecast coincidentand non-coincident peak for each customer group. Peak losses are alsoforecast via regression equations for each customer class.

Table 1 summarizes the methods currently applied to each customer class.

Economic Growth (Income) Considerations in the Forecast

Growth in electricity demand is highly correlated to medium and long-term economicgrowth prospects (especially economic growth per consuming unit, e.g. per householdor per unit of industrial output). Each of the methods used by the TLFS considerincome, either directly or indirectly. For example, the end-use model forecasts end-use consumption by the stock of dwellings classed by income type. Similarly, the floorspace model directly measures economic expansion among large businesses. Theenergy intensity model relates energy requirements to anticipated growth in valueadded by business sector. Economic regression analysis typically incorporates an


income term (e.g., gross regional product by business sector) into its forecastequations.

Table 1. Current Forecast Methods by Company and Class

Customer Class MEA PEA

Residential End-Use model Same approach, by region

Industry Short-term: First-hand sources(e.g., BOI, applications forservice, targeted surveys)Long-term: Energy intensitymodel (energy intensity per unitof value added)

Same approach, by region

Large Business(>30 kW)

Short-term: Floor Space modelLong-term: Energy intensitymodel by business sector

Energy intensity model bybusiness sector by region

Small Business Econometric regression Same approach, by region

Other Classes Econometric regression Same approach

Peak Demand Daily load curves by customergroup applied to regression-derived customer forecasts byclass. System coincident peakderived from coincident peak ofeach class.

Same approach

Notes: (1) All methods incorporate adjustments for efficiency improvement over time; e.g. end-usemodels assume progressive improvement in efficiency of household appliances, and energyintensity models assume increasing energy efficiency per unit of value added.(2) EGAT direct customers are forecast by individual firm survey.

Thus, the economic forecasts driving Thailand’s national load forecast are a crucialfactor in their accuracy. The Government of Thailand (GOT), through its NationalEconomic and Social Development Board (NESDB), forecasts anticipated nationalGDP, but typically only for five years (i.e., the next national plan). For long-termtrends, the TLFS has relied on the Thailand Development and Research Institute(TDRI) to project economic growth and to disaggregate the national GDP forecast byregion and by business sector. TDRI was hired to develop these trends for theSeptember 1998 forecast, and is revising economic projections which will be applied infuture load forecasts. TDRI applies a very complex model to develop these results.9

9 TDRI uses a “computable general equilibrium model (CGE)” for making macroeconomic projections.This is the same type of model that NESDB uses to prepare official economic forecasts for the five-yearnational plans. The model is very large and requires considerable time to readjust and calibrate a newforecast series. The most time-consuming part of the projection process, however, is to allocate the15-year macroeconomic forecast into MEA and PEA regions and the corresponding customer sub-groups specified by TLFS. For this task, TDRI needs to conduct detailed surveys in order to establishbaseline information for each regional forecast. The TLFS requires long tem economic projections


Sep-97 Sep-01Year Actual IMF/GOT RER MER LER NESDB

1992 8.2%1993 8.5%1994 8.5%1995 8.8%1996 5.7%1997 -1.5% 2.5%1998 -10.8% 3.5%1999 4.2% 5.5% 2.4% 0.6% -0.5%2000 4.3% 6.5% 5.4% 3.7% 2.5%2001 1.8% 6.5% 6.1% 4.4% 3.3%2002 6.4% 4.8% 3.7% 3.5%2003 6.4% 4.9% 3.8% 4.0%2004 6.1% 4.7% 3.6% 5.0%2005 5.9% 4.6% 3.5% 5.0%2006 5.9% 4.6% 3.6% 5.5%2007 6.2% 4.9% 3.9%2008 6.0% 4.7% 3.8%2009 5.8% 4.7% 3.9%2010 5.6% 4.6% 3.8%2011 5.3% 4.6% 3.8%

Average Annual Growth (%)2001-06 6.1% 4.7% 3.6% 4.6%2006-11 5.8% 4.7% 3.8%

Annual GDP Forecast Error (%, for full-year forecasts after 1997) 2/1998 14.3%1999 1.3% -1.8% -3.6% -4.8%2000 2.2% 1.1% -0.6% -1.8%2001 4.7% 4.3% 2.6% 1.5%

1/ RER - rapid economic recovery, MER - medium economic recovery, LER - low economic recovery 2/ Differernce between actual and forecast GDP growth rates.

Sep-98 Forecasts Assumptions 1/

Table 2. National GDP Growth Assumptions

National economic projections applied for recent load forecasts are compared inTable 2.

The August 2002 load forecast adopted the Sep-98 (MER) economic outlook for theperiod following NESDB’s near-term prediction (i.e., 2006-11). The TLFS noted thatthe 4.7% average annual GDP growth under MER for the Ninth Plan (2001-06) wasvery close to the NESDB’s projection of 4.6% for the same period. Furthermore, theTLFS believed that the average long term annual growth rate of 4.7% assumed in theSep-98 (MER) was still a reasonable estimate. Therefore, the committee decided to

broken down at this high level of detail in order to run its end-use load forecast model. As a result,the process is very time consuming and costly.

While we have no reason to doubt the methodology employed by TDRI, or the accuracy of its results,the approach has the disadvantage that a new demand forecast cannot be easily produced in responseto alternative views of economic growth. Given the difficulty that all economists have experienced inforecasting national (and international) economic growth in recent years, this slow response timecould be disadvantageous.


adopt the NESDB short-term and MER long-term economic outlooks for the Aug-02load forecast.10

Recent economic growth trends – and medium-term forecasts – are more optimisticthan the foregoing assumptions reflect. Actual 2003 growth will be approximately 6percent; the GOV is projecting 2004 growth of about 8 percent. The World Bank iscautiously optimistic, expecting 6 percent growth in 2004, but expressing severalconcerns regarding the sustainability of high growth in the medium-term.

Specifically, the Bank notes that private consumption has been the chief driver ofrecent expansion, and that private investment's contribution to growth has been lessthan in previous economic recoveries and remains lower than many other countries inthe region. Corporate access to credit has been constrained by a cautious bankingsector and slow structural reforms. Export growth has been relatively strong,however, an appreciating exchange rate and capacity constraints could restrain thisgrowth. Further, the rate of non-performing loans (NPLs) has not declined and re-entry NPLs have increased. Progress in banking and capital market reform, and in legalreform, has been limited. In summary, World Bank economists argue that Thailand willneed to improve its competitiveness and productivity in order to convert the currentrecovery into sustained high growth over the medium-term.11

Price Considerations in the Forecast

The load forecasting methodologies do not explicitly consider price as an independentvariable in forecasting demand. However, the impacts of historical price changes arecaptured in the forecasts. For example, surveys for the end-use forecasts reflect pricechanges through adjustments in appliance usage and saturation. Floor space modelscapture changes in energy use per unit of floor space which may have occurred inpart due to changes in electricity price.

Thus price is indirectly reflected in current forecasting methodologies.

Energy Conservation in the Forecast

In addition to incorporating adjustments for energy efficiency improvement in eachclass load forecast, the August 2002 Base Case is further adjusted downward toreflect the impact of a group of on-going electric energy conservation programs beingundertaken by various GOT agencies, including EPPO (formerly NEPO), DAEDE(formerly DEDP), and EGAT.

Table 3 summarizes the complete package of conservation activities; this packagerepresents the official plan of the GOT adopted by the Cabinet. The final lines of thetable show the conservation program included in the Aug-02 Base Case forecast. 10 While it is beyond the scope of the current study to produce a new load forecast, it should benoted that recent economic performance of Thailand has exceeded forecasts, and analysts aregenerally optimistic regarding medium-term economic growth prospects.

11 The views expressed in these paragraphs are based on Consultant discussions with macroeconomistsat the World Bank office in Bangkok, and opinions presented in that office's Economic Monitorpublished in October 2003.


(The forecast excludes 2,516 GWh of conservation savings achieved by FY2002;TLFS has assumed that this conservation is already reflected in base year consumptiondata.)

In fact, the TLFS has been very concerned about the effect of energy efficiencyimprovement on future electricity demand, and established a special working group tomake a detailed assessment of the various conservation-related programs. Thefindings of that group indicated that official estimates were probably too high, for thefollowing reasons:

Only about 15% of the planned electricity demand reduction in the next 10years is expected to come from mandatory programs where the set targetsare reasonable. The remaining 85% reduction in electricity demand isanticipated to come from numerous voluntary programs. The success ofthese programs will depend on their implementation procedures andconsumer willingness to participate. These factors are not yet clearlydefined.

Several programs have missed implementation deadlines, and many areexpected to face further delay. Other programs (e.g., switching streetlighting off late at night) have faced opposition from highway safetyengineers, and may not be implemented.

After considerable debate, the TLFS decided to reduce the amount of conservedelectricity by nearly 30% in the year 2011 for the Aug-02 load forecast. (An evengreater cut was considered, but it was decided to give the programs an opportunityto achieve targeted progress. A more critical evaluation will be incorporated intosubsequent load forecasts.) The forecast incorporates a total conservation savings of982 MW by 2011.


ResponsibleAgency 2003 2004 2005 2006 2007 2008 2009 2010 2011

1. GOT Cabinet Programs EPPO 1/ 1,670 1,785 1,907 2,038 2,175 2,317 2,481 2,637 2,797

2. Mandatory Programs DAEDE 2/ 559 848 1,064 1,280 1,280 1,280 1,280 1,280 1,280 - Buildings 193 330 394 458 458 458 458 458 458 - Factories 156 280 404 529 529 529 529 529 529 - Government Buildings 210 238 266 293 293 293 293 293 293

3. SME Programs EPPO 271 612 1,068 1,332 1,597 1,864 2,132 2,401 2,672 - Value Engineering 48 112 176 240 304 368 432 496 560 - SME Standards 131 306 480 655 830 1,005 1,179 1,354 1,529 - Research Projects 92 194 412 437 463 491 521 551 583

4. Residential Programs EPPO 656 838 987 1,144 1,386 1,523 1,667 1,820 1,922 - HH Design Standards 198 252 313 381 457 539 629 727 834 - EGAT DSM Program EGAT 429 409 389 369 349 328 308 288 268 - MEP Program 3/ - 125 210 295 435 495 555 615 615 - Efficiency Labeling 29 52 76 99 145 160 175 190 205

5. Recycling Progam EPPO 19 22 35 67 101 116 121 138 158

Total Planned Conservation Program 3,174 4,105 5,061 5,862 6,540 7,101 7,682 8,277 8,830

Conservation in Aug-02 Forecast - GWh 4/ 658 1,589 2,545 3,346 4,024 4,585 5,166 5,761 6,314 Conservation in Aug-02 Forecast - MW 5/ 102 247 396 520 626 713 803 896 982 % of planned conservation program 21% 39% 50% 57% 62% 65% 67% 70% 72%

1/ Energy Policy and Planning Office (formerly NEPO).2/ Department of Alternative Energy Development and Efficiency (formerly DEDP).3/ Minimum efficiency standards for household appliances.4/ Aug-02 forecast excluded 2,516 GWh assumed to have already been realized in the forecast base year (FY 2002).5/ Estimate based on system load factor; a conservative assumption since some programs target load shifting and peak reduction.

ProgramPlanned Conservation Savings (GWh)

Table 3. Integrated National Electricity Conservation Program

The conservation program outlined in Table 3 is part of a 10-year master plandeveloped by responsible GOT agencies, which emphasized technical/economicpotential rather than financial/legal constraints.12

Table 4 presents an informal “order of magnitude” alternative view of conservationpotential based on the Consultant’s discussions with conservation planners. Thisalternative scenario is presented for discussion purposes only, intended to crudelyquantify the widely held opinion that the program in Table 3 may be unduly optimisticwith regard to potential savings. The alternative view in Table 4 suggests that onlyhalf of the conservation assumed in the Aug-02 forecast may be achieved by 2011,and perhaps three-quarters of that target by 2016. In other words, the load forecastcurrently used by EGAT almost certainly assumes greater conservation than theelectricity sector will actually achieve over the forecast period.13

12 Most of the funding for energy conservation will come from the “ENCON Fund’, which is financedthrough a targeted tax on petroleum products of THB 0.40 per liter.

13 Unlike some of the other programs, EGAT’s own DSM Program has been proceeding according toplan. The program is funded directly by EGAT (vs. the ENCON Fund), and conservation savings areprojected to exceed the level forecast in the consolidated national conservation plan (Table 3). InTable 4, we have adopted EGAT’s forecast of DSM savings through FY2006, and have conservativelyassumed no increases thereafter.


Table 4. National Conservation Program – Alternative View

EPPO is currently developing a more realistic program guided on funding and otherlimitations. As of the publication of this study, a conservation action plan is not yetfinalized. Significantly, however, EPPO reports Cabinet-level approval for a majorreduction in national energy consumption, expressed as a target energy elasticity of1.0 versus the current level of 1.3 or more (see Section 2.2). Although this is aworthwhile objective, it is perhaps premature to presume the schedule for meeting ofthis goal, given that no action plan is in place, and no performance record exists fromwhich to define a realistic pace for achieving the target.

It is important to put these conservation savings in perspective. The total savings aresignificant – on the order of 1,000 MW by 2011 (Table 3) or 2016 (Table 4).However, these capacity and associated energy savings represent less than one-year’snational demand growth (even when assuming a low demand forecast); hence, theydo not obviate the need for continued expansion of the generating system.

2.2 Comparison of Forecast Results

The TLFS has prepared a total of 12 national load forecasts since 1993. Tables 5 and6 summarize the Energy Requirements and Peak Demand projections from many ofthese forecasts, excluding those prepared immediately before and after the onslaughtof the Asian economic crisis in July 1997. The crisis, with its profound impact on theThai economy, including electricity consumption, rendered earlier forecasts irrelevantfor future planning.14 Even the first “post-crisis” forecast (September 1997) provednaively optimistic in its outlook for economic recovery. (Thai forecasters, likeeconomists everywhere, simply did not foresee the depth and duration of the crisis.)It can be observed that the forecasts in the tables are progressively lower.

14 The highest forecast (April 1996) projected peak demand in fiscal year 2002 to be over 40 percent(7,000 MW) above the recorded peak of 16,681 MW. That same forecast also projected demand in2011 to exceed 42,000 MW, 45% more than the August 2002 forecast.

ResponsibleAgency 2003 2004 2005 2006 2007 2008 2009 2010 2011 2016

1. GOT Cabinet Programs EPPO 1,670 1,785 1,907 2,038 2,175 2,317 2,481 2,637 2,797 3,599

2. Mandatory Programs DAEDE 20 146 272 398 524 650 776 902 1,028 1,280

3. SME Programs EPPO 54 122 214 266 319 373 426 480 534 921

4. Residential Programs EPPO 586 588 726 905 1,068 1,237 1,491 1,643 1,800 2,684 - incl. EGAT DSM Prgm EGAT 536 488 546 530 530 530 530 530 530 530

5. Recycling Progam EPPO 19 22 35 67 101 116 121 138 158 257

Total Conservation - Alternative View 2,350 2,664 3,153 3,675 4,188 4,694 5,296 5,800 6,318 8,740

Alternative Conservation Forecast - GWh 3/ 292 606 1,095 1,617 2,129 2,635 3,238 3,742 4,259 6,682 Alternative Conservation Forecast - MW 4/ 45 94 170 251 331 410 504 582 662 1,039 % of planned conservation program 9% 15% 22% 28% 33% 37% 42% 45% 48% 76% % of Aug-02 conservation forecast 44% 38% 43% 48% 53% 57% 63% 65% 67% 106%

1/ Informal Consultant estimate based on discussions with participants.2/ Assuming slower start-up (1-2 year delay), slower growth (original program or scaled back program spread over 10 years), but continuing growth after 2011.3/ Excludes 2,058 GWh assumed to have already been realized in the forecast base year (FY 2002).4/ Estimate based on system load factor; a conservative assumption since some programs target load shifting and peak reduction.

ProgramPlanned Conservation Savings (GWh) 1/, 2/


Table 5. Historical Energy Requirements Forecasts (GWh)

The forecast of September 1998 was much more successful at incorporating thepotential implications of the crisis on electricity consumption. It included threescenarios based on anticipated speed of economic recovery – rapid (RER), medium(MER), and low (LER). Two subsequent forecasts (February 2001 and August 2002)have refined these results in response to revised economic growth scenarios from theGovernment of Thailand (NESDB), and incorporated conservation program planning.

The dramatic changes in near-term expectations regarding national electricityrequirements are obvious in Tables 5 and 6. But it is equally interesting to observefrom the tables that expected average annual growth rates for medium to long-termprojections show little variation. For the period 2001-06, the annual rate of growthin demand is between 5.9 and 6.5 percent in five of the eight forecasts. Two others –the Sep-98 RER (“rapid economic recovery”) and LER (“low economic recovery”) –were intended as High and Low scenarios to bracket a medium (“MER”) forecast. Forthe period 2006-11, five forecasts project average annual generation growth between5.7 and 6.3 percent.

Fiscal Actual Jun-93 Dec-94 Oct-95 Feb-01 Aug-02Year GWh RER MER LER Base Base

1993 62,180 62,797 1994 69,651 69,407 1995 78,880 76,388 78,023 1996 85,924 83,896 85,571 89,375 1997 92,725 91,178 92,879 97,849 1998 92,134 99,334 100,383 105,938 1999 90,414 106,891 108,160 114,029 96,904 93,178 91,834 2000 96,781 115,136 116,795 122,289 103,709 97,858 94,570 2001 103,165 124,158 126,025 131,698 111,475 103,685 98,108 103,946 2002 108,383 132,330 134,041 140,032 120,148 110,436 102,429 110,945 108,036 2003 141,138 142,849 149,076 129,080 117,341 106,947 118,540 114,754 2004 150,283 152,529 158,989 138,647 124,532 111,736 126,449 122,024 2005 159,668 162,187 168,894 149,439 132,228 116,980 134,794 130,232 2006 169,545 171,745 178,706 161,378 141,300 122,756 143,748 139,000 2007 179,533 181,745 188,881 174,490 151,322 129,738 152,743 147,835 2008 190,380 193,505 200,739 188,005 162,438 137,996 162,438 157,064 2009 201,642 204,956 212,213 200,949 173,532 146,979 173,532 168,004 2010 213,395 216,428 223,645 214,215 184,213 156,032 184,213 178,079 2011 225,720 228,445 235,564 227,993 194,930 164,381 194,930 188,446 2012 206,660 199,378 2013 219,134 211,146 2014 232,106 223,437 2015 245,948 236,364 2016 260,262 249,878

Average Annual Growth (%)2001-06 6.4% 6.4% 6.3% 7.7% 6.4% 4.6% 6.7% 6.1%2006-11 5.9% 5.9% 5.7% 7.2% 6.6% 6.0% 6.3% 6.3%2011-16 6.0% 5.8%

Forecasts by Publication DateSep-98


Table 6. Historical Peak Demand Forecasts (MW)

This similarity of result is surprising, given that each forecast started from a differentbase and with different macroeconomic expectations (the associated national GDPforecast, as reported in Table 2). Table 7 shows the simple income (GDP) elasticity ofdemand implied by each energy requirements forecast.15

These elasticities have typically ranged from 1.30 to 1.40, with many individual yearelasticities falling outside this narrow band.16 Considering that income elasticity wasnot a basis for energy forecasting of many consumer categories, the implied elasticitiesare surprisingly stable across these recent forecasts.17 Interestingly, however, thehighest of these forecasts (Sep-98 RER) had lower-than-average income elasticities,and the lowest forecast (Sep-98 LER) has somewhat higher-than-average incomeelasticities, in later forecast years. This confirms that income elasticities were not thebasis for these forecasts.

15 Clearly, a far more meaningful elasticity measure would be income per consuming unit by customerclass (e.g., electricity consumption growth per consuming unit of industrial value added per companyor per commercial establishment). We have used a far less detailed approach, since our objective isonly to confirm to reasonableness of the Base Case forecast.

16 The TLFS has independently estimated income (GDP) elasticity of demand. We understand thatthese unpublished investigations estimated an average income elasticity of about 1.4.

17 The actual experience reported in Table 7 for the period 1995-2001 tells a somewhat differentstory; electricity demand appears to have been far more stable than the performance of the incomevariables, causing remarkable variance of the implied elasticity from year to year.

Fiscal Actual Jun-93 Dec-94 Oct-95 Feb-01 Aug-02Year MW RER MER LER Base Base

1993 9,730 9,978 1994 10,709 10,975 1995 12,268 11,993 11,993 1996 13,311 13,103 13,103 13,637 1997 14,506 14,193 14,193 14,892 1998 14,180 15,315 15,315 16,075 1999 13,712 16,446 16,446 17,268 14,972 14,499 14,287 2000 14,918 17,685 17,685 18,527 16,037 15,254 14,762 2001 16,126 19,029 19,029 19,899 17,286 16,214 15,398 16,184 2002 16,681 20,237 20,237 21,139 18,678 17,308 16,150 17,388 16,700 2003 21,440 21,440 22,368 20,042 18,399 16,892 18,587 17,843 2004 22,690 22,690 23,654 21,597 19,611 17,746 19,913 19,029 2005 23,997 23,997 24,995 23,223 20,818 18,588 21,222 20,295 2006 25,371 25,371 26,392 24,958 22,168 19,467 22,552 21,648 2007 26,835 26,835 27,894 26,950 23,728 20,575 23,951 23,020 2008 28,409 28,409 29,467 29,021 25,450 21,861 25,450 24,450 2009 30,044 30,044 31,073 31,090 27,232 23,268 27,232 26,143 2010 31,749 31,749 32,756 33,132 28,912 24,671 28,912 27,711 2011 33,532 33,532 34,509 35,216 30,578 25,951 30,587 29,321 2012 32,405 31,014 2013 34,352 32,842 2014 36,366 34,743 2015 38,519 36,754 2016 40,699 38,851

Average Annual Growth (%)2001-06 5.9% 5.9% 5.8% 7.6% 6.5% 4.8% 6.9% 6.1%2006-11 5.7% 5.7% 5.5% 7.1% 6.6% 5.9% 6.3% 6.3%2011-16 5.9% 5.8%

Sep-98Forecasts by Publication Date


Table 7. Implied Income Elasticity of Energy Requirements Forecasts

Table 8 summarizes forecast performance in terms of accuracy for each year afterpublication, excluding the “crisis years.” With few exceptions, demand and energyforecasts have been accurate to within a couple of percent in their early years.(Perhaps the error observed in the October 1995 energy forecast was an earlywarning of the pending crisis.) This performance suggests that the short-termforecasting models employed by the TLFS have performed well. In the longer term,the dramatic distortions of the 1997 Asian economic crisis make it difficult to assessthe accuracy of Thailand’s forecasting models under a period of more stable marketconditions.

Table 8. Historical Forecast Accuracy 1 /

Years Jun-93 Dec-94 Oct-95 Feb-01Forecast RER MER LER Base

Energy Requirements 1 -3.2% -1.1% 4.0% 7.2% 3.1% 1.6% 0.8%2 -2.4% -0.4% 5.5% 7.2% 1.1% -2.3% 2.4%3 -1.7% 0.2% 8.1% 0.5% -4.9%4 10.9% 1.9% -5.5%

Peak Demand1 -2.2% -2.2% 2.4% 9.2% 5.7% 4.2% 0.4%2 -1.6% -1.6% 2.7% 7.5% 2.3% -1.0% 4.2%3 -2.2% -2.2% 7.2% 0.5% -4.5%4 12.0% 3.8% -3.2%

1/ Percent by which forecast exceeded (fell short of) requirement in each full yearafter publication.

Sep-98Forecasts by Publication Date

Years Jun-93 Dec-94 Oct-95 Feb-01Forecast RER MER LER Base

Energy Requirements Forecasts1 -3.2% -1.1% 4.0% 7.2% 3.1% 1.6% 0.8%2 -2.4% -0.4% 5.5% 7.2% 1.1% -2.3% 2.4%3 -1.7% 0.2% 8.1% 0.5% -4.9%4 10.9% 1.9% -5.5%

Peak Demand Forecasts1 -2.2% -2.2% 2.4% 9.2% 5.7% 4.2% 0.4%2 -1.6% -1.6% 2.7% 7.5% 2.3% -1.0% 4.2%3 -2.2% -2.2% 7.2% 0.5% -4.5%4 12.0% 3.8% -3.2%

1/ Cumulative percent by which forecast exceeded (fell short of) actual requirementin each full year after publication.

Forecasts by Publication DateSep-98

Feb-01 Aug-02Year Actual RER MER LER Base Base

1994 1.41 1995 1.51 1996 1.57 1997 n/m1998 0.06 1999 n/m2000 1.64 1.30 1.37 1.18 2001 3.66 1.23 1.35 1.14 2002 1.23 1.36 1.20 1.92 2003 1.17 1.28 1.16 1.71 1.55 2004 1.22 1.31 1.25 1.33 1.27 2005 1.33 1.36 1.35 1.32 1.35 2006 1.35 1.49 1.39 1.21 1.22 2007 1.30 1.46 1.46 1.29 1.31 2008 1.29 1.55 1.66 1.34 1.32 2009 1.18 1.44 1.69 1.44 1.47 2010 1.19 1.33 1.62 1.33 1.30 2011 1.21 1.28 1.43 1.28 1.28

Average Annual Growth (%)2001-06 1.53 1.26 1.36 1.27 1.50 1.34 2006-11 1.24 1.41 1.57 1.34 1.33

1/ Energy forecasts adopted Sep-98 (MER) economic growth forecast after 2006.n/m - not meaningful

Sep-98 Forecasts Assumptions


2.3 Load Forecast Adopted for this Study

The August 2002 Base Case load forecast18 is the planning basis for EGAT’s PDP2003, and is used for the current study. It is a technically and methodologically soundbasis for future system planning.

Due to the unique regional perspective of the present study, there are differencesbetween the Base Case forecast used in this report and the August 2002 loadforecast. Specifically, the Base Case forecast includes Lao domestic load which isassumed to grow enough to utilize its allocated share of total NT2 project output.Thus, starting in FY2010, the August 2002 forecast is increased by 300 GWh of netgeneration and 75 MW of peak demand.19

Low and High demand forecasts, as requested by the World Bank, reflect a wide bandof future loads. Based on the Bank's extensive experience with long-term loadforecast accuracy around the world, the Bank specified the Low and High Casedemand forecasts to be symmetrically keyed off the Base Case forecast using thefollowing equations, reflecting the percentage gap between these forecasts that theBank considers appropriate by year 10 of the forecast period:

(1+grL)^10 = 0.75*(1+grB)^10 [for the low case]

(1+grH)^10 = 1.25*(1+grB)^10 [for the high case]

where “grB” means Base Case growth rate of demand, “grL” means Low Casegrowth rate of demand and “grH” means High Case growth rate of demand.

Thus, the Low Case forecast is set to a growth rate at which the capacity and energyrequirements in FY2012 are 75 percent of the Base Case requirements. Symmetrically,the High Case load forecast in FY2012 is 125 percent of the Base Case requirement.The constant annual growth rates implied by these results are applied to all forecastyears.

Table 9 summarizes all three forecast scenarios adopted for this study. The averageannual growth rates of these scenarios range from a Low of about 3.4 percent to aHigh of nearly 9 percent. This wide band subsumes the range of futures that havebeen projected in the recent past: (i) the GOT's very optimistic economic growthand energy conservation targets, (ii) the World Bank's more cautious growthperspective coupled with slower energy elasticity improvement, and (iii) the slower

18 For readers who would like to review the August 2002 forecast in greater detail, complete resultsby customer class for MEA, PEA, and direct customers of EGAT are reported in Appendix A2.

19 A necessary corollary of this assumption is that Laos’ alternative to NT2 for meeting this portion ofits demand would be import of electricity from Thailand. Further, this load increment is presumed tomirror the Thai load curve, a simplifying assumption that avoids separate modeling of the Lao system.Given planned changes to that system over coming years (including regional grid integration andpossible introduction of TOU tariffs to flatten the curve), modeling of the future Lao system would bespeculative at best.


growth outlook that drives the Base Case forecast. The volatility of recent economicprognostications highlights the futility of projecting long-term economic performancewith accuracy; it is reassuring to know that the current analysis incorporatesconsideration of this uncertainty.

Note that the forecasts presented in the table exclude station use in order toconform to the requirements of the model (“PROSCREEN II”) used for least-costexpansion planning. Net generation and net peak forecasts are shown; theseforecasts are on the order of 2 percent lower than the Base Case forecast reported inTables 5 and 6.

Table 9. Recommended Load Forecast for this Study

High Base Low High Base Low2002 - 104,970 - - 16,328 - 2003 114,246 111,310 108,557 17,774 17,350 16,889 2004 124,343 118,506 112,267 19,349 18,520 17,470 2005 135,331 126,516 116,103 21,063 19,749 18,070 2006 147,291 135,039 120,070 22,928 21,057 18,691 2007 160,307 143,847 124,173 24,959 22,440 19,334 2008 174,474 153,214 128,417 27,170 23,896 19,998 2009 189,892 164,204 132,805 29,577 25,599 20,685 2010 206,974 174,688 137,643 32,272 27,263 21,471 2011 225,238 185,141 142,336 35,124 28,889 22,207 2012 245,116 196,153 147,190 38,229 30,598 22,967 2013 266,751 208,007 152,209 41,608 32,442 23,754 2014 290,298 220,372 157,400 45,287 34,358 24,568 2015 315,926 233,649 162,769 49,292 36,435 25,410 2016 343,819 247,466 168,320 53,652 38,590 26,280

Average Annual Growth (%)2002-06 8.8% 6.5% 3.4% 8.9% 6.6% 3.4%2006-11 8.9% 6.5% 3.5% 8.9% 6.5% 3.5%2011-16 8.8% 6.0% 3.4% 8.8% 6.0% 3.4%2002-16 8.8% 6.3% 3.4% 8.9% 6.3% 3.5%2002-12 8.9% 6.5% 3.4% 8.9% 6.5% 3.5%

1/ All cases exclude station use; forecasts reflect net generation and net peak as utilized by the PROSCREEN model.

2/ All cases include Lao domestic load (300 GWh, 75 MW) from FY2010, theenergy and demand assumed to be fully absorbed from NT2 project output.

RECOMMENDED LOAD FORECAST (net, including Lao Load) 1/,2/Gross Energy Requirement (GWh) Peak Demand (MW)

System Supply Assumptions 2 3

3 SYSTEM SUPPLY ASSUMPTIONS

This Chapter of the report describes the existing power system and the optionsavailable for system expansion in order to provide for the demand growth identified inChapter 2.

Section 3.1 summarizes the existing power system. Section 3.2 describes candidatesfor system expansion, including their capital and operating costs. Assumed fuel pricesfor the system are presented in Section 3.3. Section 3.4 is a preliminary screeninganalysis of thermal expansion candidates that illustrates their competitive advantagesat different utilization factors. Finally, Section 3.5 discusses the non-thermalalternative for meeting future expansion requirements – NT2.

3.1 Installed and Planned System Capacity

The study adopts PDP 2003, as published by EGAT in April 2003, as the basis fordefining the existing system, committed additions and retirements. All tables andcalculations reported in this and subsequent chapters of the report assume the samebase as PDP 2003.20

Table 10 summarizes EGAT’s installed and purchased capacity as of March 2003.EGAT’s own system is dominated by thermal capacity, accounting for over half of thetotal. These units are predominantly gas-fired, although more than 2000 MW oflignite capacity are still in service. Purchased power is a major source of supply,accounting for over 40 percent of total available capacity. Although not shown in thetable, this segment, too, is predominantly gas-fired thermal. Large thermal units –whether oil, lignite, or gas-fired, including purchased power from IPPs and SPPs – havean availability factor of at least 80 percent. (Detailed data by plant is presented inAppendix A4.)

Thailand’s hydro capacity is almost entirely reservoir storage. (The exception is 136MW Pak Mun Dam.) Dependable hydro generation, exogenously estimated usinghistorical records from each site, represents the level of energy assumed to be availableby month at the 90 percent confidence level. Capacity factors are relatively low.

Lao imports represent purchases of energy from Theun Hinboun and Huay Hohydroelectric plants whose collective capacity factor is about 65 percent.

20 It should be noted, however, that there are minor discrepancies between actual and plannedinstalled capacity as of end-FY2003 due to minor delays and adjustments in scheduled plant additions(see Appendix A4).


Table 10. Installed and Purchased Capacity (as of March 2003)

Table 11 summarizes committed plant additions from March 2003.21 The table isdivided into four groups – EGAT plants, IPPs, SPPs, and NT2 – with a total capacityof nearly six thousand MW including NT2. The first three plants listed are underconstruction and scheduled to commence commercial operation in FY2003-04. Thesecond group (3,447 MW) includes three IPP plants whose firm contracts have facedlong delays due to multiple factors including the Asian economic slowdown andconcerted environmental opposition; these issues have been resolved and schedulesare now considered firm. The third group (197 MW) includes SPP plants (90 MWmaximum plant capacity) under contract for commissioning in the next three years.(Only plants approved by the Energy Conservation Fund as of March 2003 areincluded.)

21 The study assumes installed capacity of 25,697 MW as of September 2003, equal to September2002 installed capacity of 23,530 plus 2,167 MW added in FY2003; the FY2003 additions are dividedbetween Table 10 (1,848 MW) and Table 11 (319 MW).

No. ofPlants MW %

1. Hydroelectric 20 2,886 11% - Plants >100 MW 6 2,640 10% - Plants 5-100 MW 8 244 1% - Smaller Plants 6 3 0%

2. Thermal 3 6,030 24% - Oil/Gas 2 3,630 14% - Lignite 1/ 1 2,400 9%

3. Combined Cycle (Gas) 4 5,075 20%

4. Gas Turbine 3 778 3% - Gas 2 412 2% - Diesel 1 366 1%

5. Diesel 1 6 0%

6. Renewable 1 0.5 0%

7. Purchased Power 38 10,602 42% - Privatized Plants 2/ 3 5,671 22% - IPP 3/ 4 2,463 10% - SPP 28 1,828 7% - Lao Imports 4/ 2 340 1% - Malaysia Tie (TNB) 1 300 1%

TOTAL 70 25,378 100%

1/ Excluding 3 x 75 MW at Mae Moh retired but providing cold reserve. 2/ Includes Khanom 824 MW, Rayong 1232 MW, Ratchaburi 3615 MW. 3/ Includes Independent Power 700 MW, Tri Energy 700 MW, Bowin Power 713 MW, Eastern Power 350 MW. 4/ Includes Theun Hinboun Hydro 340 MW, Houay Ho Hydro 126 MW.

Installed CapacityPlant / Fuel Type


Table 11. Committed Plant Additions (after March 2003)

Nam Theun 2 is also a committed plant in EGAT’s generation expansion plan,scheduled for commercial operation in FY2010. Although the plant is included in thetotals reported in Table 11, NT2 is treated as an expansion candidate for purposes ofthe economic analysis in this study.

Retirements scheduled for the period FY2003-1422 are summarized in Table 12. Wehasten to add that this retirement schedule is a drastic oversimplification, reflectingmainly the “planned life” for each plant type.23 It is EGAT policy to assume fixed unitlives for planning purposes. However, should units be performing well as theyapproach their planned retirement date, a plant-specific study is undertaken todetermine whether extending the service life would be cost-effective, given anyrequired investment for reconditioning.

22 As explained in the following chapter, FY2003-14 is the planning period for our analysis.

23 The Khanom Thermal plant is an exception, scheduled for early retirement in FY2007 when a farmore efficient gas-fired combined cycle plant is expected to be available in the South.

CapacityMW

1. EGAT Projects 1,307 - Lam Takhong Pumped Storage 500 - Krabi Thermal #1 300 - Lan Krabu GT 122 - Khanom CC 385

2. IPP Contracts 1/ 3,447 - BLCP Power - Unit 1 673 - BLCP Power - Unit 2 673 - Gulf Power 700 - Union Power Development - Unit 1 700 - Union Power Development - Unit 2 700

3. SPP Contracts 2/ 197 - Phase I Contracts 69 - Phase II Contracts (Renewables) 128

4. Nam Theun 2 Hydro 3/ 995

TOTAL 5,945

1/ Includes committed plants with planned COD after March 2003 as reported in PDP 2003 (April 2003) 2/ SPP plants approved but not in operation as of March 2003. 3/ This regional study defines NT2 as 995 MW, inclusive of the 75 MW Lao domestic load it will also serve; PDP 2003 defines the plant as 920 MW delivered to the Thai system.

FY2007FY2007FY2008FY2008FY2009

FY2010

FY2003-05FY2003-05

FY2003-04FY2003-04

FY2007

PlantEGAT Planned

Commissiong Date 1/

FY2003-04

CapacityMW

1. EGAT Projects 1,307 - Lam Takhong Pumped Storage 500 - Krabi Thermal #1 300 - Lan Krabu GT 122 - Khanom CC 385

2. IPP Contracts 1/ 3,447 - BLCP Power - Unit 1 673 - BLCP Power - Unit 2 673 - Gulf Power 700 - Union Power Development - Unit 1 700 - Union Power Development - Unit 2 700

4. SPP Contracts 2/ 197 - Phase I Contracts 69 - Phase II Contracts (Renewables) 128

5. Nam Theun 2 Hydro 3/ 995

TOTAL 4/ 4,950

1/ Includes committed plants with planned COD after March 2003 as reported in PDP 2003 (April 2003) 2/ SPP plants approved but not in operation as of March 2003. 3/ This regional study defines NT2 as 995 MW, inclusive of the 75 MW Lao domestic load it will also serve; PDP 2003 defines the plant as 920 MW delivered to the Thai system. 4/ Total does not include NT2.

FY2007FY2007FY2008FY2008FY2009

FY2010

FY2003-05FY2003-05

PlantEGAT Planned

Commissiong Date 1/

FY2004FY2004FY2004FY2007


Table 12. Schedule of Retirements (FY2003-14)

EGAT has concluded that life extension is economically justified for thermal capacityat South Bangkok (units 3 through 5), and Bang Pakong;24 these reconditioned unitsare included in PDP 2003. The current study evaluates these four retiring thermalunits as candidates for reconditioning (see Section 3.2).

3.2 Thermal Expansion Candidates

EGAT has identified a number of candidate plants for long-term system expansion.This Study has focused on four new candidate options which might be expected tomeet future capacity requirements. These are: (i) oil-fired steam thermal, (ii) coal-firedsteam thermal, (iii) gas-fired combined cycle, and (iv) gas turbines. The study alsoconsiders reconditioning of a group of large thermal units scheduled for retirementduring the study period (i.e., South Bangkok Thermal and Bang Pakong Thermal). Allof these candidates are summarized in Table 13.

The capital costs, lives, and operating cost assumptions for each candidate have beenreviewed and approved by the World Bank based on both (i) discussions regardingEGAT’s recent experience, and (ii) the Bank’s own experience with large powerprojects in other countries. In particular, the Bank wished to have the study reflectevidence of a spread of US$200/kW between the cost of gas turbine (GT) andcombined-cycle (CCGT) capacity to reflect EPC cost differences (includingdevelopment cost margins). Hence, Bank-recommended values of US$250/kW for GTcapacity and US$450/kW for CCGT capacity have been adopted.

24 Parallel investigations by EGAT have concluded that life extension is not justified for South Bangkokunits 1-2 or the combined cycle units at Bang Pakong.

Unit CapacityNo(s). MW Date(s) Age at retirement

1. Thermal 2,030 - South Bangkok 1-2 2x200 Oct-2006, 2007 36

3-5 3x310 Oct-2009, 2010, 2012 35 1/ - Khanom Thermal 1-2 2x75 Jan-07 26,18 2/ - Bang Pakong 1 550 Oct-13 30 1/

2. Combined Cycle 760 - Bang Pakong 1-2 2x380 Oct-2007, 2008 25

3. Gas Turbine 140 - Lan Krabu various 140 depends on available gas 30+

TOTAL 2/ 2,790

1/ Under PDP 2003, these units are to be reconditioned for further service as of this date. 2/ Early retirement due to availability of lower cost generation. 3/ Total excludes Lan Krabu

Planned Retirement SchedulePlant by Type

Unit Capacity LifePlant by Type No(s). MW (years)

1. Thermal 3,105 - South Bangkok 1-2 2x200 35 Oct-2005, 2006

3-5 3x310 35 Oct-2009, 2010, 2012 - Mae Moh 4-5 2x150 30 Oct-2014

6-7 2x150 30 Oct-2015 - Khanom PPB 1 75 31 Jun-2012 (by agreement) - Bang Pakong 1-2 2x550 30 Oct-2013, 2014

2. Combined Cycle 3,229 - Bang Pakong 1-2 2x380 24 Oct-2006, 2007

3-4 2x307 24 Oct-2015, 2016 - Rayong 1-3 2x380 20 Oct-2011

3-4 2x380 20 Oct-2012, 2013 - South Bangkok 1 335 25 Oct-2014

3. Gas Turbine 750 - Lan Krabu various 140 30+ (depending on gas availability) - Nong Chok - 3x122 20 Oct-2015 - Surat - 2x122 15 Oct-2016

TOTAL 7,084

RetirementDate(s)


Table 13. Candidate Power Plants for the Study (2003 Prices)

3.3 Fuel Price Projections

Fuel price forecasts for this study have been developed in cooperation with EGATand the World Bank. In general, the Bank adopted EGAT’s assumptions for coal andlignite, but conducted an independent analysis to establish petroleum product prices.

One of the most critical determining factors for this study is the value of natural gasto be used in combined cycle gas turbines, since these are the most likely economicalternatives to NT2. The following discussion summarizes the methodology employedby the Bank in deriving natural gas prices. (Other petroleum products have beenvalued in a similar manner, appropriately adjusted to their own unique productcharacteristics and markets.) A more comprehensive discussion of the analysis ispresented in Appendix A3.

The economic value of natural gas has been calculated based on:

the cost of discovery, development and production for local supply,

border price for Myanmar supply,

removal of taxes and royalties from domestic production,

addition of the PTT marketing margin and

the estimated LRMC of gas transmission on a postage stamp basis.

Capacity Capital Cost Life Heat Rate Fixed O&M Var. O&M FOR MaintenanceType MW US$/kW 1/ years Btu/kWh $/kW-yr $/MWh 2/ % weeks

Oil-fired Thermal 700 792 30 8,873 19.56 0.597 6.0% 6

Coal-fired Thermal 3/ 700 905 30 9,565 24.49 0.983 7.0% 6

Combined Cycle 4/ 700 450 25 7,000 16.80 0.564 4.5% 3

Gas Turbine 5/ 230 250 15 10,500 10.46 0.419 10.0% 2

South Bangkok 6/ 310 * 15 * * * 6.0% 6

Bang Pakong 6/ 550 * 15 * * * 6.0% 6

1/ Assumed expenditure profiles (%): year 0 year -1 year -2 year -3 year -4Thermal 19.0% 23.5% 34.5% 13.5% 9.5%Combined Cycle 11.1% 37.9% 34.4% 16.6%Gas Turbine 8.8% 49.6% 41.6%

2/ VOM calculated as a ratio (FOM:VOM): oil-fired (85:15), coal-fired (80:20), combined cycle (85:15), gas turbine (95:5).3/ VOM includes limestone for FGD4/ 2GT multi-shaft assumed5/ Excluding land and land rights.6/ South Bangkok and Bang Pakong thermal units are candidates for reconditioning (life extension); this option only permitted in the year immediately following retirement: SBT3 - 2010, SBT4 - 2011, SBT5 - 2013, BKT1 - 2014. Asterisk (*) indicates costs and efficiencies are included in the model's database and used in the analysis, but not identified here for reasons of confidentiality.


Although the World Bank does not have access to individual gas contracts, it isunderstood that the gas pricing structure, valid for the duration of the contract, isspecified in Thai Baht, incorporating an indexation formula which adjusts the priceover time according to the following factors:

the fob price of 3.5%S HFO Singapore,

a petroleum industry machinery inflation index reflecting USD inflation,

the Thai CPI reflecting Thai domestic inflation,

an exchange rate adjuster, and

a constant.

Given that our project numeraire is US dollars, the machinery index, the Thai CPIindex and the exchange rate adjuster are offsetting in future price projections (basedon purchasing power parity method of exchange rate projection). When working inUS$ prices, therefore, the only non-offsetting element of the index is the HFOadjuster, having a weight of about 30% in the total index.

In addition, PTT charges EGAT and IPPs a marketing margin of 1.75% of the salesprice, plus a postage-stamp pipeline toll.

Moving from the commercial value of natural gas to an economic value furtherrequires removal of all transfers – royalties and taxes – from the commercial price.Finally, resulting nominal economic natural gas values are converted into real values bydeflating the nominal series by the MUV index.25

Base Case economic fuel price projections adopted for this study are summarized inTable 14. High and Low scenario fuel price projections are reported in Appendix A3.

Table 14. Base Case Fuel Price Forecasts

25 The MUV index is more formally identified as the United Nations’ Index of Unit Value ofManufactured Exports from the G-5 industrial countries to developing country markets expressed inU.S. dollars.

Real Economic PricesFiscal Natural Gas Hvy Oil 3.5% Diesel Lignite Imported CoalYear USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.55 3.39 6.10 1.21 1.54 2004 2.44 2.74 4.94 1.20 1.55 2005 2.40 2.58 4.65 1.19 1.53 2006 2.36 2.42 4.37 1.17 1.52 2007 2.32 2.27 4.10 1.15 1.51 2008 2.31 2.31 4.17 1.14 1.50 2009 2.30 2.35 4.23 1.12 1.48 2010 2.29 2.38 4.29 1.11 1.47 2011 2.28 2.41 4.34 1.10 1.45 2012 2.27 2.44 4.40 1.08 1.44 2013 2.26 2.47 4.45 1.06 1.43 2014 2.24 2.50 4.50 1.05 1.41

End Effect 2.27 2.50 4.50 1.05 1.41 Average Annual Growth (%)2003-2014 -1.1% -2.7% -2.7% -1.3% -0.8%


3.4 Thermal Candidate Plant Screening Analysis

The Study TOR requests a preliminary screening analysis based on real economiccosts in order to confirm the expectation that natural gas-fired units are the primaryalternatives to NT2.

The analysis has been prepared for the candidate generating units summarized inTable 13, assuming the fuel price forecasts from Table 14. Each candidate has beenevaluated at constant prices, using a real economic discount rate of 10 percent.

Table 15 shows the results of this analysis. The graph in the table plots the unit costof one kWh from each source as a function of the rate of capacity utilization.26

The table shows that gas turbines are the clear thermal choice for capacity utilizationbelow 25 percent (i.e., peaking duty). Gas-fired combined cycle appears to be theclear choice for higher capacity utilization. Even at very high capacity factors, the costof combined cycle is at or below the cost of coal-fired units. Oil appears to be non-competitive at the real fuel prices adopted for the current study.

3.5 NT2 – The Alternative Expansion Candidate

Contractually, in the EGAT-NTPC power purchase agreement (PPA), NT2 is treatedas three separate transactions:

the first transaction is a firm power purchase of 4406 GWh per year(allocated to peak-period hours [6 a.m. to 10 p.m.] and according toexpected monthly generation) at the Primary Energy Tariff (“PE”) specifiedin the contract;

the second transaction is a purchase of 948 GWh annually during off-peakhours at the Secondary Energy 1 Tariff (“SE1”) specified in the contract;this transaction is treated as non-firm so that PROSCREEN does notrecord a further increment to installed capacity; and

a third transaction (not required, but at the option of EGAT) is a purchaseof an additional 282 GWh at the Secondary Energy 2 Tariff (“SE2”).

26 Because plant capacities have already been adjusted for the effect of forced outages andmaintenance, each effective kW can be used up to 100 percent of the time.


Table 15. Screening Analysis of EGAT Candidate Plants

OIL COAL COMB.CYC GTPlant Characteristics 700 MW 700 MW 700 MW 230 MW Oil Coal Gas

Life (years) 30 30 25 15 1 3.39 1.54 2.55 FOR (%) 6% 7% 4.5% 10% 2 2.74 1.55 2.44 Maintenance (wks) 6 6 3 2 3 2.58 1.53 2.40 Availability factor 0.83 0.82 0.90 0.87 4 2.42 1.52 2.36 Heat rate (Btu/kWh) 8,873 9,565 7,000 10,500 5 2.27 1.51 2.32

6 2.31 1.50 2.31 Cap.Cost ($/kW) 792 905 450 250 7 2.35 1.48 2.30 Expend.Profile (%) 8 2.38 1.47 2.29

-4 9.5% 9.5% 9 2.41 1.45 2.28 -3 13.5% 13.5% 16.6% 10 2.44 1.44 2.27 -2 34.5% 34.5% 34.4% 41.6% 11 2.47 1.43 2.26 -1 23.5% 23.5% 37.9% 49.6% 12 2.50 1.41 2.24 0 19.0% 19.0% 11.1% 8.8% 13 2.50 1.41 2.27

Levelized Cap.Cost 104.39 119.29 60.58 39.19 14 2.50 1.41 2.27 Fixed O&M ($/kW-yr) 19.56 24.49 16.80 10.46 15 2.50 1.41 2.27 Variable O&M ($/kWh) 0.00060 0.00098 0.00056 0.00042 16 2.50 1.41 2.27 Levelized Fuel ($/kWh) 0.02271 0.01412 0.01637 0.02755 17 2.50 1.41 2.27 Fuel Price Sensitivity 1.00 1.00 1.00 1.00 18 2.50 1.41 2.27 Discount rate 10% 19 2.50 1.41 2.27

20 2.50 1.41 2.27 21 2.50 1.41 2.27 22 2.50 1.41 2.27 23 2.50 1.41 2.27 24 2.50 1.41 2.27 25 2.50 1.41 2.27 26 2.50 1.41 2.27 27 2.50 1.41 2.27 28 2.50 1.41 2.27 29 2.50 1.41 2.27 30 2.50 1.41 2.27

Economic Fuel Prices (Constant US$/mmbtu)

Levelized Cost of GenerationCandidate Units ($/kWh)

$0.00

$0.05

$0.10

$0.15

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

Percent Ulilization of Effective kW

US

$ p

er

kW

h

Oil Coal Combined Cycle Gas Turbine


For purposes of the current study, total planned generation is allocated by monthbased on a review of historical data (1953-99) provided by NTPC, as summarized inthe following chart:

For the economic [real resource] analysis presented in Chapter 5, Base Caseinvestment and operating costs of the NT2 project are based on real cash flow dataderived from the project sponsor’s financial model, excluding transfers and sunk costs,but including incremental sponsor development costs that reflect use of real resources

Costs for associated transmission in Thailand and Laos are also included in theanalysis. Even when these costs are not borne by the project sponsor (as is the casewith associated transmission in Thailand), these investments represent real resourcecosts required to deliver NT2 energy from the powerhouse to end-users.

PE SE1 SE2Jan 370.4 62.2 18.5 Feb 331.0 46.2 13.7 Mar 362.1 44.0 13.1 Apr 349.8 30.0 8.9 May 361.8 77.7 23.1 Jun 355.9 114.7 34.1 Jul 386.4 147.2 43.8 Aug 391.2 107.1 31.9 Sep 382.6 98.5 29.3 Oct 389.2 88.6 26.4 Nov 363.4 70.0 20.8 Dec 362.2 61.8 18.4 Total 4,406.0 948.0 282.0

NT2 GWh by Month (1953-99)

Methodology for the Study 3 3

4 METHODOLOGY FOR THE STUDY

The primary focus of the current study is an economic analysis to determine whetherthe NT2 Project has a satisfactory economic cost-risk profile in the context of theregional power market. The main distinguishing characteristics of this second stageanalysis are threefold:

all values reflect real economic resource costs (to the greatest extentfeasible);

the scope of work includes both the Thai and Laotian electricity markets;and

the risk analysis consists of an integrated multi-event probabilisticframework that produces one overall quantitative result showing whetherimplementing the NT2 project in October 200927 would be an acceptableeconomic investment for the power sector.

Section 4.1 introduces the least-cost generation expansion planning methodologyadopted for this study. Section 4.2 describes the cost-risk framework used todetermine the Study outcome.

4.1 The Least Cost Planning Methodology

4.1.1 The PROSCREEN II ModelPROSCREEN II, the least-cost generation expansion planning model currently usedby EGAT, has been adopted for use in this study.28 This model is widely used byutilities throughout the world. Specifically, three modules within the model are used:(i) the Load Forecast Adjustment (LFA) module, (ii) the Generation and Fuels (GAF)module, and (iii) the PROVIEW module. These modules:

organize the necessary load data (annual/seasonal energy and peak load andload shape) which define capacity requirements to maintain a specified levelof system reliability;

27 Sensitivity analysis evaluated alternative start-dates, and concluded that Oct-09 (i.e., the beginning ofFY2010) is the least-cost.

28 Indeed, without the full support of EGAT generation planners, this study would not have beenpossible.


assemble the necessary data on unit operating characteristics, fuel costs, saleand purchase arrangements for evaluation of alternative generationresource plans, and calculate the production cost and reliability associatedwith these plans; and

determine the least-cost plan for meeting system demand under aprescribed set of constraints by simulating the operation of the utility todetermine the cost and reliability effects of alternative system resourceadditions.

EGAT conducts its least-cost generation expansion planning at current, financial prices,i.e., including annual inflation, and not adjusting market prices to economic prices byexcluding transfer payments (taxes, duties, and subsidies). This policy is consistentwith a gradual industry-wide trend away from traditional economic analysis as utilitiesmove toward privatization and away from government subsidies and preferentialtreatment. As noted in Chapter 1, however, this study is a regional evaluation ofexpansion options using real resource costs, and therefore cost assumptions divergefrom values currently assumed for EGAT planning.29

For the interested reader, a more complete explanation of how PROSCREEN works ispresented in Appendix A5.

4.1.2 How PROSCREEN is Applied in this StudyTo summarize, we have adopted the following assumptions for PROSCREEN least-cost expansion planning runs in the current study:

All plants defined as “committed” (Table 11) are “fixed” in the plan atnegotiated cost/timing. These units are considered as part of the system;they are not “selected” as least cost by the model.

Non-thermal resources are dispatched without regard to cost:

Hydro capacity, according to an exogenously determined level ofmonthly dependable generation;

Lao imports from Theun Hinboun and Huay Ho plants;

SPP contracts (and commitments), assuming a capacity factor of 80percent.

29 The World Bank has outlined detailed requirements in the TOR (see Appendix A1) regardingmodeling approach, and specified a large number of input assumptions. Further, the Bank recognizesthe unique perspective of a study based on real regional resource costs, and acknowledges that themethods and values used in this study for its purposes are completely without prejudice to differentones that EGAT may consider as more appropriate for its own operating context and requirements.


With the exception of EGAT’s own hydro capacity, each of these resourcesis modeled as a separate transaction, defined from contractual purchaseprice and operating constraints.

NT2 is treated as two transactions ("PE" and "SE1"; see Section 3.5) withan October 2009 starting date (FY2010) when it is included in the analysis.

Thermal resources, including both EGAT’s existing thermal capacity andavailable IPP capacity, are economically dispatched based on cost. IPPs arenot required to run, but in general are dispatched, since they are relativelylow-cost gas-fired units.30

Implicit in this modeling approach is the reasonable assumption that the Laoalternative to NT2 for meeting that portion of its demand would be importof thermal-fired electricity from Thailand.

4.2 Cost-Risk Analysis Modeling Framework

As specified in the TOR, the study outcome is to be determined by means of theresults profile shown in Table 16 (the “Cost-Risk Framework”). This profile providesfor calculating the probability-weighted present value (PV) costs of eitherimplementing or not implementing NT2 for commercial operation in FY2010, giventhe interplay of several major uncertain factors – project cost, long-term demand forelectricity, and long-term economic value of natural gas as well as the suggestedprobabilities of occurrence for Base Case, Low and High estimates of these variables.The difference between the probability-weighted PV cost of implementing the projectin FY2010 versus not implementing it at all is the decision criteria for this analysis. Alower net present value (NPV) “with NT2” indicates that the project is an acceptableeconomic investment for the regional power market.

The specific steps undertaken to complete the cost-risk analysis are summarized in thefollowing paragraphs:

30 Thermal capacity at Krabi is dispatched without regard to cost, as transmission constraintsnecessitate its use for reliability in the South.


Table 16. The Cost-Risk Framework

Determine Base Case, Low, and High real economic values for the three keyuncertainties – (i) project cost, (ii) growth rate of electricity demand, and(iii) the economic value of natural gas – expected to have the mostsignificant potential impact on the economic decision to develop NT2.

Define a probability of occurrence for each state (Base Case, Low, andHigh) of each variable. In fact, these probabilities are specified in theproject TOR, and shown in Table 16. It should be noted that theprobabilities were selected based on judgment – backed by World Bankstudies from other projects – about relationship between extent ofvariance and its probability of occurrence, as well as the presumption thatthe base case should have a higher probability of occurrence while High

A. Present Values WITH NT2:

Case Probability Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 h 0.25 hhh <Scenario PV> 0.01563 h 0.25 h 0.25 m 0.50 hhm <Scenario PV> 0.03125 h 0.25 h 0.25 l 0.25 hhl <Scenario PV> 0.01563 h 0.25 m 0.50 h 0.25 hmh <Scenario PV> 0.03125 h 0.25 m 0.50 m 0.50 hmm <Scenario PV> 0.06250 h 0.25 m 0.50 l 0.25 hml <Scenario PV> 0.03125 h 0.25 l 0.25 h 0.25 hlh <Scenario PV> 0.01563 h 0.25 l 0.25 m 0.50 hlm <Scenario PV> 0.03125 h 0.25 l 0.25 l 0.25 hll <Scenario PV> 0.01563 m 0.50 h 0.25 h 0.25 mhh <Scenario PV> 0.03125 m 0.50 h 0.25 m 0.50 mhm <Scenario PV> 0.06250 m 0.50 h 0.25 l 0.25 mhl <Scenario PV> 0.03125 m 0.50 m 0.50 h 0.25 mmh <Scenario PV> 0.06250 m 0.50 m 0.50 m 0.50 mmm <Scenario PV> 0.12500 m 0.50 m 0.50 l 0.25 mml <Scenario PV> 0.06250 m 0.50 l 0.25 h 0.25 mlh <Scenario PV> 0.03125 m 0.50 l 0.25 m 0.50 mlm <Scenario PV> 0.06250 m 0.50 l 0.25 l 0.25 mll <Scenario PV> 0.03125 l 0.25 h 0.25 h 0.25 lhh <Scenario PV> 0.01563 l 0.25 h 0.25 m 0.50 lhm <Scenario PV> 0.03125 l 0.25 h 0.25 l 0.25 lhl <Scenario PV> 0.01563 l 0.25 m 0.50 h 0.25 lmh <Scenario PV> 0.03125 l 0.25 m 0.50 m 0.50 lmm <Scenario PV> 0.06250 l 0.25 m 0.50 l 0.25 lml <Scenario PV> 0.03125 l 0.25 l 0.25 h 0.25 llh <Scenario PV> 0.01563 l 0.25 l 0.25 m 0.50 llm <Scenario PV> 0.03125 l 0.25 l 0.25 l 0.25 lll <Scenario PV> 0.01563

A. Probability-weighted Present Value WITH NT2 #VALUE! 1.00000


Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 hh <Scenario PV> 0.06250 h 0.25 m 0.50 hm <Scenario PV> 0.12500 h 0.25 l 0.25 hl <Scenario PV> 0.06250 m 0.50 h 0.25 mh <Scenario PV> 0.12500 m 0.50 m 0.50 mm <Scenario PV> 0.25000 m 0.50 l 0.25 ml <Scenario PV> 0.12500 l 0.25 h 0.25 lh <Scenario PV> 0.06250 l 0.25 m 0.50 lm <Scenario PV> 0.12500 l 0.25 l 0.25 ll <Scenario PV> 0.06250

B. Probability-weighted Present Value WITHOUT NT2 #VALUE! 1.00000

Probability-weighted PV Savings (Cost) WITH NT2 #VALUE! (Result A minus Result B; 2003 USD million)


SCENARIO RESULTS (2003 USD million)POWER DEMAND GAS PRICE

CONSTRUCTION COST POWER DEMAND GAS PRICE


and Low values should have high-enough probabilities so that they have ameasurable impact final cost-risk analysis results.

Run the PROSCREEN expansion planning model under Economic BaseCase assumptions with NT2 as a candidate competing for a place in the least-cost expansion plan from its earliest expected commercial operation date ofFY2010. This initial analysis added NT2 to the system in October 2009,i.e., it specified that the least-cost expansion plan included NT2commencing operation in October 2009. This date was therefore fixed forall subsequent "with NT2" model runs to conform to the logic of thedecision matrix (the decision being whether to develop NT2 for commercialoperation in October 2009 or not to do so).31

Run the PROSCREEN expansion planning model with NT2 commencingcommercial operation in October 2009 (FY2010) for all combinations of theabove-defined uncertainties. The PROSCREEN “objective function” (i.e.,basis for comparison of results) is the present value of future investmentand operating costs over the Study Period.

Re-run each of the defined scenarios without NT2 so that demand must beserved from alternative resources.

Calculate the probability-weighted present value of costs for the “withNT2” and “without NT2” scenario groups.

Subtract the probability-weighted result “with NT2” from the result“without NT2” to determine the Study outcome.

To complete the Cost-Risk Framework, a total of 18 scenario runs are required, 9with NT2 and 9 without NT2. These scenarios are formed from combinations of twoplanning variables – power demand and natural gas price. Three cases– Base, Low, andHigh – are used for each of these variables. The 9 scenarios run with NT2 areexpanded to 27 scenarios in the economic assessment by combining manually thethree cases for the construction cost of NT2 with the results of the other scenarios.

For each scenario, the combined probability is simply the product of the probabilitiesof each of its components. For example, the probability of the “with NT2” Base Caseor “mmm” scenario (i.e., “medium” values for each possible outcome) is equal to 0.125(0.50 x 0.50 x 0.50), and the probability of the “without NT2” Base Case ("mm"scenario) is 0.25 (0.50 x 0.50). Similarly, the probability of the “with NT2” scenarioassuming all “high” outcomes (“hhh”) is 0.015625 (0.25 x 0.25 x 0.25). When allscenarios are considered, of course, the probabilities for the "with NT2" and "withoutNT2" scenario groups each sum to 1.00.

Chapters 5 explains the specific Base Case, Low, and High values adopted for eachvariable in the economic cost-risk analysis.

31 The sensitivity of results to a delay in commercial operation date was also evaluated, as reported inChapter 5.


Economic Evaluation 3 9

5 ECONOMIC EVALUATION

The objective of this chapter is to evaluate whether NT2 is a part of the least-costgeneration expansion plan for meeting future regional electricity needs when it isevaluated using the real economic cost of the resources required. The cost-riskanalytical framework outlined in Chapter 4 is applied to give a comprehensive,probabilistic answer to this question which systematically incorporates the range ofuncertainties – construction costs, load growth, fuel prices – assumed in this study toface the regional electricity sector in the coming years.

Section 5.1 summarizes the basic assumptions adopted for system expansion planning.Section 5.2 presents Base Case results. Section 5.3 reports the results of the cost-riskanalysis. Section 5.4 discusses the sensitivity of results to changes in specific variables.

5.1 Economic Planning Assumptions

5.1.1 Basic Economic AssumptionsThe World Bank has specified the following economic basis for the real resourceanalysis of NT2:

All costs exclude internal fiscal transfers (e.g. taxes, duties, and subsidies)

All values are expressed in constant US dollars of 2003

The discount rate is 10% real

The MUV index (a UN index of the unit value of manufactured exportsfrom G-5 industrial countries to developing country markets, expressed inUS dollars) is used as the price deflator to restate future year prices in real2003 US dollars; the MUV index averages 1.2 percent per annum through2015, and a constant rate of 1.5 percent is assumed thereafter. Thaiinflation is assumed to be a constant 2.25 percent, the rate currentlyadopted by EGAT.

An exchange rate of 42 Thai Baht per US dollar was used for planning purposes. Thestandard assumption of purchasing power parity (PPP) is adopted to estimate theexchange rate in future years based on the above-noted differential inflationassumptions.


5.1.2 System CharacteristicsIn general, system characteristics adopted for the current analysis follow EGAT’sPower Development Plan for 2003 (PDP2003) as published in April 2003.Characteristics common to the Economic runs of PROSCREEEN, as detailed inChapter 4, are summarized below:

The Base Case load forecast is Thailand’s official Base Case of August 2002(see Chapter 3), augmented by a Lao PDR domestic load of 75 MW and300 GWh.

The reliability criterion is a reserve margin of 15 percent.

The existing system corresponds to the summary in Table 10.

All “committed plants” as identified in Table 11 are presumed to commencecommercial operation according to schedule.

The schedule for plant retirements follows the assumptions detailed in Table12.

NT2 (995 MW) is added to the system in October 2009 (FY2010) in the“with NT2” scenarios.32

All other plants – including plants proposed for reconditioning and allgeneric expansion options (see Table 13) – are modeled as candidateswhich much compete for a place in the least cost economic plan. (Notethat candidates for “reconditioning” – South Bangkok thermal (units 3-5)and Bang Pakong (unit 1) – are only permitted to enter the expansion planin the year following scheduled retirement.)

Generation of existing plants and selected candidates is dispatched byPROSCREEN according to the following rules:

All non-thermal generation – notably domestic hydro plants and Laoimports – is dispatched first, without regard to cost. With theexception of EGAT’s own hydro capacity, each of these resources ismodeled as a separate transaction, defined from contractualpurchase price and operating constraints.

NT2 energy is dispatched in two parts according to the monthlyvariation reported previously in Chapter 3, one to provide peak-period energy and a second to provide off-peak energy. Optionaloff-peak generation is not assumed.

32 Project-associated transmission works in Laos are included in the project cost. Project-associatedincremental transmission costs for Thailand do not presume any other future hydro exports fromLaos to Thailand, due to the uncertainty of these exports.


All thermal generation – the majority of the entire system – is subjectto economic dispatch, and run only when it is lowest cost.Exceptions are small power producers (SPPs), which are assumed torun at an 80 percent capacity factor.33

. The following section discusses the NT2 cost assumptions for the economic projectassessment.

5.1.3 NT2 Planning Assumptions for the Economic AnalysisAs already noted, the Base Case economic analysis has been run in two modes – “withNT2” included in the expansion plan for commercial operation from October 2009(FY2010), and “without NT2” in the plan.34

Base Case economic investment and operating costs of the NT2 project are based onreal cash flow data derived from the project sponsor’s financial model, excludingtransfers and sunk costs, but including incremental sponsor development costs thatreflect use of real resources.35

The total capital cost of NT2 will be US$729 million, equivalent to a present value ofUS$499 million at 2003 prices. Associated transmission (including lines andsubstations, but excluding sunk costs) has a capital cost of US$135 million, equivalentto a present value of US$82 million. Table 17 summarizes the investment coststreams.

Low and High estimates of construction costs for NT2 and associated transmissionhave been specified in the TOR to be ±30% of the expected construction cost usedfor the Base Case. These costs are reported at the bottom of Table 17.

Operating costs for NT2 have likewise been derived from the project sponsor’sfinancial model. The real annual cost of O&M is estimated as US$16.28 million peryear.

Based on preliminary analysis, it is presumed that NT2 would replace gas-firedcombined cycle generation. The World Bank has requested that an environmentalbenefit – a “carbon credit” of $3 per tonne Carbon of gas substitution – should begiven to NT2 for its contribution to global greenhouse gas reduction. This valuereflects recent global carbon trading experience. The resulting annual credit of

33 This is a reasonable assumption given the high percentage of this output which is fossil fueled(predominantly by gas).

34 As discussed in Section 4.2 above, the starting date was fixed based on a PROSCREEN run in whichNT2, treated as a candidate, was added to the least cost plan in October 2009. FY2010 (Oct-09) isconsidered to be the earliest possible commercial operation date (COD); Section 5.3 reports thesensitivity of results to delayed starting dates.

35 For a commercial evaluation at market prices, negotiated PPA payments per kWh purchased wouldbe taken as the project cost rather than actual developer cash flows, since NT2 generation is beingpurchased at that agreed price.


US$1.91 million is included in the analysis as a decrease in the annual O&M cost ofNT2.

Table 17. Capital Costs of NT2 (constant US$2003, 10% discount rate)

The TOR requests that the Consultant determine whether there is any “systematicbias” in the estimated construction costs for NT2 (i.e., whether the Base Caseestimated project cost reported here can be assumed to be the expected projectcost). There is evidence that the Base Case project cost estimate is not systematicallybiased either positively or negatively:

As with planning for any large hydropower project, NT2 developer planninghas included comprehensive activity scheduling to assure efficient projectdevelopment at least cost. Moreover, NT2 project developers have reliedon fixed-price bidding for key civil and electro-mechanical contracts. Facedwith fixed prices, contract bidders necessarily undertake an evaluation ofthe risks they are undertaking. Further, these fixed-price contracts includeboth physical and price contingencies, further protecting the developeragainst a wide range of unforeseen cost overruns.

NT2 project developers have also employed sophisticated risk models totrace the linkages from randomly selected project activity delays, and theircumulative impact on the critical path to final project completion. In otherwords, complex models have been utilized to ascertain if randomly selecteddelays might cause subsequent delays that could not be mitigated so as toachieve targeted project deadlines. The Base Case project cost estimateincludes a quantified estimate of the risk premium associated with suchunanticipated delays. Thus, there is a risk “insurance” against unexpectedcost overruns already incorporated into the Base Case cost estimatesreported in Table 17.

TotalFiscal Cost PV of Cost Cost PV of Cost PV of CostYear USD million USD million USD million USD million USD million20032004 - 1.4 1.2 2005 196.5 154.8 6.3 5.0 2006 137.9 98.8 6.1 4.4 2007 236.1 153.7 28.8 18.8 2008 118.5 70.2 69.2 41.0 2009 39.9 21.5 15.6 8.4 2010 - - 7.4 3.6

Base Case 728.9 499.0 135.0 82.4 581.4

High Case 947.6 648.7 175.5 107.1 755.8 - increase 218.7 149.7 40.5 24.7 174.4 Low Case 510.2 349.3 94.5 57.7 407.0 - decrease 218.7 149.7 40.5 24.7 174.4

NT2 Associated Transmission


5.2 Base Case Results

Table 18 summarizes the results of the Base Case scenario “with NT2” included inthe expansion plan from FY2010. (A detailed summary of these results is presented inAppendix A6.)

A total of 17,673 MW are added to the system during the planning period. NT2, ofcourse, accounts for 995 MW of new capacity. A further 6,798 MW representcapacity that is already committed (i.e., not competing for a place in the plan). All ofthe candidates selected to meet future load are gas-fired. Recommended additionsinclude 10,500 MW of combined cycle capacity and 690 MW of gas turbine capacity.Reconditioned thermal plants account for a further 1,480 MW.

The lower panel of Table 18 shows the present value (PV) of this expansion program.The PV of total cost over the planning horizon is US$26,200 million. AfterPROSCREEN calculates the end-effects of this expansion program in order to avoidany biases which might result from a short planning horizon, the estimated total PV ofcosts over the Study Period is US$43,681 million.

Table 19 presents results of an expansion planning model run identical to the onespecified for Table 18 except that NT2 is not included. The table shows therecommended expansion plan in the absence of the 995 MW from NT2. This caserequires a total of 12,600 MW of combined cycle plant over the Planning Period, withless gas turbine plant and less reconditioning – a net increase of 940 MW.

The middle panel of Table 19 compares the PV of total costs required for each of theBase Case generation expansion plans, both “with” and “without” NT2. Assumingthat all assumptions adopted for the Base Case analysis prove correct, the estimatedPV of total costs over the Study Period is US$43,681 million when NT2 is included inthe plan, and US$43,958 million when NT2 is excluded.

The graph at the bottom of Table 19 charts the annual cumulative benefits associatedwith the decision to proceed with NT2. Each point on the “without NT2” linerepresents the annual accumulated difference in costs over the “with NT2” case. (Apositive difference indicates a real resource savings associated with developing NT2,while negative numbers would indicate a real resource cost.) The chart suggests thatthe decision to purchase NT2 power will produce a significant savings over the studyhorizon. The accumulated present value of savings to the region over the entireStudy Period totals US$277 million at 2003 prices.36

A total present value of savings of US$277 million may seem small in relation to thetotal long term investment requirements. These savings should be put in perspective.They are equivalent to 48% of the total capital investment in NT2, and represent asavings to the region of US$0.012 per kWh of NT2 sales to EGAT.

36 The US$ 277 million represents a ‘savings” since the least-cost plan without NT2 would come atgreater total cost.


Table 18. Base Case “with NT2”

5.3 Cost-Risk Analysis

The Base Case tells us that NT2 should be included in the region’s least costgeneration expansion plan assuming that the assumptions adopted for decision-making are correct. The objective of cost-risk analysis is to determine whether thesame decision is justified given the high probability that future events will diverge fromthe Base Case assumptions.

As specified in the TOR, the study outcome is determined by means of the resultsprofile shown in Table 16 (the “Cost-Risk Framework”). This profile provides forcalculating the probability-weighted present value (PV) costs of either implementingor not implementing NT2 for commercial operation in FY2010, given the interplay ofseveral major uncertain factors – project cost, long-term demand for electricity, andlong-term economic value of natural gas as well as the suggested probabilities ofoccurrence for Base Case, Lower and Higher estimates of these variables. Thedifference between the probability weighted PV cost of implementing the project inFY2010 versus not implementing it at all is the decision criteria for this analysis. Alower net present value (NPV) “with NT2” would indicate that the project is anacceptable economic investment for the regional power market.

Fiscal Installed ReserveYear MW Addition Retirement CC GT Recondition Import Margin2003 25,697 2,167 37.4%2004 26,417 720 33.5%2005 26,497 80 25.5%2006 26,297 (200) 16.9%2007 27,678 1,732 (350) 15.9%2008 29,398 1,400 (380) 700 16.0%2009 31,118 700 (380) 1,400 15.1%2010 33,043 (310) 700 230 310 995 15.1%2011 34,903 (310) 1,400 460 310 15.1%2012 37,003 2,100 15.5%2013 39,103 (310) 2,100 310 15.4%2014 41,203 (550) 2,100 550 15.1%

Total 43,370 6,798 (2,790) 10,500 690 1,480 995

Notes: CC - gas-fired combined cycle, GT - gas turbine.

PRESENT VALUE OF COSTS(US$ million) With NT2 A. Planning Period (2003-2014) 26,200 B. End-Effects Period 17,481 C. Study Period (A + B) 43,681

Committed Plant Planned Additions (including NT2)


Table 19. Base Case “without NT2”

Fiscal Installed ReserveYear MW Addition Retirement CC GT Recondition Import Margin (%)2003 25,697 2,167 37.4%2004 26,417 720 33.5%2005 26,497 80 25.5%2006 26,297 (200) 16.9%2007 27,678 1,732 (350) 15.9%2008 29,398 1,400 (380) 700 16.0%2009 31,118 700 (380) 1,400 15.1%2010 33,138 (310) 2,100 230 15.5%2011 34,928 (310) 2,100 15.2%2012 37,028 2,100 15.5%2013 39,048 (310) 2,100 230 15.4%2014 41,148 (550) 2,100 550 15.0%

Total 43,315 6,798 (2,790) 12,600 460 550 -


PRESENT VALUE OF COSTS(US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 26,200 26,304 B. End-Effects Period 17,481 17,654 C. Study Period (A + B) 43,681 43,958

PV of Savings with NT2 A. Planning Period (2003-2014) 104 B. End-Effects Period 173 C. Study Period (A + B) 277 % of total cost 0.63%

Planned Additions (excluding NT2)Committed Plant

Savings (Cost) Due to Selecting Nam Theun 2Difference in Accumulated Present Value (US$ million)

-40

0

40

80

120

160

200

240

280

2010 2015 2020 2025 2030 2035

US

$ m

illi

on

with NT2 without NT2


The key decision variables for this study are defined in the study TOR (see AppendixA1). They are:

Capital cost of NT2. The World Bank has specified a cost range of +30percent (High capital cost) and –30 percent (Low capital cost); thesevalues are reported in Table 17.

Regional demand forecast. The World Bank has specified a very wide range inorder to reflect accumulated international experience with load forecastaccuracy over time; the regional High and Low demand forecasts aresummarized in Table 10.

Natural gas price forecast.37 The World Bank has developed its own fuel priceprojections, with particular emphasis on the price of natural gas since it isthe most competitive alternative fuel. The Base Case projections arepresented in Table 15; High and Low scenarios are reported in AppendixA3.

For each of these three key variables, the TOR specifies base case, low case and highcase assumptions, as well as the probabilities of occurrence associated with each. Basecase assumption values are assigned a 50 percent probability of occurrence, while theLow and High case assumption values are assigned probabilities of 25 percent each.

Based on these assumptions, a total of 27 possible scenarios are required to representall probable outcomes “with NT2”, and 9 possible scenarios to represent all possibleoutcomes “without NT2”.

The results of the cost-risk analysis are summarized in Table 20. They confirm thattaking all evaluated potential outcomes into account, a system expansion planfeaturing the commissioning of NT2 in October 2009 is the correct decision from aneconomic least-cost perspective. The probability-weighted PV of total savings overthe entire Study Period is estimated to be US$269 million, equivalent to US$0.012 perkWh sold from the NT2 project.

37 Since natural gas is the primary fuel alternative to NT2, this report uses the terms "natural gasprice forecast" and "fuel price forecast" interchangeably; readers should be reminded that either termrefers to the complete sets of fossil fuel forecasts (Base Case, High, and Low) presented in AppendixA3.


Table 20. Economic Cost Risk Analysis Results

A review of the cost-risk matrix indicates that NT2 capital cost is the variable havingthe greatest impact on results. High capital costs decrease the savings by US$174million when other variables are held constant (i.e., from US$277 to US$103 million),while Low capital costs increase savings by US$175 million.

High and low demand have an uneven impact; high demand increases savings by onlyUS$22 million, but low demand reduces savings by US$80 million. Results areasymmetrical around the Base Case despite the symmetry of input assumptions;investment decisions are made by PROSCREEN at specific trigger-points that aresomewhat differently timed between low and high cases, making outcomes lesssymmetrical than the inputs would suggest. Further, since NT2 is fully utilized in theBase Case, there is limited opportunity for increased benefits due to an increase insystem load. NT2 cannot be accelerated in response to higher demand, but othercapacity can be delayed in response to low demand under the “without NT2”








POWER DEMAND GAS PRICE

CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million)



scenarios. A High natural gas price increases savings by US$83 million, while a Lowprice reduces savings by US$51 million. In this regard, it should be noted that naturalgas price projections are not perfectly symmetrical around the Base Case (seeAppendix A3), resulting in somewhat greater savings under high gas price scenarios.

In fact, there is only one combination, the most adverse future possible from theperspective of NT2 (high capital costs, low demand, and low gas prices), thatproduces and unfavorable result, and this by a very small margin with an extremelylow probability of occurrence.

5.4 Sensitivity Analysis

The results of the cost-risk analysis can be better understood by studying thesensitivity of the Base Case to changes in modeling assumptions and the values ofindividual variables. This section reports on the following specific cases:

Sensitivity to changes in the date of commercial operation

Sensitivity to changes in the forecasts of key variables

Sensitivity to changes in the probability distribution adopted for the cost-risk analysis.

5.4.1 Delay in Commercial OperationThe Base Case economic analysis “with NT2” presumes an October 2009 startingdate; we have separately established that this COD minimizes total system cost. Asalready noted, this is both the earliest feasible starting date and the date ofcommercial operation selected by PROSCREEN under Base Case assumptions (seeSection 4.2).

However, the project PPA, which was signed in November 2003, faced manyunanticipated delays, so it is certainly possible that the estimated October 2009 CODwill not be achieved. We tested the impact of a two-year delay (i.e., an October 2011COD) on the net savings (cost) due to implementing the NT2 project. This case iscompared with the Base Case in Table 21.

The delay of NT2 necessitates an early investment in thermal capacity of 1170 MWto meet system reliability requirements; 1400 MW of additional combined cyclecapacity is required in FY2010, coupled with delay of 230 MW of gas turbinecapacity. Although the total capacity mix is identical to the Base Case as soon asNT2 is commissioned in FY2012, this early investment, and associated higher fuelcosts, increases the total Study Period cost of the "with NT2" scenario.

As shown in the table, a two-year delay would reduce the net real resource savings toabout US$146 million, a net benefit reduction of about US$130 million.


Table 21. Sensitivity of Base Case to Delay of Commercial Operation

5.4.2 Changes in the Forecasts of Key Variables

Changes in the Demand Forecast

The spread between the high and low demand forecasts adopted for this study isdramatic: By FY2012, the Low Case is only 75 percent of the Base Case, while theHigh Case is 125 percent. Not surprisingly, system expansion requirements areextremely different as a result. Table 22 compares the expansion plans requiredunder the two load forecasts.

The table suggests that savings "with NT2" would be modestly increased with higher-than-expected demand (US$299 million vs. US$277 in the Base Case). (Note thesubstantial requirement for gas turbine investment in order to meet FY2006 loadgrowth.)

Savings under a low demand forecast are significantly reduced (US$198 million). Thisresult follows from the fact that new gas-fired generation is not required in the“without NT2” case until FY2013.

Changes in the Price of Natural Gas and Other Fuels

Differences between high and low fuel price forecasts adopted for the study are notas dramatic as the spread noted for the demand forecast. (The prices adopted forthese sensitivity scenarios are reported in Appendix A3.) When scenarios are runwith either high or low fuel prices, gas remains the fuel of choice for incrementalcapacity both “with NT2” and "without NT2".

As might be expected, the low gas price scenario resulting in lower total Study Periodsavings (US$226 million) than the high gas price scenario (US$361 million). Morethermal plant reconditioning is justified under the low fuel price scenario; higher gasprices make relatively less efficient reconditioned units uneconomic in comparison withmore efficient new capacity.

Table 23 compares the Base Case results with the expected savings from NT2assuming higher and lower fuel prices.

PRESENT VALUE OF COSTS Without NT2(US$ million) Oct-09 Oct-11 A. Planning Period (2003-2014) 26,200 26,272 26,304 B. End-Effects Period 17,481 17,540 17,654 C. Study Period (A + B) 43,681 43,812 43,958

PV of Savings with NT2 A. Planning Period (2003-2014) 104 32 B. End-Effects Period 173 114 C. Study Period (A + B) 277 146 % of total cost 0.63% 0.33%

With NT2


Table 22. Sensitivity of Results to the Load Forecast

Fiscal Installed InstalledYear MW CC GT Recondition Import MW CC GT Recondition Import2003 25,697 25,697 2004 26,417 26,417 2005 26,497 26,497 2006 26,297 28,137 1,840 2007 27,678 30,918 1,400 2008 28,698 33,338 1,400 2009 29,018 35,758 2,100 2010 29,703 995 38,853 2,100 310 995 2011 29,393 42,353 3,500 310 2012 29,393 45,853 3,500 2013 29,083 49,583 3,500 230 310 2014 29,933 1,400 53,773 3,500 690 550

Total 32,100 1,400 - - 995 55,940 21,000 2,760 1,480 995

Fiscal Installed InstalledYear MW CC GT Recondition Import MW CC GT Recondition Import2003 25,697 25,697 2004 26,417 26,417 2005 26,497 26,497 2006 26,297 28,137 1,840 2007 27,678 30,918 1,400 2008 28,698 33,338 1,400 2009 29,018 35,758 2,100 2010 28,708 38,948 3,500 2011 28,398 42,138 3,500 2012 28,398 45,638 3,500 2013 29,098 700 310 49,518 3,500 690 2014 29,948 1,400 53,708 3,500 690 550

Total 32,115 2,100 - 310 - 55,875 22,400 3,220 550 -


PRESENT VALUE OF COSTS(US$ million) With NT2 Without NT2 With NT2 Without NT2 A. Planning Period (2003-2014) 21,596 21,637 31,120 31,227 B. End-Effects Period 11,413 11,570 24,326 24,519 C. Study Period (A + B) 33,010 33,208 55,447 55,746


LOW DEMAND SCENARIO HIGH DEMAND SCENARIO

Low Demand High Demand

Planned Additions (excluding NT2)Planned Additions (excluding NT2)

Planned Additions (including NT2) Planned Additions (including NT2)


-40

0

40

80

120

160

200

240

280

2010 2015 2020 2025 2030 2035

US

$ m

illi

on

with NT2 Economic Base Case Low Demand High Demand


Table 23. Sensitivity of Results to the Price of Natural Gas

GAS PRICE SENSITIVITY - ECONOMIC PRICES

Fiscal Installed InstalledYear MW CC GT Recondition Import MW CC GT Recondition Import2003 25,697 25,697 2004 26,417 26,417 2005 26,497 26,497 2006 26,297 26,297 2007 27,678 27,678 2008 29,398 700 29,398 700 2009 31,118 1,400 31,118 1,400 2010 33,043 700 230 310 995 33,203 1,400 995 2011 34,903 1,400 460 310 34,993 2,100 2012 37,003 2,100 37,093 2,100 2013 39,103 2,100 310 39,113 2,100 230 2014 41,203 2,100 550 41,123 2,100 460

Total 43,370 10,500 690 1,480 995 43,290 11,900 690 - 995

Fiscal Installed InstalledYear MW CC GT Recondition Import MW CC GT Recondition Import2003 25,697 25,697 2004 26,417 26,417 2005 26,497 26,497 2006 26,297 26,297 2007 27,678 27,678 2008 29,398 700 29,398 700 2009 31,118 1,400 31,118 1,400 2010 33,218 2,100 310 33,138 2,100 230 2011 35,078 1,400 460 310 34,928 2,100 2012 36,938 1,400 460 37,028 2,100 2013 39,038 2,100 310 39,048 2,100 230 2014 41,368 2,100 230 550 41,148 2,100 550

Total 43,535 11,200 1,150 1,480 - 43,315 12,600 460 550 -


PRESENT VALUE OF COSTS(US$ million) With NT2 Without NT2 With NT2 Without NT2 A. Planning Period (2003-2014) 24,441 24,531 28,714 28,854 B. End-Effects Period 16,069 16,205 19,671 19,892 C. Study Period (A + B) 40,510 40,736 48,385 48,746


LOW GAS PRICE SCENARIO HIGH GAS PRICE SCENARIO

Low Gas Price High Gas Price

Planned Additions (including NT2) Planned Additions (including NT2)

Planned Additions (excluding NT2) Planned Additions (excluding NT2)


-40

0

40

80

120

160

200

240

280

320

360

2010 2015 2020 2025 2030 2035

US

$ m

illi

on

with NT2 Economic Base Case Low Gas Price High Gas Price


Changes in NT2 Capital Cost

Sensitivity analyses reflecting changes in the load forecast and in fuel prices requirecompletely new runs of the PROSCREEN model for both the “with NT2” and“without NT2” cases, since modifying these parameters will impact the entire systemexpansion plan.

Changes in the capital cost of NT2, however, only affect the cost of a single plant, soreliable estimates of the resulting impact on the least-cost system expansion plan canbe prepared by simply adjusting the present value cost of the Base Case “with NT2”by the present value of the change in NT2 capital cost implied by the High and Lowcapital cost scenarios. (The required adjustments are summarized in Table 17.)

Table 24 compares the Base Case results with the expected savings from NT2assuming higher and lower capital costs for NT2. Not surprisingly, the decrease(increase) in savings produced by a 30 percent increase (decrease) in cost is dramatic.Even under the high capital cost assumption, however, NT2 produces a real netbenefit to the regional economy (US$103 million).

Table 24. Sensitivity to Changes in NT2 Capital Cost

Changes in Cost-Risk Probabilities

The selection of appropriate probabilities of occurrence for the assumed Base, Low,and High parameter values in the cost-risk analysis requires a combination ofexperience, judgment and – when available – historical evidence,38 and uncertaintyremains about the values adopted.

38 See, for example, Bacon, Robert W., John E. Besant-Jones, and Jamshid Heidarian, EstimatingConstruction Costs and Schedules: Experience with power generation projects in developing countries. WorldBank Technical Paper No. 325. Energy Series, 1996. Besant-Jones has expanded on this work in aninternal Bank document, "Assigning Probabilities to Scenarios for Risk Analysis – The Case ofHydropower Project Construction Costs".

PRESENT VALUE OF COSTS Without NT2(US$ million) BASE CASE LOW HIGH A. Planning Period (2003-2014) 26,200 26,200 26,200 26,304 B. End-Effects Period 17,481 17,307 17,656 17,654 C. Study Period (A + B) 43,681 43,507 43,856 43,958

PV of Savings with NT2 A. Planning Period (2003-2014) 104 104 104 B. End-Effects Period 173 347 (1) C. Study Period (A + B) 277 452 103 % of total cost 0.63% 1.04% 0.23%

Note: NT2 capital cost adjustments for the high and low cases has been allocated entirelyto the End-Effects Period; PROSCREEN would allocate these adjustments to thePlanning Period as well.

With NT2


To address this uncertainty, we have re-calculated the cost-risk matrix to determinean estimated “switching value”39 at which the net savings from NT2 would disappear(i.e., the net present value would be zero). In other words, we have determined howpessimistic our cost-risk probability assumptions would need to be in order toeliminate the Base Case savings reported in Table 19. Specifically,

We first assumed a very minimal "positive" probability that future eventswould prove advantageous to NT2 (i.e., would increase savings "withNT2"). Specifically, we assumed a notional 5 percent probability of (i)construction cost at the low cost estimate, (ii) demand at the high loadforecast, and (iii) natural gas price at the high fuel price forecast.

We then calculated the “negative” probability (i.e., the probability thatfuture events would be adverse to NT2) at which the net present value ofsavings from investment in NT2 would be zero. “Negative” is defined ashigh construction costs, low demand, and low natural gas price; all of theseassumption values reduce the advantages of NT2 in relation to alternativesources of generation. (Of course, the “medium” probability is the residual,i.e., 1.0 minus the positive and negative probabilities.)

We hasten to add that we are not as pessimistic about the future as this scenarioimplies: NT2 construction costs already incorporate premiums for risk; natural gasprices were already at historic lows when fuel prices were defined for this study; andthe current consensus among economists regarding medium-term growth of the Thaieconomy is very optimistic. Nevertheless, the scenario does serve to illustrate thedegree of pessimism required to make NT2 a marginal investment.

Table 25 shows the results of the switching value analysis. With positive assumptionvalues limited to a 5 percent probability, negative assumption values would berequired in seven of every eight scenarios (87 percent probability), and base caseassumption values reduced to an 8 percent probability, in order to eliminate theexpected savings from NT2.

While there is no such thing as certainty in the field of economic forecasting, theanalysis indicates that – from the perspective of real resource costs – the net benefitsaccruing from the inclusion of NT2 in the least-cost plan appear to be relativelyrobust.

39 The “switching value” is usually defined as the percentage change in a variable which would causethe project outcome to change. For our purposes, we have not calculated percentage changes in theprobabilities adopted for the cost-risk matrix.


Table 25. Economic Cost-Risk Sensitivity Test









SCENARIO RESULTS (2003 USD million)POWER DEMAND GAS PRICE

CONSTRUCTION COST POWER DEMAND GAS PRICE

Conc lu s ion 5 5

6 CONCLUSION

Our economic assessment of the project concludes that the decision to purchaseNT2 power offers significant savings to the regional power system. Based on thecomprehensive probability-weighted real resource cost-risk analysis, a real savings (i.e.,in present value terms at 2003 prices) on the order of US$269 million will accrue tothe region over the lifetime of the plant, equivalent to approximately US$0.012 perkWh sold from the NT2 project.

As summarized in Chapters 5, there are many potential circumstances in which thedecision to develop NT2 could provide far greater real resource cost savings to theregional economy. Most notable among these is a scenario of higher-than-expectedgas prices and/or higher than expected demand growth. The decision to “lock-in” ina major source of capacity at fixed price is robust to a wide range of behavior for thekey uncertain factors that influence the project’s long-term value-added. In particular,the individual scenarios show that the project is very robust with respect to fossil fuelprice volatility, a feature of energy markets in recent decades that is expected topersist.

Terms of Reference 5 7

A1 Terms of Reference

Terms of Reference for Determining the Economic Least-Cost Justification forthe Nam Theun 2 Regional Hydro-electric Power Project

[A] Context

The World Bank has received the Thailand Power Scenario Study (TPSS)40 andacknowledges its valuable contribution to understanding the commercial rationale ofthe Nam Theun 2 (NT2) Project in the context of the Thai power system. Elementsfrom the TPSS are adopted as indicated in this terms of reference (ToR), whichdescribes the next stage of the economic due diligence the Bank requires41 todetermine whether the project has a satisfactory economic cost-risk profile for theregional42 power market. The main distinguishing characteristics of this second stageanalysis are threefold: (i) to the greatest extent feasible, all values reflect real economicresource costs, (ii) the scope of work includes both the Thai and Laotian electricitymarkets, and (iii) the risk analysis consists of an integrated multi-event probabilisticframework that produces one overall quantitative result showing whetherimplementing the NT2 project for 2009 would be an acceptable economic investmentfor the power sector.

To meet the Bank’s project preparation schedule, timeliness is of the essence. Tofacilitate this objective, the tasks in this ToR that are identified in Section [G] are tobe completed, reviewed and delivered to the Bank latest June 5, 2003. The remainingtasks are due by August 1, 2003.

The Bank acknowledges that the full participation of the Electricity GeneratingAuthority of Thailand (EGAT) is important to the conduct of this study. The Bankexpects the Consultant to work with EGAT much in the manner done for the TPSS.Because the multiple scenario analysis required to implement this ToR may need asubstantial commitment of EGAT’s human and computer resources over a relativelyshort period of time, the Bank is prepared to help the Consultant and EGATaccommodate operational constraints in this respect.

[B] Study Outcome

The study outcome will be determined by means of the results profile shown in Annex1: “Cost-Risk Framework”. This profile provides for calculating the probability- 40 “Thailand Power Scenario Study”, by Robert Vernstrom, consulting economist, Bangkok, March2003. The World Bank financed and supervised this study.

41 World Bank guidelines for the economic evaluation of investment operations, including electricpower projects: OP 10.04 and GP 4.45.

42 “Regional” means Laos and Thailand in this Terms of Reference.


weighted present value (PV) costs of either implementing or not implementing NT2for 2009, given the interplay of several major uncertain factors – project cost, long-term demand for electricity and long-term economic value of natural gas as well as thesuggested probabilities of occurrence for Base Case, Lower and Higher estimates ofthese variables. The difference between the probability weighted PV cost ofimplementing the project in 2009 versus that of not implementing it is the decisioncriteria for this analysis by showing whether the project is an acceptable economicinvestment for the regional power market.

The following sections describe the Bank’s requirements for this stage of its economicdue diligence. Because the Bank is specifying these requirements for the purpose of areal resource cost-based analysis, neither the Consultant nor EGAT would be heldaccountable for specific assumptions and values that the Bank requires or to whichthe Bank agrees. The Bank acknowledges that the methods and values used in thisstudy for its purposes are completely without prejudice to different ones that EGATmay consider as more appropriate for its own operating context and requirements.

[C] Basic Parameters

1. All values will be expressed in terms of real US dollars of 2003.2. The discount rate will be 10% real.3. The power system reliability criterion for generation capacity expansion is

EGAT’s standard of 15% reserve margin over forecast peak load.4. All costs will exclude internal fiscal transfers (e.g. taxes and subsidies).5. NT2 is commissioned in 2009 in the “with project” case, or not at all in the

“without project’ case.6. The expected values of NT2 production for primary energy and secondary

energy are as stated in the TPSS. The study will check whether it is reliable toassume that the probability of under-achieving these values is negligible, andshall document evidence to support this assumption.

7. The scenarios with NT2 should include a carbon credit of $x per ton ofcarbon displaced by NT2 to be credited against the operating costs of NT2.The Bank will confirm the acceptable unit value per ton carbon.

8. The system expansion period will end in the year that the NT2 projectoutput would be fully absorbed under the low demand forecast. The durationof the run-out period for end effects will be till the year at which the residualvalue in that year would discount to an insignificant present value. The Bankwill discuss with the consultant how the power system model neutralizes endeffects before the model runs are undertaken.

9. The EGAT plant retirement schedule is adopted, subject to reportingrequirements described in Section [F].

[D] Variables

[D.1] Demand Forecast:

1. The Base Case Demand Forecast used in the Thailand Power Scenario Studyis acceptable for the Thai load. For Laotian demand, the Bank recommends a


Base Case in which Laos fully absorbs 200GWh of energy in the year theproject is commissioned.

2. For both countries the Low Case demand forecast will be keyed off the BaseCase forecast using the following equation, reflecting the percentage gapbetween these forecasts the Bank considers appropriate by year 10 into theforecast period (based on forecasting experience in Thailand and elsewhere):

(1+grL)^10 = 0.75*(1+grB)^10

where grL means Low Case growth rate of demand and grB means Base Casegrowth rate of demand.

3. The High Case load forecast will be symmetrical to that of the Low Case. Thegrowth rate for the High Case (“grH”) will therefore be determined accordingto the following formula:

(1+grH)^10 = 1.25*(1+grB)^10

[D.2] NT2 Project

1. The Bank will provide the real cash flows for the Base Case economicinvestment and operating costs of the NT2 project based on data from theproject sponsor’s financial model. This cash flow series will exclude transfersand sunk costs, but include incremental sponsor development costs thatreflect use of real resources.

2. The High Case for the construction cost of NT2 will be 30% above of theexpected construction cost used for the Base Case. The Low Case for theconstruction cost of NT2 will be 30% below that of the Base Case.

[D.3] Other Power Generation Technologies

1. The screening curve analysis of the type used in the TPSS will be deployedusing real economic costs to determine the least-cost alternative options,using the same technologies as in the TPSS. It is expected that as in the TPSS,natural gas will emerge as the primary alternative to NT2. In case it does not,several aspects of this ToR related to fuel value and fuel value risk will need tobe revised accordingly.

2. The real economic costs of alternative generation capacity will also includeprivate sector incremental development costs appropriate to thosetechnologies.

3. The Bank recommends that there be a spread of about USD200/kW toappropriately reflect the EPC cost difference between GT and CCGT plant.

4. The Bank will confirm with the consultant the actual EPC costs anddevelopment cost margins to be used for GT and CCGT capacity.

5. The Consultant will assume that Laos’ alternative to NT2 for meeting thatportion of its demand would be import of electricity from Thailand.

[D.4] Oil Products and Natural Gas


1. The Bank will confirm with the consultant the real values it considersacceptable for oil product prices in the screening curve analysis, as well as theBase, Low and High natural gas price trajectories.

2. The coal prices in the TPSS may be adopted, unless it seems appropriate tomake some adjustment in relation to the assumptions for natural gas and oilproduct prices to be used in this study.

[D.5] Transmission

1. The project-associated transmission works in Laos are included in the projectcost.

2. The project-associated incremental transmission costs for Thailand need to bedetermined in co-operation with EGAT on a basis that does not include anyother future hydro exports from Laos to Thailand, because of theiruncertainty, notwithstanding the higher level of potential exports containedin the MoU between the two countries on power exports from Laos toThailand.

3. If EGAT and the consultant believe that the non-NT2 options also requireincremental generation-associated transmission works, the economic costs ofthese should be determined and included.

[E] Modeling

1. The Consultant will use EGAT’s Proscreen Model as in the TPSS, subject tothe custom parameter and variable assumptions made for this study.

2. Before the modeling begins, Bank staff will obtain from EGAT and theconsultant, by verbal and documentary communication, a clear understandingof how this model works, especially but not limited to the following factors: (i)optimization and simulation characteristics, (ii) treatment of mixed hydro-thermal capacity (valuation of stored water, optimization of hydro-electricreservoir management), (iii) dispatching optimization (stacking merit order anddispatching algorithm), and (iv) calculation of end effects.

3. In these model runs, NT2 and all other generation capacity on the regionalpower system – including existing capacity owned and operated by IPPs - willbe subject to economic dispatch for meeting incremental demand and thespecified amount of Laotian demand, without consideration of contractualtake-or-pay constraints.

4. Before proceeding with paragraph E5 below, two sensitivity tests are required:(i) for the MMM case (ref. Annex 1) a “with” and “without” NT2 comparisonin a situation where the commissioning of NT2 is delayed for 24 months, theinvestment cash flow being extended over the additional time period, and (ii)the same test but with a 30% cost over-run of NT2 (the HMM case of Annex1). The results of these tests should be reported to the Bank beforecommencing the model runs described below, to determine whether it wouldbe appropriate to amend the cost-risk analysis framework (Annex 1).

5. To complete the Cost-Risk Framework (Annex 1), a total of 18 scenario runswill be required, 9 with NT2 and 9 without NT2 as described in the Annex.The scenarios are formed from combinations of two planning variables –


power demand and natural gas price. Three cases– high, base, low – are usedfor each of these variables.

6. The 9 scenarios run with NT2 will be expanded to 27 scenarios by combiningmanually the three cases for the construction cost of NT2 with the results ofthese scenarios.

7. The probabilities associated with the High, Medium and Low assumptions arestated in Annex 1.

8. A second set of model runs for these scenarios will be carried out underwhich the economic values are converted to commercial values, but expressedin real US dollars of 2003, using the same framework as in Annex 1, in orderto assess the commercial sustainability of the NT2 Power Purchase Agreementagainst the underlying economic trends in the regional power market.

[F] Reporting

This study will serve a number of purposes eventually involving a considerable range ofaudiences within and outside of the World Bank. For this reason, it is essential thatthe reporting of this work be thorough and self-standing, so that the assumptions,methods and corresponding results are detailed, transparent and easilyunderstandable.

Without limitation to the generality of this requirement, the Bank stresses theimportance of comprehensive documentation, in Annexes as appropriate, for certainkey aspects:

1. The economic characteristics of the NT2 project.2. The Base Case demand forecast (forecasting methods, key input assumptions,

benchmark data and main results per consumer category);3. Justification for NT2 hydrological performance assumption;4. Explanation for assuming in respect of NT2 that there is no systemic bias in

the estimated construction cost for NT2, namely that no difference should beassumed between Base Case estimated and Base Case expected project cost;

5. The valuation of oil products and natural gas;6. The status of the individual power plants included in the EGAT retirement

schedule adopted for this study;7. Model characteristics and modeling implementation;8. Description of the logic underlying the cost-risk decision framework;9. Explanation of results, and enhanced explanation of any counter-intuitive

results;10. Explanation of differences in values and results between the economic and

commercial model runs; and11. For the commercial runs, how the PPA revenues are composed and converted

to US dollar terms.12. For data output, the Bank requires the present values of each of the major

components contributing to the total PV cost of each scenario, in order tofacilitate a clear understanding of the reasons for differences in total PV costbetween scenarios. The Bank also requires production and value data for thedispatch of each plant at five year intervals in the MMM case, to better


understand how the model handles the merit order, and the contribution inenergy and cost of each operating facility.

[G] Timing of Deliverables

Items required for June 5th, 2003:

The results of the model runs; this includes all the aforementioned factors necessaryfor operating the model and to be agreed with the Bank.

Items required for August 1, 2003:

The Report write-up as outlined in Section [F].

May 8, 2003


Annex 1: Cost-Risk Framework

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647

A B C D E F G H

Value Probability Value Probability Value Probability Value Probability

h 0.25 h 0.25 h 0.25 hhh 0.01563h 0.25 h 0.25 m 0.50 hhm 0.03125h 0.25 h 0.25 l 0.25 hhl 0.01563h 0.25 m 0.50 h 0.25 hmh 0.03125h 0.25 m 0.50 m 0.50 hmm 0.06250h 0.25 m 0.50 l 0.25 hml 0.03125h 0.25 l 0.25 h 0.25 hlh 0.01563h 0.25 l 0.25 m 0.50 hlm 0.03125h 0.25 l 0.25 l 0.25 hll 0.01563m 0.50 h 0.25 h 0.25 mhh 0.03125m 0.50 h 0.25 m 0.50 mhl 0.06250m 0.50 h 0.25 l 0.25 mhi 0.03125m 0.50 m 0.50 h 0.25 mmh 0.06250m 0.50 m 0.50 m 0.50 mmm 0.12500m 0.50 m 0.50 l 0.25 mml 0.06250m 0.50 l 0.25 h 0.25 mlh 0.03125m 0.50 l 0.25 m 0.50 mlm 0.06250m 0.50 l 0.25 l 0.25 mll 0.03125l 0.25 h 0.25 h 0.25 lhh 0.01563l 0.25 h 0.25 m 0.50 lhm 0.03125l 0.25 h 0.25 l 0.25 lhl 0.01563l 0.25 m 0.50 h 0.25 lmh 0.03125l 0.25 m 0.50 m 0.50 lmm 0.06250l 0.25 m 0.50 l 0.25 lml 0.03125l 0.25 l 0.25 h 0.25 llh 0.01563l 0.25 l 0.25 m 0.50 llm 0.03125l 0.25 l 0.25 l 0.25 lll 0.01563

WGTD PV 1.00000[B] Present Values Without NT2

Value Probability Value Probability Value Probability

h 0.25 h 0.25 hhh 0.06250h 0.25 m 0.50 hhm 0.12500h 0.25 l 0.25 hhl 0.06250m 0.50 h 0.25 hmh 0.12500m 0.50 m 0.50 hmm 0.25000m 0.50 l 0.25 hml 0.12500l 0.25 h 0.25 hlh 0.06250l 0.25 m 0.50 hlm 0.12500l 0.25 l 0.25 hll 0.06250

WGTD PV 1.00000

0.00000Net PV with NT2

Power Demand Gas Price Scenario

Cost-Risk Analysis Matrix[A] Present Values with NT2

Construction Cost Power Demand Gas Price Scenario

Thailand Demand Forecast 6 5

A2 Thailand Demand Forecast

This appendix provides details of Thailand’s official Aug-02 load forecast. Thisforecast, supplemented by Lao PDR domestic load to be served by NT2 (75 MWcapacity and 300 GWh generation), is the Base Case load forecast for our regionalstudy.

This appendix includes the following tables:

Table A2-1. EGAT Total Generation Requirement Forecast

Table A2-2. EGAT Total Sales Forecast

Table A2-3. MEA Purchases and Sales Forecast by Customer Class

Table A2-4. PEA Purchases and Sales Forecast by Customer Class


Table A2-1. EGAT Total Generation Requirement Forecast

Base Case_August 2002

Fiscal Peak Energy Load

Year Increase Increase Factor

MW % GWh % %

Actual1991 8,045.00 951.30 13.41 49,225.03 6,036.24 13.98 69.85

1992 8,876.90 831.90 10.34 56,006.44 6,781.41 13.78 72.02

1993 9,730.00 853.10 9.61 62,179.73 6,173.29 11.02 72.95

1994 10,708.80 978.80 10.06 69,651.14 7,471.41 12.02 74.25

1995 12,267.90 1,559.10 14.56 78,880.37 9,229.23 13.25 73.40

1996 13,310.90 1,043.00 8.50 85,924.14 7,043.77 8.93 73.69

1997 14,506.30 1,195.40 8.98 92,724.66 6,800.52 7.91 72.97

1998 14,179.90 -326.40 -2.25 92,134.44 -590.22 -0.64 74.17

1999 13,712.40 -467.50 -3.30 90,414.15 -1,720.29 -1.87 75.27

2000 14,918.30 1,205.90 8.79 96,780.72 6,366.57 7.04 74.06

2001 16,126.40 1,208.10 8.10 103,165.20 6,384.48 6.60 73.03

Average Growth1991-2001 - 821.15 7.20 - 5,452.40 7.68 -

Forecast2002 16,700.00 573.60 3.56 108,036.00 4,870.80 4.72 73.85

2003 17,843.00 1,143.00 6.84 114,754.00 6,718.00 6.22 73.42

2004 19,029.00 1,186.00 6.65 122,024.00 7,270.00 6.34 73.20

2005 20,295.00 1,266.00 6.65 130,232.00 8,208.00 6.73 73.25

2006 21,648.00 1,353.00 6.67 139,000.00 8,768.00 6.73 73.30

2007 23,020.00 1,372.00 6.34 147,835.00 8,835.00 6.36 73.31

2008 24,450.00 1,430.00 6.21 157,064.00 9,229.00 6.24 73.33

2009 26,143.00 1,693.00 6.92 168,004.00 10,940.00 6.97 73.36

2010 27,711.00 1,568.00 6.00 178,079.00 10,075.00 6.00 73.36

2011 29,321.00 1,610.00 5.81 188,446.00 10,367.00 5.82 73.37

2012 31,014.00 1,693.00 5.77 199,378.00 10,932.00 5.80 73.39

2013 32,842.00 1,828.00 5.89 211,146.00 11,768.00 5.90 73.39

2014 34,743.00 1,901.00 5.79 223,437.00 12,291.00 5.82 73.41

2015 36,754.00 2,011.00 5.79 236,364.00 12,927.00 5.79 73.41

2016 38,851.00 2,097.00 5.71 249,878.00 13,514.00 5.72 73.42

Average Growth1992-1996 - 1,053.18 10.60 - 7,339.82 11.79 -

1997-2001 - 563.10 3.91 - 3,448.21 3.73 -

2002-2006 - 1,104.32 6.07 - 7,166.96 6.14 -

2007-2011 - 1,534.60 6.26 - 9,889.20 6.28 -

2012-2016 - 1,906.00 5.79 - 12,286.40 5.81 -

Thailand Load Forecast Subcommittee

August 2002

MW GWh


Table A2-2. EGAT Total Sales Forecast


Fiscal Peak Energy Load

Year Increase Increase Factor

MW % GWh % %

Actual1991 8,000.92 926.17 13.09 44,773.24 5,404.46 13.73 63.88

1992 9,243.13 1,242.21 15.53 50,770.86 5,997.62 13.40 62.70

1993 10,336.68 1,093.55 11.83 56,558.43 5,787.57 11.40 62.46

1994 11,424.52 1,087.84 10.52 63,642.85 7,084.42 12.53 63.59

1995 12,990.34 1,565.82 13.71 72,779.57 9,136.72 14.36 63.96

1996 14,263.97 1,273.63 9.80 79,450.96 6,671.39 9.17 63.59

1997 15,475.54 1,211.57 8.49 85,896.66 6,445.70 8.11 63.36

1998 1 / 13,724.01 -1,751.53 -11.32 85,597.60 -299.06 -0.35 71.20

1999 13,596.30 -127.70 -0.93 84,512.03 -1,085.57 -1.27 70.96

2000 14,815.02 1,218.72 8.96 90,725.42 6,213.39 7.35 69.91

2001 16,005.76 1,190.74 8.04 97,412.45 6,687.03 7.37 69.48

Forecast

2002 16,643.00 637.24 3.98 102,260.00 4,847.55 4.98 70.14

2003 17,615.00 972.00 5.84 108,437.00 6,177.00 6.04 70.27

2004 18,724.00 1,109.00 6.30 115,447.00 7,010.00 6.46 70.38

2005 19,951.00 1,227.00 6.55 123,249.00 7,802.00 6.76 70.52

2006 21,270.00 1,319.00 6.61 131,553.00 8,304.00 6.74 70.60

2007 22,630.00 1,360.00 6.39 140,134.00 8,581.00 6.52 70.69

2008 24,062.00 1,432.00 6.33 149,258.00 9,124.00 6.51 70.81

2009 25,679.00 1,617.00 6.72 159,965.00 10,707.00 7.17 71.11

2010 27,238.00 1,559.00 6.07 169,885.00 9,920.00 6.20 71.20

2011 28,842.00 1,604.00 5.89 180,070.00 10,185.00 6.00 71.27

2012 30,514.00 1,672.00 5.80 190,798.00 10,728.00 5.96 71.38

2013 32,295.00 1,781.00 5.84 202,344.00 11,546.00 6.05 71.52

2014 34,159.00 1,864.00 5.77 214,391.00 12,047.00 5.95 71.65

2015 36,145.00 1,986.00 5.81 227,324.00 12,933.00 6.03 71.79

2016 38,223.00 2,078.00 5.75 240,786.00 13,462.00 5.92 71.91

Average Growth1992-1996 - 1,252.61 12.26 - 6,935.54 12.15 -

1997-2001 - 348.36 2.33 - 3,592.30 4.16 -

2002-2006 - 1,052.85 5.85 - 6,828.11 6.19 -

2007-2011 - 1,514.40 6.28 - 9,703.40 6.48 -

2012-2016 - 1,876.20 5.79 - 12,143.20 5.98 -

Note : 1/ 1991 - 1997 are non-coincident peak, while 1998 onwards are coincident peak of each

electricity authority and direct customers.

Thailand Load Forecast Subcommittee

August 2002

MW GWh


Table A2-3. MEA Purchases and Sales Forecast by Customer Class

Base Case_August 2002 Unit : GWh

Historical Forecast

DESCRIPTION 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554 2555 2556 2557 2558 2559

Residential (Total) 6,669 7,355 7,381 7,678 8,057 8,461 8,885 9,353 9,836 10,340 10,851 11,375 11,903 12,443 13,000 13,567 14,148

%increase 3.43 10.29 0.35 4.02 4.94 5.01 5.01 5.27 5.16 5.12 4.94 4.83 4.64 4.54 4.48 4.36 4.28

< 150 kWh per month 435 425 425 431 440 450 460 469 478 486 494 502 510 518 526 533 541

%increase 4.07 -2.30 0.00 1.41 2.09 2.27 2.22 1.96 1.92 1.67 1.65 1.62 1.59 1.57 1.54 1.33 1.50

> 150 kWh per month 6,234 6,930 6,956 7,247 7,617 8,011 8,425 8,884 9,358 9,854 10,357 10,873 11,393 11,925 12,474 13,034 13,607

%increase 3.38 11.16 0.38 4.18 5.11 5.17 5.17 5.45 5.34 5.30 5.10 4.98 4.78 4.67 4.60 4.49 4.40

Small General Service 4,334 4,749 4,848 5,029 5,275 5,529 5,816 6,107 6,408 6,722 7,041 7,367 7,643 7,926 8,217 8,516 8,824

%increase 5.32 9.58 2.08 3.73 4.89 4.82 5.19 5.00 4.93 4.90 4.75 4.63 3.75 3.70 3.67 3.64 3.62

Medium General Service 7,494 7,817 8,024 8,343 8,731 9,147 9,598 10,026 10,450 10,919 11,384 11,852 12,269 12,697 13,135 13,583 14,042

%increase 4.96 4.31 2.65 3.98 4.65 4.76 4.93 4.46 4.23 4.49 4.26 4.11 3.52 3.49 3.45 3.41 3.38

Large General Service 10,247 11,122 11,682 12,296 12,951 13,629 14,309 14,979 15,614 16,337 17,054 17,759 18,376 18,995 19,617 20,241 20,865

%increase 13.00 8.54 5.04 5.26 5.33 5.24 4.99 4.68 4.24 4.63 4.39 4.13 3.47 3.37 3.27 3.18 3.08

Specific Business 1,442 1,517 1,559 1,623 1,705 1,756 1,814 1,869 1,936 1,997 2,058 2,132 2,207 2,284 2,363 2,443 2,524

%increase 5.80 5.20 2.77 4.11 5.05 2.99 3.30 3.03 3.58 3.15 3.05 3.60 3.52 3.49 3.46 3.39 3.32

Government Offices & NPO 1,141 1,134 1,179 1,225 1,279 1,330 1,384 1,440 1,489 1,531 1,574 1,614 1,655 1,697 1,740 1,783 1,826

%increase -16.53 -0.61 3.97 3.90 4.41 3.99 4.06 4.05 3.40 2.82 2.81 2.54 2.54 2.54 2.53 2.47 2.41

Street Lighting 148 153 178 186 195 204 210 215 220 225 229 232 236 240 243 246 250

%increase 4.96 3.38 16.34 4.49 4.84 4.62 2.94 2.38 2.33 2.27 1.78 1.31 1.72 1.69 1.25 1.23 1.63

TOTAL ENERGY SALES 31,475 33,847 34,851 36,380 38,193 40,056 42,016 43,989 45,953 48,071 50,191 52,331 54,289 56,282 58,315 60,379 62,479

%increase 6.18 7.54 2.97 4.39 4.98 4.88 4.89 4.70 4.46 4.61 4.41 4.26 3.74 3.67 3.61 3.54 3.48

ENERGY RECEIVED FROM EGAT 32,889 35,327 36,378 38,015 39,909 41,855 43,904 45,965 48,018 50,231 52,446 54,682 56,729 58,811 60,935 63,092 65,287

%increase 6.32 7.41 2.98 4.50 4.98 4.88 4.90 4.69 4.47 4.61 4.41 4.26 3.74 3.67 3.61 3.54 3.48

PEAK DEMAND (MW) 5,800 6,229 6,418 6,706 7,041 7,385 7,748 8,112 8,475 8,865 9,256 9,652 10,014 10,381 10,757 11,138 11,528

%increase 8.27 7.40 3.03 4.49 5.00 4.89 4.92 4.70 4.47 4.60 4.41 4.28 3.75 3.66 3.62 3.54 3.50

% LOAD FACTOR 64.73 64.74 64.70 64.71 64.70 64.70 64.69 64.68 64.68 64.68 64.68 64.67 64.67 64.67 64.67 64.66 64.65

% LOSS 4.30 4.19 4.20 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30

0

1

2

2000

0

1

2

1


Table A2-4. PEA Purchases and Sales Forecast by Customer Class

Unit: GWh

Historical FORECAST

DESCRIPTION 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554 2555 2556 2557 2558 2559

Residential 12,190 13,602 14,270 15,206 16,257 17,432 18,722 20,092 21,532 23,044 24,633 26,303 28,071 29,946 31,941 34,065 36,327

%increase 4.66 11.59 4.91 6.56 6.91 7.23 7.40 7.32 7.17 7.02 6.90 6.78 6.72 6.68 6.66 6.65 6.64

Small General Service 4,112 4,467 4,662 4,965 5,317 5,711 6,145 6,598 7,072 7,568 8,087 8,632 9,207 9,814 10,458 11,141 11,867

%increase 3.85 8.62 4.37 6.51 7.09 7.41 7.60 7.37 7.18 7.01 6.87 6.74 6.65 6.60 6.56 6.53 6.51

Medium General Service 9,820 10,430 10,737 11,399 12,154 13,028 14,051 15,139 16,276 17,464 18,704 20,000 21,362 22,794 24,307 25,906 27,598

%increase 7.58 6.21 2.94 6.16 6.63 7.19 7.86 7.74 7.51 7.30 7.10 6.93 6.81 6.71 6.64 6.58 6.53

Large General Service * 22,350 23,688 25,595 27,511 29,732 32,171 34,789 37,507 40,529 44,907 48,295 51,589 55,408 59,739 64,215 69,209 74,334

%increase 11.46 5.99 8.05 7.48 8.07 8.20 8.14 7.81 8.06 10.80 7.54 6.82 7.40 7.82 7.49 7.78 7.40

Specific Business 1,311 1,431 1,509 1,614 1,725 1,843 1,973 2,112 2,258 2,412 2,574 2,747 2,929 3,123 3,329 3,547 3,779

%increase 4.91 9.15 5.46 6.98 6.86 6.87 7.07 7.02 6.91 6.82 6.75 6.70 6.65 6.62 6.58 6.56 6.53

Government Offices & NPO 1,970 2,264 2,365 2,547 2,747 2,957 3,179 3,413 3,659 3,917 4,189 4,475 4,777 5,097 5,436 5,796 6,178

%increase 8.79 14.95 4.47 7.70 7.84 7.67 7.50 7.34 7.20 7.06 6.94 6.83 6.75 6.70 6.65 6.62 6.60

Agricultural Pumping 145 179 188 202 216 229 241 254 267 280 294 309 324 339 356 373 391

%increase -22.00 23.48 5.47 7.44 6.60 6.00 5.55 5.22 5.09 5.01 4.95 4.91 4.88 4.86 4.84 4.82 4.80

Temporary 473 414 382 396 413 435 463 498 535 574 615 658 704 753 805 859 916

%increase -5.53 -12.57 -7.72 3.60 4.38 5.30 6.41 7.59 7.41 7.27 7.16 7.08 6.99 6.91 6.82 6.74 6.66

TOTAL SALES 52,370 56,473 59,709 63,840 68,560 73,806 79,564 85,613 92,127 100,165 107,392 114,713 122,783 131,607 140,846 150,896 161,391

%increase 7.91 7.83 5.73 6.92 7.39 7.65 7.80 7.60 7.61 8.73 7.21 6.82 7.03 7.19 7.02 7.14 6.96

Free of Charge 665 643 747 813 880 950 1,023 1,099 1,180 1,266 1,357 1,454 1,557 1,668 1,785 1,909 2,041

%increase 37.23 -3.19 16.14 8.82 8.28 7.91 7.65 7.47 7.35 7.26 7.20 7.16 7.11 7.07 7.02 6.97 6.93

TOTAL CONSUMPTIONS 53,035 57,117 60,456 64,654 69,441 74,756 80,587 86,713 93,307 101,431 108,749 116,167 124,340 133,274 142,631 152,805 163,432

%increase 8.20 7.70 5.85 6.94 7.40 7.65 7.80 7.60 7.60 8.71 7.21 6.82 7.04 7.19 7.02 7.13 6.95

* included standby rate


Fuel Price Assumptions 7 1

A3 Fuel Price Assumptions

This appendix includes the following table:

Table A3-1. Economic Fuel Prices Adopted for the Study (constant US$2003)

Following the table is an excerpt from Appendix 7 of the Economics Annex of WorldBank's draft Project Appraisal Document for the NT2 Project, which outlines themethodology employed to develop the natural gas price projections adopted for thecurrent study.


Table A3-1. Economic Fuel Price Projections (constant US$2003)

Real Economic Prices - Base CaseFiscal Natural Gas Hvy Oil 3.5% Diesel Lignite Imported CoalYear USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.55 3.39 6.10 1.21 1.54 2004 2.44 2.74 4.94 1.20 1.55 2005 2.40 2.58 4.65 1.19 1.53 2006 2.36 2.42 4.37 1.17 1.52 2007 2.32 2.27 4.10 1.15 1.51 2008 2.31 2.31 4.17 1.14 1.50 2009 2.30 2.35 4.23 1.12 1.48 2010 2.29 2.38 4.29 1.11 1.47 2011 2.28 2.41 4.34 1.10 1.45 2012 2.27 2.44 4.40 1.08 1.44 2013 2.26 2.47 4.45 1.06 1.43 2014 2.24 2.50 4.50 1.05 1.41

End Effect 2.27 2.50 4.50 1.05 1.41

Average Annual Growth (%)2003-2014 -1.1% -2.7% -2.7% -1.3% -0.8%

Real Economic Prices - Low CaseFiscal Natural Gas Hvy Oil 3.5% Diesel Lignite Imported CoalYear USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.32 3.00 5.40 1.21 1.24 2004 2.21 2.15 3.89 1.20 1.24 2005 2.16 1.93 3.49 1.19 1.22 2006 2.13 1.78 3.23 1.17 1.22 2007 2.09 1.64 2.97 1.15 1.21 2008 2.07 1.59 2.88 1.14 1.20 2009 2.05 1.54 2.79 1.12 1.19 2010 2.03 1.49 2.70 1.11 1.17 2011 2.00 1.44 2.62 1.10 1.16 2012 1.99 1.43 2.58 1.08 1.15 2013 1.97 1.41 2.55 1.06 1.14 2014 1.95 1.39 2.52 1.05 1.13

End Effect 2.00 1.39 2.52 1.05 1.13


Real Economic Prices - High CaseFiscal Natural Gas Hvy Oil 3.5% Diesel Lignite Imported CoalYear USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.81 3.92 7.04 1.21 1.85 2004 2.81 3.92 7.05 1.20 1.85 2005 2.79 3.87 6.96 1.19 1.84 2006 2.76 3.83 6.89 1.17 1.82 2007 2.74 3.80 6.82 1.15 1.81 2008 2.72 3.75 6.75 1.14 1.79 2009 2.69 3.71 6.67 1.12 1.78 2010 2.67 3.67 6.59 1.11 1.76 2011 2.64 3.62 6.50 1.10 1.75 2012 2.63 3.67 6.59 1.08 1.73 2013 2.62 3.71 6.66 1.06 1.71 2014 2.61 3.75 6.74 1.05 1.70

End Effect 2.60 3.75 6.74 1.05 1.70


1/ Assumed fuel heat content: - Natural Gas: 1,000 Mbtu/MCuF - Heavy Oil 3.5%: 38,886 Mbtu/MLtr - Diesel: 36,307 Mbtu/MLtr - Lignite: 10,912 Mbtu/kTon - Imported Coal: 26,467 Mbtu/kTon


Natural Gas Valuation

An important component of the economic due diligence on the NT2 project is todetermine whether NT2 is cost-effective for the Thai power system, as the project’sprimary purpose and underlying bankability relates to the Thai power market. Thiscost-effectiveness is assessed by evaluating whether the project is least-cost for theduty-service envisaged. One of the most important determining factors is the value ofnatural gas that would be used in combined cycle gas turbines, as these are the mostlikely economic alternative to NT2.

The long-term supply and demand outlook for natural gas, and its opportunity costwhether as an export or import commodity are key factors determining theappropriate principles for calculating its economic value. The industry has grownconsiderably and the long-term supply: demand picture has evolved over the pastseveral decades. As well, because of the commercial interests at stake between buyersand sellers, competition for the market between sellers, the real uncertainty aboutfuture demand and supply conditions and the complexity of the contractingarrangements, this is an industry that doles out information very cautiously. Theinsights leading to the valuations presented in this note rely for the most part onverbally communicated confidential information from players active in the industry,some power sector documentation and some relevant oil price projections providedby the World Bank. While this is not the optimal basis for the purpose at hand, it wassufficient for developing reasonable valuations.

This note develops the value series in the following steps:

1. Principles of commodity valuation;2. Evidence of long term supply and demand for natural gas in Thailand;3. Comments on the market structure;4. Implications of (2) and (3) for the approach to valuation;5. Insights about economic value from contracting principles (GPAs) in Thailand;6. Calculations and projections (Base, low and high gas value cases).

Natural gas may be valued at its economic resource costs of finding, developing,producing (EDP) and transporting the commodity (supply cost basis), or at itsopportunity value as an export commodity or import requirement (border pricebasis). It may also be appropriate to include a depletion premium (also called a “usercost”). This reflects the possibility that an increased current use of the resourceaccelerates the time path to depletion, at which point a “backstop” price would bepaid for the commodity that replaces it.

The supply cost basis is appropriate where the potential supply of natural gas is verylarge relative to the market, with little likelihood over an economically meaningful timeperiod that foregone economic export potential or heavy domestic use would triggerborder prices as the key determinant of economic value. Save for these circumstances,border prices, or a combination of supply cost and depletion premium based on


expected border prices should be the valuation basis. Which to use is informed by thedata.Economic supply costs are the real costs incurred over time of finding, developing,producing and transporting the commodity, net of taxes and royalties. Border pricesare projected real f.o.b. netbacks to the wellhead in respect of forgone exports, or c.i.f.import values in respect of imported gas, net of taxes and royalties. The user cost is aprice signal that tells consumers the present value consequences of an increase in theiruse of an exhaustible resource. It compensates the resource owner who may choosewhether to leave the resource in the ground for future appreciation or produce itsooner. The calculation of a user cost requires knowing the time path to depletion,the shape of the marginal cost curves with and without the incremental consumptionover that time and the likely cost of the backstop at depletion time. The moreuncertain the basis of the supply, demand and cost projections, the lower theexpected backstop value, the further off the expected depletion time and the flatterthe marginal cost curves, the less the attention that should be focused on user costs.All of these factors indicate that user costs should not be computed for Thailand.

On the whole, the industry is optimistic about both the resource base and demandgrowth. Evidence of this optimism is these companies’ continued commitment ofresources to exploration and development as needed, the creation of long term jointarrangements between countries sharing resources in the Gulf of Thailand43, and aone billion dollar pipeline from the Gulf to the mainland (target of January 2006).Existing transportation capacity is nearing saturation. The new line will almost doubleexisting transportation capacity. This capacity should be fully utilized by 2015, basedon projected demand growth of about 6% per year.

The R/P ratio is now about 20. This is higher than the industry typically considersideal, and is partly the result of conservatively regulated reservoir depletion rates, aswell as strenuous effort to expand the industry over the past two decades. Given thiscomfortable supply position, the market will pace reserves additions; however therewill be a rush between companies to reserve capacity in the new pipeline. This meansdeveloping new GPAs over the next few years and proving-up the necessary reservesas required.

The industry views demand as driving new contracts. Producers use demand forecastsfrom PTT and EGAT to do their E&P planning. Hence supply will evolve to meetgrowing demand.

Several sources say that supply costs have declined dramatically over the past twentyyears with major advances in exploration and drilling technology. The latter isespecially important for the Gulf of Thailand, which is geologically fractured. Theysuggest that future E&P costs should decrease very gradually in well-known areas, butcosts could increase due to more difficult production conditions and higher CO2

content of the gas in certain other off shore areas. It is not clear whether to believethat aggregate supply costs in the future will remain about the same, increase

43 These include the Myanmar Thailand joint area and the Thai Kampuchea overlap – there is adispute about resource sharing between the latter.


moderately or decrease moderately. The supply from Myanmar is about 50% costlierthan that from Thailand, and has a 30% share in the market. This share varies fromperiod to period, its value being uncertain over the long term.

Regarding demand, the power sector absorbs about 80% of consumption and theindustrial sector the other 20%. This split is likely to be sustained. Assuming thatpower sector and industrial demand continue to grow at 6% per year over the longterm, gas supply from known areas should be adequate for at least the next severaldecades.

The basic market structure is one of monopoly buyer and competition betweensellers. The four majors are UNOCAL, TotalElfFina, PTT (now privatized) and Mitsui.There are several other companies with a smaller presence in the E&P business. Stiffdownward pressure on prices is exercised by a vigilant public, vigilant government andthe monopoly buyer (PTT) having a window on the producing industry through itsown E&P subsidiary. Several industry players assert that the producers do not cohere,they are not coordinated, and they are vying with each other for market share.

The predominant transaction form is long-term contracts covering the life of aconcession, with regulated depletion rates (1 in 6000) to prevent reserves lossthrough accelerated depletion. Each concession has its own particular cost structureand gas quality; hence the detailed contract terms vary from contract to contract.However, there is a general pricing structure common to most contracts.

The following factors distilled from the foregoing discussion seem most pertinent tothe choice of valuation approach:

i. there is apparent comfort in respect of long-term supply from domestic reservesand the MTJDA, with no issue of export opportunity cost;

ii. a minority share of gas comes from Myanmar, it being expected that this sharewill vary moderately over time; the time period to depletion – if it ever happens– is far off for backstop values to have much weight in present value terms;

iii. there are competitive pressures characterizing the contracting process, suchthat the terms of the contracts can be said to reflect a market-based valuationof the cost recovery and remuneration levels needed to keep the producers inoperation;

iv. in general, there is uncertainty about the size of future reserves additions andtheir incremental costs, the predominant view in the industry being optimistic onsupply and rather unclear about whether marginal cost will increase moderatelyor decrease moderately.

Under these conditions, it seems most appropriate to base the economic value ofnatural gas on:

i. the cost of discovery, development and production for local supply as evidencedin current pool pricing;

ii. border price for the Myanmar supply, iii. removal of taxes and royalties from domestic production, iv. addition of the PTT marketing margin and


v. estimated LRMC of gas transmission on a postage stamp basis (there being noinformation available allowing the computation of point to point marginal costtransmission pricing).

Because each GPA differs and we do not have access to the individual contracts, itwas necessary to create a “typical contract” the key elements of which industryinterviewees claimed to be representative of the average.

The basic pricing structure, valid for the duration of the contract, is as follows. In thecontracts, the current gas price payable to producers is specified in THB. It is theresult of applying a series of indices (contained in one formula) to a base price.

The indexation formula applied to the Base Price reflects changes in: (i) the fob priceof 3.5%S HFO Singapore, (ii) a petroleum industry machinery inflation index reflectingUSD inflation, (iii) the Thai CPI reflecting Thai domestic inflation, (iv) an exchangerate adjuster and (v) a constant. Given that our numeraire in this project analysis isUSD, the machinery index, the Thai CPI index and the exchange rate adjuster wouldbe offsetting in future price projections using the PPP method of exchange rateprojection. When working in USD prices rather than THB prices, the only necessaryelement of the index is the HFO adjuster, having a weight of about 30% in the index.PTT charges EGAT and IPPs a marketing margin of 1.75% of the sales price, plus apostage-stamp pipeline toll.

The pen-ultimate step for moving from commercial value to economic value is toremove transfers from the commercial price, these being royalties and taxes. Theroyalty rate for new reserves is 12.5% of the producers’ selling price. The actualamount of income tax producers pay in total or per mmbtu of gas sold cannot beknown without access to company accounts, and we have no such access. Anapproximation of the income tax load is made by taking the difference between theprojected producer selling price net of royalties from the foregoing steps, deducting anadvised producer EDP cost, the residual being gross profit, of which 50% is deductedin taxes. These deductions of income taxes and royalties are made only for the Thaiportion of gas supply, because Myanmar is beyond the welfare boundary of theanalysis. At the welfare boundary Thailand faces a border price, and any embeddedtaxes and royalties going to the Government of Myanmar are included in economiccosts facing Thailand, therefore not deducted.

The final calculation is to convert the nominal economic natural gas values into realvalues by deflating the nominal series with the MUV index. This is the index theWorld Bank uses for converting hydrocarbon prices between real and nominal values.

Low and High Value Projections: The gas value projections for the low andhigh cases consist of two changes to the base case presented above:

Firstly, the values of HFO to be used in the price adjustment index are recalculatedusing high and low price projections for the World Bank Crude Mix. These latter


projections were prepared per World Bank methodology44 as done when it publishedthese ranges in the past. The current projection is asymmetrical, reflecting anassessment that oil prices are unlikely to be sustained over the long term at pricesbelow USD 12.00/bbl or above USD 33.00/bbl (current) within a 70% range ofpossible outcomes.

Secondly, the Myanmar share is decreased or increased moderately in the low andhigh price projections respectively, according to the range of conceivable Myanmarshare mentioned by industry participants.

Thus, the low price trajectory reflects the combined impact of a lower valuedinternational hydrocarbon market along with a more plentiful outlook for Thai supplyat no increase in marginal cost, hence less involvement of costlier Myanmar bordervalues, while the high trajectory reflects the reverse. We believe that the range socreated accounts for the two key uncertainties going forward: (i) the future value ofworld oil, and (ii) the degree of future Thai exposure to (costlier) imported naturalgas.

On the whole, the low price is about 12% below, and the high price about 16% abovethe base price (USD 2.27/mmbtu base, versus USD 2.00 low and USD 2.64 high).

The range appears moderately skewed on the high side. One reason for this lays in thecrude oil price projections. For example, in 2011, low case crude oil is 40% cheaperthan in the Base Case, while high case crude is 50% more expensive (minus 8 dollarsversus plus 10 dollars on a 20 dollar base). The second reason is the change ofMyanmar share between the high and low cases. This change differently impacts thecomposite tax and royalty deductions removed from the Base price. For example, thehigher the Myanmar share, the less the weight of taxes and royalties to be deductedfrom the composite pre-tax gas price, leaving the net economic price higher than itwould have been had the Myanmar share not been increased. Put otherwise, moreexposure to international border prices reduces the weight of domestic transfers tobe removed from the composite commercial value in getting to economic value. Thereverse applies too.

The valuation methodology described above was back-casted to 2002 excludingadjustments from commercial to economic value, and the result indicated an error of+2.5% for the back-casted value relative to the average actual paid-up value for theyear. Considering all the components in this calculation and possible differences inspecific months included as “2002” between sources, this error is insignificant.

In the final analysis, these gas price projections partly determine the value of NT2relative to that of using CCGT capacity in its place. One industry participant believesthat Thai natural gas contracts are priced about the lowest of contracts anywhere,for the kind of term and geological structures at play. When the base case levelizedeconomic gas value is combined with the other costs of the CCGT option, the result

44 These series are no longer official Bank series, as the Bank does not prepare them in the formalmanner it did when they were published.


is USD 0.028/kWh at 74% plant factor. This value sits well within the (rather low)range of CCGT economic supply prices assessed for other CCGT projects.

The year to year projected economic natural gas prices used in the cost risk analysisare as follows (USD of 2003 per mmbtu):

Economic values of Natural Gas - Thailand

Year Base High Low2003 2.55 2.81 2.322004 2.44 2.81 2.212005 2.40 2.79 2.162006 2.36 2.76 2.132007 2.32 2.74 2.092008 2.31 2.72 2.072009 2.30 2.69 2.052010 2.29 2.67 2.032011 2.28 2.64 2.002012 2.27 2.63 1.992013 2.26 2.62 1.972014 2.24 2.61 1.952015 2.23 2.60 1.93

ex-2015 levelized:2.27 2.64 2.00

Detailed Plant Data (Existing System) 7 9

A4 Detailed Plant Data (Existing System)


Table A4-1. Existing Installed Generating Capacity (as of Sep-03)

Table A4-2. Existing Hydro Power Plant Data

Table A4-3. Existing and Committed Small Power Producers (as of Sep-03)

Table A4-4. Schedule of Planned Power Plant Retirements


Table A4-1. Existing Installed Generating Capacity (as of Sep-03)

Plant Type Fuel Installed Capacity Total CapacityType (MW) (MW)

A. Hydroelectric Plant -Bhumibol - (6x82.2)+115+171 779.2Sirikit - 4x125 500.0Ubolratana - 3x8.4 25.2Sirindhorn - 3x12 36.0Chulabhorn - 2x20 40.0Kaeng Krachan - 1x17.5 17.5Nam Pung - 2x3 6.0Srinagarind - (3x120)+(2x180) 720.0Bang Lang - 3x24 72.0Tha Thung Na - 2x19 38.0Vajiralongkorn - 3x100 300.0Pak Mun - 4x34 136.0Huai Kum - 1x1.06 1.1Ban Santi - 1x1.275 1.3Mae Ngat - 2x4.5 9.0Rajjaprabha - 3x80 240.0Miscellaneous - 0.429 0.4

Total 2,921.7B. Thermal Power Plant

South Bangkok Oil/Gas (2x200)+(3x310) 1,330.0Mae Moh Lignite (3x75)+(4x150)+(6x300) 2,625.0Bang Pakong Oil/Gas (2x550)+(2x600) 2,300.0

Total 6,255.0C. Combined Cycle Power Plant

Bang Pakong Block 1-2 Gas 2x[(4x60.7)+(137.5)] 760.6Block 3-4 Gas 2x[(2x104)+(1x99)] 614.0

Nam Phong Block 1-2 Gas 2x[(2x121)+(1x113)] 710.0South Bangkok Block 1 Gas (2x110)+(1x115) 335.0

Block 2 Gas (2x202)+(1x220) 624.0Wang Noi Block 1-2 Gas 2x[(2x223)+(1x205)] 1,302.0

Block 3 Gas (2x236)+(1x257) 729.0Total 5,074.6

D. Gas Turbine Power PlantLan Krabu Gas (4x14)+(2x16)+(4x20) 168.0Nong Chok 1-2 Diesel 3x122 366.0Surat Thani Gas 2x122 244.0

Total 778.0E. Diesel

Mae Hong Son Diesel 1x6 6.0Total 6.0

F. Renewable Energy SourceTotal 0.534 0.5

G. Purchased PowerKhanom Thermal Oil/Gas 2x75 150.0Khanom CC Gas (4x112)+(1x226) 674.0Rayong CC Block 1-4 Gas 4x[(2x103)+(1x102)] 1,232.0Ratchaburi Thermal Gas 2x720 1,440.0Ratchaburi CC Block 1-3 Gas 3x[(2x230)+(1x265)] 2,175.0Tri Energy Gas (2x224)+(1x252) 700.0Independent Power Gas (2x230)+(1x240) 700.0Bo Win Power Gas (2x356.5) 713.0Eastern Power&Electric Gas 350 350.0SPP - 1837.2 1,837.2Theun Hinboun Hydro - 2x115 214.0Houay Ho Hydro - 2x75 126.0EGAT-TNB Tie Line - 300 300.0

Total 10,611.2Grand Total 25,647.0

Note: FY2003 installed capacity reported in the Study is based on mid-year estimates, and therefore varies slightly from the actual end-year data reported above; differences generally relate to SPP scheduling.


Table A4-2. Existing Hydro Power Plant Data

Power Plant Est. Life Commission

(years) Date Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Total

I Bang Lang #1-3 50 Jul-81 MW 57.0 60.4 66.0 66.8 63.7 60.3 60.7 60.6 61.3 60.5 58.0 57.0 MWh 8,930 8,640 8,930 15,490 12,260 12,240 8,640 8,930 8,640 8,930 8,640 8,930 119,200 monthly share 0.075 0.072 0.075 0.130 0.103 0.103 0.072 0.075 0.072 0.075 0.072 0.075

2 Rajjaprabha #1-3 50 May-87 MW 196.9 198.1 196.2 190.2 182.1 173.2 179.6 170.9 163.3 165.9 178.3 190.9 MWh 29,800 28,800 29,800 29,800 26,900 29,800 28,800 29,800 28,800 29,800 29,800 28,800 350,700 monthly share 0.085 0.082 0.085 0.085 0.077 0.085 0.082 0.085 0.082 0.085 0.085 0.082

3 Bhumibol #1-8 50 May-64 MW 557.1 508.4 512.6 492.0 487.3 418.7 470.9 561.6 553.3 510.3 562.5 559.6 MWh 62,540 55,500 59,540 95,440 123,930 140,060 181,320 70,400 67,480 72,150 69,930 63,630 1,061,920 monthly share 0.059 0.052 0.056 0.090 0.117 0.132 0.171 0.066 0.064 0.068 0.066 0.060

4 SirJkit #1-4 50 Mar-74 MW 436.4 394.1 400.6 383.6 361.0 314.5 340.5 339.2 351.5 346.7 389.3 424.6 MWh 37,200 36,000 37,200 68,200 93,600 117,600 88,600 37,000 35,900 45,000 37,200 36,000 669,500 monthly share 0.056 0.054 0.056 0.102 0.140 0.176 0.132 0.055 0.054 0.067 0.056 0.054

5 Ubolratana #1-3 50 Mar-66 MW 20.4 21.2 21.0 20.7 19.8 18.3 17.0 16.9 16.7 16.6 16.2 18.5 MWh 4,290 1,130 10 860 3,180 4,410 3,860 970 10 1,610 2,960 3,130 26,420 monthly share 0.162 0.043 0.000 0.033 0.120 0.167 0.146 0.037 0.000 0.061 0.112 0.118

6 Chulabhorn #1-2 50 Oct-72 MW 40.0 40.0 40.0 39.9 40.0 40.0 40.0 40.0 39.6 39.9 40.0 40.0 MWh 4,980 4,820 4,980 4,980 4,500 4,980 4,820 4,980 4,820 4,980 4,980 4,820 58,640 monthly share 0.085 0.082 0.085 0.085 0.077 0.085 0.082 0.085 0.082 0.085 0.085 0.082

7 Sirindhorn #1-3 50 Nov-72 MW 36.0 36.0 36.0 35.6 34.7 33.6 32.7 32.1 32.2 32.4 33.4 35.6 MWh 4,460 4,320 4,460 4,460 4,030 4,460 4,320 4,460 4,320 4,460 4,460 4,300 52,510 monthly share 0.085 0.082 0.085 0.085 0.077 0.085 0.082 0.085 0.082 0.085 0.085 0.082

8 Kang Krachan #1 60 Aug-74 MW 13.9 13.9 14.7 14.5 14.3 13.6 13.2 13.0 12.6 12.0 11.0 11.3 MWh 2,600 4,890 2,600 3,000 3,750 2,650 2,520 3,050 8,640 8,260 8,340 6,330 56,630 monthly share 0.046 0.086 0.046 0.053 0.066 0.047 0.044 0.054 0.153 0.146 0.147 0.112

9 Nam Pung #1-3 50 Oct-65 MW 5.8 5.8 5.8 5.7 5.7 5.6 5.6 5.5 5.5 5.6 5.6 5.7 MWh 1,190 1,150 740 740 670 740 720 740 720 740 1,190 720 10,060 monthly share 0.118 0.114 0.074 0.074 0.067 0.074 0.072 0.074 0.072 0.074 0.118 0.072

10 Vachiralongkorn #1-3 50 Feb-85 MW 230.3 234.3 232.5 229.0 222.7 213.0 203.6 195.3 190.7 192.2 201.4 217.6 (Khao Laem) MWh 29,800 28,800 29,800 29,800 59,200 58,900 37,100 36,000 39,300 38,100 44,600 28,800 460,200

monthly share 0.065 0.063 0.065 0.065 0.129 0.128 0.081 0.078 0.085 0.083 0.097 0.063

11 Srinagarind #1-5 50 Feb-80 MW 675.0 682.2 683.4 681.3 677.9 359.1 358.2 351.3 347.2 346.0 346.5 352.4 MWh 74,000 72,200 74,600 75,100 66,800 98,500 97,600 101,400 71,600 74,500 74,400 72,700 953,400 monthly share 0.078 0.076 0.078 0.079 0.070 0.103 0.102 0.106 0.075 0.078 0.078 0.076

12 Tha Thung Na #1-2 50 Dec-82 MW 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 MWh 4,700 4,530 6,420 10,670 11,280 14,790 17,000 4,700 4,500 6,600 4,800 4,500 94,490 monthly share 0.050 0.048 0.068 0.113 0.119 0.157 0.180 0.050 0.048 0.070 0.051 0.048

13 Mae Ngat #1-2 50 Oct-85 MW 1.6 1.1 2.7 7.6 7.3 3.9 1.0 - - - - 2.7 MWh 1,100 540 1,810 5,530 5,530 2,490 540 - - - - 1,810 19,350 monthly share 0.057 0.028 0.094 0.286 0.286 0.129 0.028 - - - - 0.094

14 Pak Mun #1-4 50 Oct-94 MW 100.0 108.0 93.2 59.6 56.8 60.0 67.2 97.6 89.6 112.4 97.2 66.4 MWh 49,200 32,000 14,000 7,600 6,400 7,600 8,400 11,600 21,200 32,000 26,800 34,400 251,200 monthly share 0.196 0.127 0.056 0.030 0.025 0.030 0.033 0.046 0.084 0.127 0.107 0.137

15 Ban Yang+Huai Kum+ 50 Feb-74 MW 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 Ban Khun Klang MWh 1,299 1027 977 1064 891 829 718 779 928 1225 1188 1448 12,373

monthly share 0.105 0.083 0.079 0.086 0.072 0.067 0.058 0.063 0.075 0.099 0.096 0.117

16 Khirtharn #1-2 50 Oct-86 MW 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 MWh 2,020 1910 1920 1940 1780 1930 1850 1890 1880 1960 2000 1940 23,020 monthly share 0.088 0.083 0.083 0.084 0.077 0.084 0.080 0.082 0.082 0.085 0.087 0.084

Total Dependable Capacity 1/ MW 2,411 2,344 2,346 2,267 2,214 1,755 1,831 1,925 1,904 1,881 1,980 2,023 Total Generation 1/ MWh 316,089 284,347 275,867 352,734 422,921 500,049 484,958 314,809 296,858 328,355 319,288 300,318 4,219,613

monthly share 0.075 0.067 0.065 0.084 0.100 0.119 0.115 0.075 0.070 0.078 0.076 0.071

1/ Excluding Khiritharn, which is non-firm (under Irrigation Department control).

Monthly Dependable Hydro Capacity (MW) and Energy (MWh)


Table A4-3. Existing and Committed Small Power Producers (as of Sep-03)

Power Plant Location

Type of Fuel

Date of Purchase

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

1 Glow SPP Public Co.,Ltd (1) Rayong Gas 1 Apr. 96 902 Glow SPP Public Co.,Ltd (2) Rayong Gas 1 Oct. 96 903 TPT Utility Co.,Ltd Rayong Coal 1 Feb. 97 104 National Petrochemical Public Co.,Ltd Rayong Gas 1 Apr. 97 325 Glow SPP 1 Co.,Ltd (1) Rayong Gas 3 Feb. 98 556 Thai Oil Power Co.,Ltd. Chon Buri Gas 1 Apr. 98 417 Defence Energy Chiang Mai Heavy Oil 26 Jun. 98 98 Gulf Cogeneration Co.,Ltd Sara Buri Gas 3 Sep. 98 909 Amata-EGCO Power Co.,Ltd Chon Buri Gas 17 Sep. 98 90

10 Glow SPP 1 Co.,Ltd (2) Rayong Gas 18 Sep. 98 5511 Bangkok Cogeneration Co.,Ltd Rayong Gas 4 Feb. 99 9012 National Power Supply Co.,Ltd (1) Pra Chin Buri Coal 12 Mar. 99 9013 Glow SPP 2 Co.,Ltd (1) Rayong Gas 29 Mar. 99 6014 Saha Cogen (Chon Buri) Co.,Ltd Chon Buri Gas 19 Apr. 99 9015 Thai Power Supply Co.,Ltd (1) Cha Choeng Sao Rice Husk 21 Apr. 99 2516 Glow SPP 2 Co.,Ltd (2) Rayong Gas 26 Apr. 99 6017 Thai Power Supply Co.,Ltd (2) Cha Choeng Sao Rice Husk 7 May. 99 6.418 Rojana Power Co.,Ltd Ayutthaya Gas 26 May. 99 9019 National Power Supply Co.,Ltd (2) Pra Chin Buri Coal 12 Jul. 99 9020 Samutprakarn Cogeneration Co.,Lld Samut Prakarn Gas 23 Aug. 99 9021 Glow SPP 3 Co.,Ltd (1) Rayong Coal 1 Sep. 99 9022 Glow SPP 3 Co.,Ltd (2) Rayong Coal 20 Mar. 00 9023 Thai National Power Co.,Ltd Rayong Gas 4 Oct. 00 9024 Nong Khae Cogeneration Co.,Ltd Sara Buri Gas 12 Oct. 00 9025 Laem Chabang Power Co.,Ltd Chon Buri Gas 16 Jul. 01 6026 Bio-Mass Power Co.,Ltd Chainat Rice Husk 9 Sep. 01 527 Amata Power Co.,Ltd Chon Buri Gas 28 Sep. 01 9028 T.L.P. Cogeneration Co.,Ltd Rayong Gas 28 Jan. 03 6029 Roi Et Green Co.,Ltd Roiet Rice Husk 29 May. 03 8.830 Siam Power Co.,Ltd Rayong Gas 1 Jan 06 6031 Gulf Electric Public Co.,Ltd (Yala) Yala Wood Chip 1 Jun 04 20.232 Country Electric Co.,Ltd Lopburi Rice Husk - 1533 Mitr Phol Sugar Corp.,Ltd Suphan Buri Bagasse/Wood - 2534 Gulf Electric Public Co.,Ltd (Trang) Trang Wd Chp Plm Shll - 20.235 A.A. Pulp Mill (2) Co.,Ltd Pra Chin Buri Black Liquor - 2536 Advance Agro Public Co.,Ltd Chon Buri Rice Hsk Wd Chp - 5037 Korach Industry Co.,Ltd Nakhon Ratchasima Bagasse - 838 United Farmer& Industry Co.,Ltd Chaiyaphum Bagasse/wood - 2939 A.T. Bio Power Co.,Ltd Phichit Rice Husk - 2040 Mitr Kalasin Sugar Co.,Ltd Kalasin Bagasse - 841 Thai Power Supply Co.,Ltd (3) Cha Choeng Sao Rice Hsk Wd Chp - 2

Total -Gas 90 212 543 1,023 1,023 1,353 1,353 1,413 1,413 1,473 1,473

-Coal 0 10 10 280 370 370 370 370 370 370 370

-Heavy Oil 0 0 9 9 9 9 9 9 9 9 9

0 0 0 31 31 36 36 45 45 45 268

Grand Total 90 222 562 1,343 1,433 1,768 1,768 1,837 1,837 1,897 2,120

Note: The Study, based on mid-year estimates, assumes somewhat different SPP additions than the most recent assumptions reported above: 128.9 MW in FY2003, 60 MW in FY2004, 80 MW in FY2005, and none thereafter.

-Renewable energy

Small Producers Project


Table A4-4. Schedule of Planned Plant Retirements

Power Plant Rating Year(s) of Year of Planned Life(MW) Commissioning Retirement (Years)

Thermal PlantSouth Bangkok #1 200 1970 2006 36

#2 200 1971 2007 36#3 310 1974 2009 35 1/#4 310 1975 2010 35 1/#5 310 1977 2012 35 1/

Mae Moh #4-5 2x150 1984 2014 30 1/#6-7 2x150 1985 2015 30 1/#8 300 1989 2018 30#9 300 1990 2019 30#10-11 2x300 1991 2021 30#12 300 1995 2024 30#13 300 1995 2025 30

Khanom PPB #1 75 1981 2007 26 2/#2 75 1989 2007 18 2/

Bang Pakong #1 550 1983 2013 30 1/#2 550 1984 2014 30 1/#3-4 2x600 1992 2021 30

Ratchaburi TH #1-2 2x720 2000 2025 25Krabi #1 300 2003 2033 30

Combined Cycle PlantBang Pakong Block #1 380 1980-82 2008 26

#2 380 1981-83 2009 26#3 307 1990-92 2015 25#4 307 1990-92 2016 25

Rayong Block #1-2 308 1990-92 2011 20 1/#3 308 1991-92 2012 20 1/#4 308 1992-93 2013 20 1/

Nam Pong Block #1 355 1990-92 2017 25#2 355 1993-94 2019 25

South Bangkok #1 335 1993-94 2014 25#2 623 1996-97 2017 25

Wang Noi #1 651 1996-97 2023 25#2 651 1996-97 2023 25#3 729 1997-98 2023 25

Ratchaburi CC #1-2 2x725 2002 2022 25#3 725 2002 2023 25

Gas Turbine PlantLan Krabu 2x16+2x14 1969-70 Depending on gas availabilityLan Krabu 4x20 1981 Depending on gas availabilityNong Chok 3x122 1995 2016 21Surat 2x122 2001 2016 15

1/ Candidates for reconditioning. 2/ Retirement advanced due to planned availability of lower cost resources in South.

How PROSCREEN Works 8 5

A5 How PROSCREEN Works

PROSCREEN selects the least-cost plan by identifying the expansion scenario withthe lowest present value over a user-specified period (the “objective function”). Toachieve this objective requires a user manual over a foot thick and model inputspecification of several hundred pages. While it is beyond the scope of the currentstudy to explain these details, the following paragraphs attempt to describe themethodology in layman’s terms.

PROSCREEN divides the “Study Period” into two parts:

the “Planning Period”, defined for the current study as FY2003-14, inwhich decisions regarding system operation and expansion are analyzedannually and sub-annually (i.e., for user-defined seasons). The duration ofthe Planning Period has been selected based on preliminary model runsindicating (i) that NT2 is a least-cost addition to the Base Case expansionplan as of October 2009 (FY2010), and (ii) that NT2 would be fullyabsorbed into the regional power system by that date under the Lowdemand forecast (see Chapter 2).

The “End Effects Period” in which sophisticated programming techniquesanalyze differences between alternatives (e.g., due to different lives andoperating characteristics) beyond the Planning Period horizon. Withoutend effects analysis, results would be biased against commissioning capital-intensive units near the end of the planning period.

The objective function for our analysis is based on the Study Period, which representsthe sum of both the Planning Period and End-Effects Period results.

Production Costing and System Dispatch

The production costing procedure used by PROSCREEN has two stages. In the firststage, operation of hydro generation, transactions (i.e., IPP purchases), and economicoperation of pumped storage is simulated. The result of this first stage is the seasonalthermal load duration curve. In the second stage, the expected operation of thethermal units within the year is simulated based on a probabilistic technique. Theresults are production costs and the associated level of reliability.

Dispatch of non-thermal resources. Resources are dispatched to meet systemload (modeled as typical weekly load shapes) without regard to cost in thefollowing order:

Transactions (e.g. contract purchases) are dispatched eitheraccording to an hourly profile or designated shape (e.g., peak-


shaving, valley-filling, etc.). Although many SPPs are thermal, they areall treated as must-run transactions.

Hydro generation is dispatched simply as monthly generation whichcontributes to meeting system load, peak-shaving where possible.Available monthly hydro generation is exogenously determined byEGAT. (While PROSCREEN permits more complex modeling ofhydro resources, these capabilities are not used by EGAT, sincehydro makes up a relatively small portion of the total system.)

Pumped Storage is dispatched when (and if) off-peak pumping foron-peak generation is economically justified.

Dispatch of thermal resources. Each in-service thermal unit is dispatchedaccording to standard probabilistic production costing procedures. Any“must-run” units are dispatched first, followed by enough other units ineconomic order45 to meet system load and resource requirements.

Evaluating Expansion Alternatives

PROSCREEN uses a mathematical approach called “dynamic programming” todetermine the combination of sequential, interrelated decisions which produce thedesired least-cost result. Specifically, for each year of the Planning Period, allcombinations of expansion alternatives are evaluated; each combination (known as a“state”) that meets user-defined goals (i.e., to provide required capacity and targetreserve margin) is defined as a feasible state. A feasible state includes:

Capital costs expressed as the economic carrying cost associated with eachcandidate in the state; and

Production costs derived from a complete probabilistic dispatch of the totalsystem including both existing and candidate units.

The present value of capital and production costs determines the accumulated cost ofeach feasible state.

For the next year, each of these “origin states” becomes a starting point forgenerating additional states which are feasible in the current year. Again, all possiblecombinations of the initial state and alternative resource additions are considered.Each feasible state for the year is defined by the required additions, the origin state,and the cumulative objective function value to date. This process continues throughthe Planning Period, with the objective function value for each year equal to theobjective function value for the “origin state” plus the present value of productionand capital cost from the current state.

After the last year of the Planning Period is analyzed, end-effects are considered toaccount for differences in operating characteristics, fuel costs, O&M costs, and the

45 As modified to reflect fuel contract and availability constraints.


lives of the alternatives resources beyond the Planning Period. The End Effects Periodtotal costs are equal to the present value of capital costs plus production costs.Capital costs equal the economic carrying costs associated with each year of thespecified End Effects Period. (Since EGAT adopts the model option of an infinite EndEffects Period, this calculation is analogous to a perpetuity.) Production costs equalthe total system cost from a single-period simulation representing this same end-effects period; the dispatch is based on a constant load (the load from the last year ofthe Planning Period) and time-weighted inputs for fuel and operating costs.

Economic Base Case with NT2 – Detail 8 9

A6 Economic Base Case with NT2 – Detail


Table A6-1. Demand and Supply Balance

Table A6-2. System Costs by Plant Group

Table A6-3. Fuel Use by Type

Table A6-4. Fuel Type by Individual Plant


Table A6-1. Demand and Supply Balance – Economic Base Case with NT2

2003 2004 2005 2006 2007 2008LOADS - MW SYSTEM PEAK LOAD 17,350 18,520 19,749 21,057 22,440 23,896

RESOURCES - MW HYDRO 1,831 1,831 1,831 1,831 1,831 1,831

PUMPED STORAGE - 490 490 490 490 490

TRANSACTIONS 2,155 2,263 2,323 2,343 2,343 2,343 TOTAL SPP 1,837 1,945 2,005 2,025 2,025 2,025 THEUN HINBOUN HYDRO 192 192 192 192 192 192 HOUAYHO HYDRO 126 126 126 126 126 126 NAM THEUN 2 - - - - - -

THERMAL (by fuel type) 19,844 20,131 20,131 19,940 21,475 23,059 GAS - Combined Cycle 11,691 11,691 11,691 11,691 12,071 13,798 GAS - Thermal 5,048 5,048 5,048 4,856 4,665 4,521 HFO (Heavy Fuel Oil) - 287 287 287 287 287 DIESEL 597 597 597 597 597 597 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported - - - - 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

INSTALLED CAPACITY 23,830 24,715 24,775 24,604 25,996 27,723 CAPACITY RESERVE 6,480 6,195 5,026 3,547 3,556 3,827

ENERGY - GWh ENERGY REQUIRED 111,310 118,506 126,516 135,039 143,847 153,214

GENERATION HYDRO 4,054 4,054 4,054 4,054 4,054 4,054 PUMPED GENERATION - - 2 248 266 237 PUMPING ENERGY - - (2) (354) (380) (338) NET TRANSACTIONS 15,820 16,430 16,856 16,992 16,942 16,892 THERMAL 91,436 98,021 105,607 114,098 122,962 132,364 EMERGENCY ENERGY - - - - 2 4 SYSTEM LOAD FACTOR 0.73 0.73 0.73 0.73 0.73 0.73


2009 2010 2011 2012 2013 2014LOADS - MW SYSTEM PEAK LOAD 25,599 27,263 28,889 30,598 32,442 34,358

RESOURCES - MW HYDRO 1,831 1,831 1,831 1,831 1,831 1,831

PUMPED STORAGE 490 490 490 490 490 490

TRANSACTIONS 2,343 3,338 3,338 3,338 3,338 3,338 TOTAL SPP 2,025 2,025 2,025 2,025 2,025 2,025 THEUN HINBOUN HYDRO 192 192 192 192 192 192 HOUAYHO HYDRO 126 126 126 126 126 126 NAM THEUN 2 - 995 995 995 995 995

THERMAL (by fuel type) 24,786 25,716 27,576 29,676 31,776 33,876 GAS - Combined Cycle 15,526 16,226 17,626 19,726 21,826 23,926 GAS - Thermal 4,521 4,521 4,521 4,521 4,521 4,521 HFO (Heavy Fuel Oil) 287 287 287 287 287 287 DIESEL 597 827 1,287 1,287 1,287 1,287 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported 1,347 1,347 1,347 1,347 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

INSTALLED CAPACITY 29,451 31,376 33,236 35,336 37,436 39,536 CAPACITY RESERVE 3,852 4,113 4,347 4,738 4,994 5,178

ENERGY - GWh ENERGY REQUIRED 164,204 174,688 185,141 196,153 208,007 220,372

GENERATION HYDRO 4,054 4,054 4,054 4,054 4,054 4,054 PUMPED GENERATION 296 228 224 217 265 277 PUMPING ENERGY (422) (325) (321) (309) (379) (395) NET TRANSACTIONS 16,842 22,171 22,109 22,071 22,021 21,971 THERMAL 143,431 148,559 159,073 170,120 182,045 194,464 EMERGENCY ENERGY 3 1 1 - - - SYSTEM LOAD FACTOR 0.73 0.73 0.73 0.73 0.73 0.73


Table A6-2. System Costs by Plant Group – Economic Base Case with NT2

(US$ 000) 2003 2004 2005 2006 2007 2008

OPERATING COSTSTHERMAL COST - TOTAL TOTAL FUEL COST 1/ 1,694,520 1,763,763 1,902,758 2,065,773 2,157,753 2,276,429 VAR. O&M COST 55,007 58,055 62,169 67,993 78,685 84,094 FIXED 0&M COST 368,831 381,972 381,972 376,866 400,463 416,730 THERMAL COST ($/MWh) 23 22 22 22 21 21

HYDRO COST - TOTAL TOTAL VAR COST 6,933 6,933 6,941 8,089 8,174 8,038 TOTAL FIXED COST 49,846 57,472 57,472 57,472 57,472 57,472

TRANSACTION PURCHASES 513,864 535,738 551,482 557,672 557,672 557,672

EMERGENCY ENERGY COST - - - 559 3,291 5,871

TOTAL SYSTEM COST 2,689,000 2,803,933 2,962,794 3,134,424 3,263,510 3,406,306 SYSTEM COST ($/MWh) 24 24 23 23 23 22 AVG. MARGINAL COST ($/MWh) 23 22 24 49 63 68

FIXED COSTSTOTAL CAPITAL COST 2/ - - - - - 42,454

TOTAL COSTTOTAL UTILITY COST 2,689,000 2,803,933 2,962,794 3,134,424 3,263,510 3,448,760 PRESENT VALUE OF COST 2,689,000 2,549,030 2,448,590 2,354,939 2,229,021 2,141,409 ACCUM. PRESENT VALUE 2,689,000 5,238,030 7,686,620 10,041,560 12,270,580 14,411,990

1/ See attached table of fuel usage by type. 2/ Capital costs for each addition discounted to the year of commissioning.


(US$ 000) 2009 2010 2011 2012 2013 2014

OPERATING COSTSTHERMAL COST - TOTAL TOTAL FUEL COST 1/ 2,409,845 2,474,061 2,637,113 2,777,755 2,944,153 3,109,684 VAR. O&M COST 90,940 92,035 97,997 104,163 111,051 118,450 FIXED 0&M COST 455,623 474,653 502,985 538,265 573,545 608,825 THERMAL COST ($/MWh) 21 20 20 20 20 20

HYDRO COST - TOTAL TOTAL VAR COST 8,311 7,994 7,979 7,942 8,170 8,222 TOTAL FIXED COST 57,472 57,472 57,472 57,472 57,472 57,472

TRANSACTION PURCHASES 557,672 561,597 561,597 561,637 561,597 561,597

EMERGENCY ENERGY COST 4,264 856 741 368 306 315

TOTAL SYSTEM COST 3,584,126 3,668,670 3,865,885 4,047,603 4,256,296 4,464,567 SYSTEM COST ($/MWh) 22 21 21 21 20 20 AVG. MARGINAL COST ($/MWh) 57 43 41 36 33 32

FIXED COSTSTOTAL CAPITAL COST 2/, 3/ 127,363 290,452 396,580 523,943 654,613 787,145

TOTAL COSTTOTAL UTILITY COST 3,711,489 3,959,122 4,262,465 4,571,546 4,910,909 5,251,712 PRESENT VALUE OF COST 2,095,039 2,031,655 1,988,471 1,938,782 1,893,368 1,840,693 ACCUM. PRESENT VALUE 16,507,030 18,538,680 20,527,150 22,465,940 24,359,300 26,200,000

1/ See attached table of fuel usage by type. 2/ Capital costs for each addition discounted to the year of commissioning. 3/ Capital cost data exclude NT2 associated transmission; post-PROSCREEN manual adjustment by author.


Table A6-3. Fuel Use by Type – Economic Base Case with NT2

2003 2004 2005 2006 2007 2008

GENERATION (GWh) GAS - Combined Cycle 70,507 74,726 76,619 77,642 79,500 90,080 GAS - Thermal 5,146 6,317 11,357 18,280 17,176 14,203 HFO (Heavy Fuel Oil) - 1,141 1,835 1,963 2,012 1,835 DIESEL 36 41 48 444 561 637 LIGNITE 15,747 15,796 15,747 15,747 15,747 15,796 COAL - Imported - - - - 7,905 9,738 TNB (tie line) - - - 21 61 75

THERMAL CAPACITY BY FUEL 1/ GAS - Combined Cycle 11,691 11,691 11,691 11,691 12,071 13,798 GAS - Thermal 5,048 5,048 5,048 4,856 4,665 4,521 HFO (Heavy Fuel Oil) - 287 287 287 287 287 DIESEL 597 597 597 597 597 597 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported - - - - 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

FUEL BURNED (mmBtu) GAS - Combined Cycle 534,788 566,192 582,540 592,564 605,896 677,615 GAS - Thermal 50,732 61,487 108,820 174,300 163,722 135,567 HFO (Heavy Fuel Oil) - 11,659 17,543 18,631 19,043 17,551 DIESEL 331 383 453 4,132 5,377 6,058 LIGNITE 164,813 165,323 164,813 164,813 164,813 165,323 COAL - Imported - - - - 77,767 95,804 TNB (tie line) - - 3 248 719 887

TOTAL FUEL COST (US$ 000) GAS - Combined Cycle 1,363,708 1,381,507 1,398,095 1,398,451 1,405,679 1,565,291 GAS - Thermal 129,367 150,029 261,168 411,348 379,835 313,159 HFO (Heavy Fuel Oil) - 31,946 45,260 45,087 43,229 40,544 DIESEL 2,020 1,891 2,108 18,056 22,047 25,261 LIGNITE 199,424 198,388 196,128 192,831 189,535 188,469 COAL - Imported - - - - 117,428 143,706

AVG. FUEL USE (Btu/kWh) GAS - Combined Cycle 7.58 7.58 7.60 7.63 7.62 7.52 GAS - Thermal 9.86 9.73 9.58 9.54 9.53 9.54 HFO (Heavy Fuel Oil) - 10.22 9.56 9.49 9.46 9.56 DIESEL 9.19 9.34 9.44 9.31 9.58 9.51 LIGNITE 10.47 10.47 10.47 10.47 10.47 10.47 COAL - Imported - - - - 9.84 9.84 TNB (tie line) - - - 11.81 11.79 11.83

AVG. FUEL COST (US mills/kWh) GAS - Combined Cycle 19.34 18.49 18.25 18.01 17.68 17.38 GAS - Thermal 25.14 23.75 23.00 22.50 22.11 22.05 HFO (Heavy Fuel Oil) - 28.00 24.66 22.97 21.49 22.09 DIESEL 56.11 46.12 43.92 40.67 39.30 39.66 LIGNITE 12.66 12.56 12.45 12.25 12.04 11.93 COAL - Imported - - - - 14.85 14.76

CAPACITY FACTOR BY TYPE GAS - Combined Cycle 0.69 0.73 0.75 0.76 0.75 0.75 GAS - Thermal 0.12 0.14 0.26 0.43 0.42 0.36 HFO (Heavy Fuel Oil) - 0.45 0.73 0.78 0.80 0.73 DIESEL 0.01 0.01 0.01 0.08 0.11 0.12 LIGNITE 0.81 0.82 0.81 0.81 0.81 0.82 COAL - Imported - - - - 0.67 0.83

1/ Approximate capacity since some units use more than one fuel; see attached table of fuel use by plant.


2009 2010 2011 2012 2013 2014

GENERATION (GWh) GAS - Combined Cycle 104,654 110,836 120,590 133,611 145,996 157,946 GAS - Thermal 11,043 10,195 10,873 9,087 9,045 9,668 HFO (Heavy Fuel Oil) 1,736 1,686 1,609 1,503 1,231 1,116 DIESEL 488 369 530 374 309 272 LIGNITE 15,747 15,747 15,747 15,796 15,747 15,747 COAL - Imported 9,708 9,708 9,708 9,738 9,708 9,708 TNB (tie line) 54 18 15 10 8 8

THERMAL CAPACITY BY FUEL 1/ GAS - Combined Cycle 15,526 16,226 17,626 19,726 21,826 23,926 GAS - Thermal 4,521 4,521 4,521 4,521 4,521 4,521 HFO (Heavy Fuel Oil) 287 287 287 287 287 287 DIESEL 597 827 1,287 1,287 1,287 1,287 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported 1,347 1,347 1,347 1,347 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

FUEL BURNED (mmBtu) GAS - Combined Cycle 774,760 816,955 884,015 972,120 1,055,468 1,135,507 GAS - Thermal 105,684 98,919 106,414 89,521 90,273 97,498 HFO (Heavy Fuel Oil) 16,707 16,283 15,629 14,736 12,418 11,444 DIESEL 4,638 3,407 4,951 3,492 2,883 2,538 LIGNITE 164,813 164,813 164,813 165,323 164,813 164,813 COAL - Imported 95,509 95,509 95,509 95,804 95,509 95,509 TNB (tie line) 635 217 183 118 90 91

TOTAL FUEL COST (US$ 000) GAS - Combined Cycle 1,781,947 1,870,828 2,015,553 2,206,712 2,385,358 2,543,536 GAS - Thermal 243,073 226,524 242,623 203,213 204,017 218,395 HFO (Heavy Fuel Oil) 39,261 38,753 37,666 35,955 30,672 28,610 DIESEL 19,621 14,617 21,489 15,366 12,828 11,422 LIGNITE 184,591 182,943 181,294 178,549 174,702 173,054 COAL - Imported 141,353 140,398 138,487 137,958 136,577 134,667

AVG. FUEL USE (Btu/kWh) GAS - Combined Cycle 7.40 7.37 7.33 7.28 7.23 7.19 GAS - Thermal 9.57 9.70 9.79 9.85 9.98 10.08 HFO (Heavy Fuel Oil) 9.62 9.66 9.71 9.80 10.09 10.25 DIESEL 9.50 9.23 9.34 9.34 9.33 9.33 LIGNITE 10.47 10.47 10.47 10.47 10.47 10.47 COAL - Imported 9.84 9.84 9.84 9.84 9.84 9.84 TNB (tie line) 11.76 12.06 12.20 11.80 11.25 11.38

AVG. FUEL COST (US mills/kWh) GAS - Combined Cycle 17.03 16.88 16.71 16.52 16.34 16.10 GAS - Thermal 22.01 22.22 22.31 22.36 22.56 22.59 HFO (Heavy Fuel Oil) 22.62 22.99 23.41 23.92 24.92 25.64 DIESEL 40.21 39.61 40.55 41.09 41.51 41.99 LIGNITE 11.72 11.62 11.51 11.30 11.09 10.99 COAL - Imported 14.56 14.46 14.27 14.17 14.07 13.87

CAPACITY FACTOR BY TYPE GAS - Combined Cycle 0.77 0.78 0.78 0.77 0.76 0.75 GAS - Thermal 0.28 0.26 0.27 0.23 0.23 0.24 HFO (Heavy Fuel Oil) 0.69 0.67 0.64 0.60 0.49 0.44 DIESEL 0.09 0.05 0.05 0.03 0.03 0.02 LIGNITE 0.81 0.81 0.81 0.82 0.81 0.81 COAL - Imported 0.82 0.82 0.82 0.83 0.82 0.82

1/ Approximate capacity since some units use more than one fuel; see attached table of fuel use by plant.


Table A6-4. Fuel Type by Individual Plant – Economic Base Case with NT2

Code THERMAL Unit CAPACITY FUEL FUEL COMM'N RETIREM'TNo. UNIT No. MW CLASS YEAR YEAR

Existing Gas-fired C-C - with some Diesel support1 LKB 1 232 DGLKB GCC 1970 20502 NPO_CC 1 347.2 DGNP GCC 1992 20173 NPO_CC 2 347.2 DGNP GCC 1994 2019

Existing Gas-fired C-C Plant4 BPK_CC 1 372.7 GAS_MIX GCC 1983 20075 BPK_CC 2 372.7 GAS_MIX GCC 1983 20086 BPK_CC 3 300.9 GAS_MIX GCC 1992 20167 BPK_CC 4 300.9 GAS_MIX GCC 1992 20178 SB_CC 1 328.1 GAS_MIX GCC 1994 20199 SB_CC 2 610.3 GAS_MIX GCC 1998 202210 WN_CC 1 632.5 GAS_MIX GCC 1997 202311 WN_CC 2 632.5 GAS_MIX GCC 1998 202312 WN_CC 3 708.3 GAS_MIX GCC 1998 202316 RY_CC 1 301.8 GAS_MIX GCC 1992 201517 RY_CC 2 301.8 GAS_MIX GCC 1992 201518 RY_CC 3 301.8 GAS_MIX GCC 1992 201519 RY_CC 4 301.8 GAS_MIX GCC 1993 201520 KN_CC 1 165.1 GAS_MIX GCC 1995 201621 KN_CC 2 165.1 GAS_MIX GCC 1995 201622 KN_CC 3 165.1 GAS_MIX GCC 1995 201623 KN_CC 4 165.1 GAS_MIX GCC 1995 201624 RB_CC 1 725 GAS_MIX GCC 2002 202725 RB_CC 2 725 GAS_MIX GCC 2002 202726 RB_CC 3 725 GAS_MIX GCC 2003 202727 IPT 1 700 GAS_MIX GCC 2000 202528 EPEC 1 350 GAS_MIX GCC 2003 202229 TECO 1 700 GAS_MIX GCC 2000 202030 Bowin 1 713 GAS_MIX GCC 2003 2027

Existing Gas- and Oil-fired Thermal Plant31 SB_TH 1 191.2 GAS_TH GTH 1971 200532 SB_TH 2 191.2 GAS_TH GTH 1972 200633 SB_TH 3 296.4 GAS_TH GTH 1974 200934 SB_TH 4 296.4 GAS_TH GTH 1976 201035 SB_TH 5 296.4 GAS_TH GTH 1978 201236 NB_TH 1 71.9 HOIL_2S HFO 1961 200137 NB_TH 2 71.9 HOIL_2S HFO 1963 200138 NB_TH 3 83.8 HOIL_2S HFO 1969 200139 BPK_TH 1 524.2 GAS_TH GTH 1983 201340 BPK_TH 2 524.2 GAS_TH GTH 1984 201441 BPK_TH 3 571.9 GAS_TH GTH 1992 202142 BPK_TH 4 571.9 GAS_TH GTH 1993 202144 KA_TH1 1 287.4 HOIL_2S HFO 2004 203345 PPB_TH 1 71.9 GAS_TH GTH 1981 200746 PPB_TH 2 71.9 GAS_TH GTH 1989 200747 RB_TH 1 720 GAS_TH GTH 2000 202548 RB_TH 2 720 GAS_TH GTH 2001 2025

Existing Lignite-fired Thermal Plant49 MM_TH 1 69 LIGN_MM LIGN 1978 200250 MM_TH 2 69 LIGN_MM LIGN 1979 200251 MM_TH 3 69 LIGN_MM LIGN 1981 200252 MM_TH 4 138 LIGN_MM LIGN 1984 201453 MM_TH 5 138 LIGN_MM LIGN 1984 201454 MM_TH 6 138 LIGN_MM LIGN 1985 201555 MM_TH 7 138 LIGN_MM LIGN 1985 201556 MM_TH 8 276 LIGN_MM LIGN 1989 201857 MM_TH 9 276 LIGN_MM LIGN 1990 201958 MM_TH 10 276 LIGN_MM LIGN 1991 202159 MM_TH 11 276 LIGN_MM LIGN 1991 202160 MM_TH 12 276 LIGN_MM LIGN 1995 202461 MM_TH 13 276 LIGN_MM LIGN 1995 2025


Code THERMAL Unit CAPACITY FUEL FUEL COMM'N RETIREM'TNo. UNIT No. MW CLASS YEAR YEAR

Committed Gas-fired C-C Plant (IPPs)62 UPDC 1 700 GAS_MIX GCC 2008 203263 UPDC 2 700 GAS_MIX GCC 2009 203364 GULF 1 700 GAS_MIX GCC 2008 2032

Committed Coal-fired Plant (IPPs)66 BLCP 1 673.3 COAL_IND COAL 2007 203167 BLCP 2 673.3 COAL_IND COAL 2007 2031

Existing Diesel-fired GT Plant68 NC_GT 1 119.4 DIESEL DISE 1995 201569 NC_GT 2 119.4 DIESEL DISE 1995 201570 NC_GT 3 119.4 DIESEL DISE 1995 201571 NC_GT 4 119.4 DIESEL DISE 1995 200072 SRTGT 1 119.4 DIESEL DISE 2001 201673 SRTGT 2 119.4 DIESEL DISE 2001 2016

Existing tie with Malaysia74 TNB_300 1 300 TNB TNB 2002 205075 TNB OLD 1 80 TNB TNB 1994 2002

Committed Gas-fired C-C Plant114 KNCCD2 1 380.2 GAS_MIX GCC 2007 2031

ECONOMIC BASE CASE - Recommended Additions (including Reconditioning)229 CC700 229 700 GAS_NEW GCC 2014 2038230 CC700 230 700 GAS_NEW GCC 2014 2038231 CC700 231 700 GAS_NEW GCC 2014 2038232 BKT1 232 524.2 GAS_TH GTH 2014 2028233 CC700 233 700 GAS_NEW GCC 2013 2037234 CC700 234 700 GAS_NEW GCC 2013 2037235 CC700 235 700 GAS_NEW GCC 2013 2037236 SBT5 236 296.4 GAS_TH GTH 2013 2027237 CC700 237 700 GAS_NEW GCC 2012 2036238 CC700 238 700 GAS_NEW GCC 2012 2036239 CC700 239 700 GAS_NEW GCC 2012 2036240 GT230 240 230 DIESEL DISE 2011 2025241 GT230 241 230 DIESEL DISE 2011 2025242 CC700 242 700 GAS_NEW GCC 2011 2035243 CC700 243 700 GAS_NEW GCC 2011 2035244 SBT4 244 296.4 GAS_TH GTH 2011 2025245 GT230 245 230 DIESEL DISE 2010 2024246 CC700 246 700 GAS_NEW GCC 2010 2034247 SBT3 247 296.4 GAS_TH GTH 2010 2024248 CC700 248 700 GAS_NEW GCC 2009 2033249 CC700 249 700 GAS_NEW GCC 2009 2033250 CC700 250 700 GAS_NEW GCC 2008 2032

CANDIDATE ADDITIONS (including Reconditioning)121 O700 1 700 HOIL_2S HFO123 C700 1 700 COAL_IND COAL127 CC700 1 700 GAS_NEW GCC130 GT230 1 230 DIESEL DISE157 SBT3 3 296.4 GAS_TH GTH158 SBT4 4 296.4 GAS_TH GTH159 SBT5 5 296.4 GAS_TH GTH160 BKT1 1 524.2 GAS_TH GTH161 BKT2 2 524.2 GAS_TH GTH164 MM4 4 138 LIGN_MM LIGN171 RYC1 1 301.8 GAS_MIX GCC

Nam Theun 2 Hydro Power Project Regional Economic …siteresources.worldbank.org/INTLAOPRD/491761-1094074854903/... · Least-Cost Analysis Draft Final Report ... NT2 Nam Theun 2 hydro

Documents