67582 report to The World Bank Nam Theun 2 Hydro Power Project Regional Economic Least-Cost Analysis Final Report March 2005 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). Robert Vernstrom consulting economist Bangkok, Thailand 662 2520186 fax 662 2532176 vernstrom@stanfordalumni.org The author wishes to thank the Electricity Generating Authority of Thailand (EGAT), Dr. Kajornsak Hotrabhavananda, Deputy Governor for Policy and Planning, and Mr. Prutichai Chonglertvanichkul, Director – System Planning Division, for the extensive support of their experienced professional team. Special thanks are due to Ms. Petchara Rompruek (Head of Power Development Planning), and her staff (including Manop Tanglakmongkol, Nimit Sujiratanavimol, Thanawadee Deetae, and Yoothapong Tancharoen, among others), without whose support the Study would not have been possible. Countless hours were spent in discussing and refining assumptions used in the Study, and many additional hours were expended to complete the generation expansion planning scenarios discussed in this report. The demand forecasting sections of this report were prepared with the expert assistance of Dr. Tienchai Chongpeerapien, President of Business and Economic Research Associates (BERA), a Bangkok consultant with many years of experience working on load forecasting issues for the Thai power sector. Special thanks are due to Mr. Mark Segal, Mr. Darayes Mehta, and Mr. Robert Mertz, World Bank supervisors and advisors to the project, for their professional guidance and support. T ABLE OF C ONTENTS Executive Summary i 1 Introduction 9 1.1 Background 9 1.2 Study Objective 10 1.3 Organization of the Report 10 2 System Demand Assumptions 12 2.1 Overview of the Forecasting Methodology 12 2.2 Comparison of Forecast Results 19 2.3 Load Forecast Adopted for this Study 23 3 System Supply Assumptions 25 3.1 Installed and Planned System Capacity 25 3.2 Thermal Expansion Candidates 28 3.3 Fuel Price Projections 29 3.4 Thermal Candidate Plant Screening Analysis 31 3.5 NT2 – The Alternative Expansion Candidate 32 4 Methodology for the Study 35 4.1 The Least Cost Planning Methodology 35 4.1.1 The PROSCREEN II Model 35 4.1.2 How PROSCREEN is Applied in this Study 36 4.2 Cost-Risk Analysis Modeling Framework 37 5 Economic Evaluation 41 5.1 Economic Planning Assumptions 41 5.1.1 Basic Economic Assumptions 41 5.1.2 System Characteristics 42 5.1.3 NT2 Planning Assumptions for the Economic Analysis 43 5.2 Base Case Results 45 5.3 Cost-Risk Analysis 47 5.3.1 Sensitivity Analysis 49 5.3.2 Cost-Risk Analysis Results 52 6 Commercial Assessment 57 6.1 Commercial Planning Assumptions 57 6.1.1 Basic Commercial Assumptions 57 6.1.2 System Characteristics 57 6.1.3 The Cost of NT2 59 6.1.4 Private Sector Commercial View 59 6.2 Commercial Base Case Results 61 6.3 Cost-Risk Analysis 63 6.3.1 Sensitivity Analysis 63 6.3.2 Cost-Risk Analysis Results 67 7 Conclusion 69 A1 Terms of Reference 71 A2 Thailand Demand Forecast 77 A3 Fuel Price Assumptions 83 A4 Detailed Plant Data (Existing System) 93 A5 How PROSCREEN Works 99 A6 Economic Base Case with NT2 – Detail 103 T ABLES AND F IGURES Table S-1. Economic Cost-Risk Analysis Results v Table S-2.Comparison of Economic and Commercial Analyses vi Table S-3. Commercial Cost Risk Analysis Results vii Table 1. Current Forecast Methods by Company and Class 14 Table 2. National GDP Growth Assumptions 15 Table 3. Integrated National Electricity Conservation Program 18 Table 4. National Conservation Program – Alternative View 19 Table 5. Historical Energy Requirements Forecasts (GWh) 20 Table 6. Historical Peak Demand Forecasts (MW) 21 Table 7. Implied Income Elasticity of Energy Requirements Forecasts 22 Table 8. Historical Forecast Accuracy 1/ 22 Table 9. Recommended Load Forecast for this Study 24 Table 10. Installed and Purchased Capacity (as of March 2003) 26 Table 11. Committed Plant Additions (after March 2003) 27 Table 12. Schedule of Retirements (FY2003-14) 28 Table 13. Candidate Power Plants for the Study (2003 Prices) 29 Table 14. Base Case Fuel Price Forecasts 31 Table 15. Screening Analysis of EGAT Candidate Plants 33 Table 16. The Cost-Risk Framework 38 Table 17. Capital Costs of NT2 (constant US$2003, 10% discount rate) 44 Table 18. Base Case “with NT2� 45 Table 19. Base Case “without NT2� 46 Table 20. Sensitivity of Results to Lower Demand 50 Table 21. Sensitivity of Results to the Price of Natural Gas 51 Table 22. Sensitivity to Changes in NT2 Capital Cost 52 Table 23. Economic Cost Risk Analysis Results 53 Table 24. Economic Cost-Risk Sensitivity Test 55 Table 25. Commercial Base Case 62 Table 26. Sensitivity of Results to Lower Demand 65 Table 27. Sensitivity of Results to Lower Natural Gas Prices 66 Table 28. Commercial Cost-Risk Analysis 67 Table 29. Commercial Cost-Risk Sensitivity Test 68 Table A2-1. EGAT Total Generation Requirement Forecast 78 Table A2-2. EGAT Total Sales Forecast 79 Table A2-3. MEA Purchases and Sales Forecast by Customer Class 80 Table A2-4. PEA Purchases and Sales Forecast by Customer Class 81 Table A2-5. Comparison of The August 2002 and January 2004 Forecasts 82 Table A3-1. Economic Fuel Price Projections (constant US$2003) 84 Table A3-2. Commercial Fuel Price Projections (current US$) 85 Table A4-1. Existing Installed Generating Capacity (as of Sep-03) 94 Table A4-2. Existing Hydro Power Plant Data 95 Table A4-3. Existing and Committed Small Power Producers (as of Sep-03) 96 Table A4-4. Schedule of Planned Plant Retirements 97 Table A6-1. Demand and Supply Balance – Economic Base Case with NT2 104 Table A6-2. System Costs by Plant Group – Economic Base Case with NT2 106 Table A6-3. Fuel Use by Type – Economic Base Case with NT2 108 Table A6-4. Fuel Type by Individual Plant – Economic Base Case with NT2 110 L IST OF A CRONYMS AAGR average annual growth rate BOI Board of Investment BTU British Thermal Unit (standard measure of fuel heat content) CCGT combined cycle gas turbine CIDA Canadian International Development Agency COD commercial operation date DAEDE Department of Alternative Energy Development and Efficiency (formerly DEDP) DEDP Department of Economic Development and Promotion (now DAEDE) E&P exploration and production EDP exploration, development, production EGAT Electricity Generating Authority of Thailand EIA Energy Information Administration (U.S. Department of Energy) EPPO Energy Policy and Planning Office (formerly NEPO) ESI electricity supply industry GDP gross domestic product GHG greenhouse gas GMS Greater Mekong Sub-region GOL Government of the Lao People’s Democratic Republic GOT Government of the Kingdom of Thailand GPA gas purchase agreement GRP gross regional product GT gas turbine GWh gigawatt hour (one million kWh) HFO heavy fuel oil IBRD International Bank for Reconstruction and Development (official name for the World Bank) IMF International Monetary Fund IPP independent power producer kWh kilowatt hour LER low economic recovery (Sep-98 forecast scenario) LFCR levelized fixed charge rate LOLP loss of load probability MEA Metropolitan Electricity Authority MER medium economic recovery (Sep-98 forecast scenario) MM million MOU memorandum of understanding MUV United Nations index of the unit value of manufactured exports MW 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 loan NPV net present value NSO National Statistics Office NT2 Nam Theun 2 hydro power project NTPC Nam Theun Power Company PCF Prototype Carbon Fund administered by the World Bank PDP power development program of EGAT PE primary energy (required purchases from NT2, 6 a.m. to 10 p.m.) PEA Provincial Electricity Authority PPA power purchase agreement PTT Petroleum Authority of Thailand PV present value RER rapid economic recovery (Sep-98 forecast scenario) RM reserve margin R/P reserves to production ratio SCF 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 producer TDRI Thailand Development Research Institute THB Thai Baht; in this study, US$1.00 = 40 THB TLFS Thailand Load Forecast Sub-committee WACC weighted average cost of capital WB World Bank WCD World Commission on Dams Executive Summary i E XECUTIVE S UMMARY S-1 Background and Objectives Nam Theun 2 (NT2) is a planned hydroelectric project of a thousand megawatts in the Lao PDR to be developed by a private company (NTPC). The Government of Laos (GOL) is a 25 percent shareholder in NTPC. Upon anticipated commencement of commercial operation in 2009 (FY2010), NTPC will sell fixed amounts of power at pre-negotiated prices to the Electricity Generating Authority of Thailand (EGAT). 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 is a complement to an earlier study with the same name, the Regional Economic Least-Cost Analysis of June 2004 (RELC/2004),1 developed in cooperation with the Electricity Authority of Thailand (EGAT), utilizing EGAT’s least-cost planning tools. That study assessed the economic viability of NT2 from a regional2 perspective through a structured “cost- risk� analysis that evaluated the project in light of alternative outlooks on demand, natural gas prices and NT2 construction costs. The study was conducted solely from an economic perspective. Rapidly changing events subsequent to the publication of RELC/2004 led The World Bank to conclude that the earlier results should be completely reassessed. Most significantly, NT2 costs have increased since early 2004, and the world has experienced a dramatic increase in fossil fuel prices. Both of these changes potentially impact the viability of the project. Moreover, the Bank concluded that it would be useful to conduct, along with the economic analysis, a parallel commercial analysis on a totally consistent basis. The current study reports the findings of the analysis conducted to achieve these expanded objectives. Chapter 2 presents the demand forecast of the regional power system which has been adopted for the current study. Chapter 3 presents detailed background on the existing power supply system, and on candidate plants for future system expansion. S-2 Study Objective and Methodology 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 for calculating the probability-weighted present value (PV) costs of either implementing or not implementing NT2 for commercial operation in FY2010, given the interplay of 1 Robert Vernstrom, Regional Economic Least-Cost Analysis, Bangkok, June 2004. The World Bank financed and supervised the study. Throughout this document, the original study is referenced as RELC/2004, while the present study is referenced as RELC. 2 Throughout this document, the word “regional� refers Lao PDR and Thailand. Executive Summary ii several major uncertain factors – project cost, long-term demand for electricity, and long-term economic value of natural gas as well as the suggested probabilities of occurrence for Base Case, Low and High estimates of these variables. The difference between the probability weighted PV cost of implementing the project in FY2010 versus not implementing it at all is the decision criteria for this analysis. A lower net present value (NPV) “with NT2� would indicate that the project is an efficient economic investment for the regional power market. The specific steps undertaken to complete the cost-risk analysis are summarized in the following paragraphs:  Determine Base Case, Low, and High real economic values for the three key uncertainties expected to have the most significant potential impact on the economic decision to develop NT2 – (i) project cost, (ii) growth rate of electricity demand, and (iii) the economic value of natural gas.  Define a probability of occurrence for each state (Base Case, Low, and High) of each variable.  Run the PROSCREEN expansion planning model under Economic Base Case assumptions with NT2 as a candidate competing for a place in the least- cost expansion plan from its earliest expected commercial operation date of FY2010. This initial analysis added NT2 to the system in FY2010, i.e., it specified that the least-cost expansion plan included NT2 commencing operation in October 2009. (By FY2010, EGAT's current capacity surplus is fully absorbed, and NT2 is selected as the least cost capacity addition to achieve the target reliability criterion of 15 percent.) This date was therefore fixed for all subsequent "with NT2" model runs to conform to the logic of the decision matrix (the decision being whether to develop NT2 for commercial operation in October 2009 or not to do so).  Run the PROSCREEN generation expansion planning model with NT2 commencing commercial operation in FY2010 for all combinations of the above-defined uncertainties. The PROSCREEN “objective function� (i.e., basis for comparison of results) is the present value of future investment and operating costs over the Study Period.  Re-run each of the defined scenarios without NT2 so that demand must be served from alternative resources.  Calculate the probability-weighted present value of costs for the “with NT2� and “without NT2� scenario groups.  Subtract the probability-weighted result “with NT2� from the result “without NT2� to determine the Study outcome.  Repeat the above analysis, converting all real economic values in the least- cost planning runs to nominal commercial values (i.e., using market prices including inflation). This analysis is designed to test the long-term Executive Summary iii sustainability of the PPA in a competitive commercial market environment. We refer to these cases as the Commercial model runs. To complete the Cost-Risk Framework, a total of 18 scenario runs are required (9 “with NT2� and 9 “without NT2�), or a total of 36 model runs for both the economic and commercial cost-risk assessments. These scenarios are formed from combinations of two planning 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 were expanded to 27 scenarios for the economic assessment by combining manually the three cases for the construction cost of NT2 with the results of the other scenarios. High and low project cost is not evaluated in the commercial runs because the commercial arrangement is a fixed-price PPA. A complete economic cost-risk analysis – requiring 18 PROSCREEN model runs by EGAT system planners – was prepared for the RELC/2004 study. Although the World Bank wished to update that economic analysis to incorporate current information (i.e., current perspectives on Thai fuel prices and the most recent data on NT2 capital cost) and to conduct a parallel commercial analysis of equivalent scope, it was considered unnecessary (and unreasonable!) to request twice the original support (i.e., 36 model runs, each requiring considerable set-up and run time) from the EGAT System Planning Division. It was therefore decided to focus the cost-risk analysis for the current study only on the downside risks to NT2. Specifically, the analysis was limited to the base case and those cases which could be expected to pose the greatest test to project viability, i.e., conditions of lower than expected demand, lower than expected fuel prices, and higher than anticipated NT2 capital costs. 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 and up to 300 GWh per year.  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 commence commercial operation according to schedule.  The schedule for plant retirements follows the assumptions detailed in Table 12.  NT2 (995 MW) is added to the system in FY2010 (October 2009) in the “with NT2� scenarios. Executive Summary iv  All other plants – including plants proposed for reconditioning and all generic expansion options (see Table 13) – are modeled as candidates which must compete for a place in the least cost economic plan.  Generation of existing plants and selected candidates is dispatched by PROSCREEN according to the following rules:  All non-thermal generation – notably domestic hydro plants and Lao imports – is dispatched first, without regard to cost, since capacity costs are sunk and operating costs negligible. With the exception of EGAT’s own hydro capacity, each of these resources is modeled as a separate transaction, defined from contractual purchase price and operating constraints.  NT2 energy is dispatched in two parts according to the monthly variation reported in Chapter 3, one to provide peak-period energy and a second to provide off-peak energy.  All thermal generation – the majority of the entire system – is subject to economic dispatch, and each unit is run only when it is lowest cost. Exceptions are small power producers (SPPs), which are assumed to run at an 80 percent capacity factor. S-3 Results of the Economic Assessment The Base Case economic analysis tells us that NT2 should be included in the region’s least cost generation expansion plan. The accumulated present value of real resource savings to the region over the entire Study Period (FY2003-14 and beyond3) totals US$266 million at 2003 prices.4 The project outcome is determined by a cost-risk analysis, designed to determine whether the same decision is justified given the high probability that future events will diverge from Base Case assumptions. The key decision variables for this study are defined in the study TOR (see Appendix A1). They are:  Capital cost of NT2. The World Bank has specified a cost range of +30 percent (High capital cost) and –30 percent (Low capital cost); these values are reported in Table 17. 3 The Study Period includes both the planning period (FY2003-14) and an "end effects" analysis which utilizes sophisticated programming techniques to analyze differences between alternatives (e.g., due to different lives and operating characteristics) beyond the planning period. Without an end-effects analysis, results may be biased against commissioning capital-intensive units near the end of the planning period. 4 The costs and benefits being evaluated in this report are in general restricted to the power sector, but for NT2 they include all the environmental and social costs that the project will fund directly as per agreement with the developer. The US$ 266 million represents a ‘savings� since the least-cost plan without NT2 would come at greater total cost. Executive Summary v  Regional demand forecast. The World Bank has specified a very wide range in order to reflect the Bank's long-term experience with demand forecast performance;5 the regional High and Low demand forecasts are summarized in Table 9.  Natural gas price forecast. The World Bank commissioned a separately prepared forecast of natural gas prices taking into account region-specific pricing conventions with indexation factors based on its own world petroleum product price projections, with particular emphasis on the price of natural gas since gas is the most competitive alternative fuel. The Base Case projections are presented in Table 14; High and Low scenarios are reported 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 in the cost-risk matrix, with the High and Low assumption values assigned a probability of 25 percent each. Table S-1. Economic Cost-Risk Analysis Results A. Present Values WITH NT2: CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Savings by Case Probability Case Probability Case Probability Case Present Value Probability Scenario h 0.25 h 0.25 h 0.25 hhh 46,808 0.01563 61 h 0.25 h 0.25 m 0.50 hhm 46,808 0.03125 61 h 0.25 h 0.25 l 0.25 hhl 43,741 0.01563 (6) h 0.25 m 0.50 h 0.25 hmh 46,808 0.03125 61 h 0.25 m 0.50 m 0.50 hmm 46,808 0.06250 61 h 0.25 m 0.50 l 0.25 hml 43,741 0.03125 (6) h 0.25 l 0.25 h 0.25 hlh 34,548 0.01563 (181) h 0.25 l 0.25 m 0.50 hlm 34,548 0.03125 (181) h 0.25 l 0.25 l 0.25 hll 32,214 0.01563 (259) m 0.50 h 0.25 h 0.25 mhh 46,603 0.03125 266 m 0.50 h 0.25 m 0.50 mhm 46,603 0.06250 266 m 0.50 h 0.25 l 0.25 mhl 43,536 0.03125 199 m 0.50 m 0.50 h 0.25 mmh 46,603 0.06250 266 m 0.50 m 0.50 m 0.50 mmm 46,603 0.12500 266 m 0.50 m 0.50 l 0.25 mml 43,536 0.06250 199 m 0.50 l 0.25 h 0.25 mlh 34,343 0.03125 24 m 0.50 l 0.25 m 0.50 mlm 34,343 0.06250 24 m 0.50 l 0.25 l 0.25 mll 32,009 0.03125 (54) l 0.25 h 0.25 h 0.25 lhh 46,399 0.01563 471 l 0.25 h 0.25 m 0.50 lhm 46,399 0.03125 471 l 0.25 h 0.25 l 0.25 lhl 43,331 0.01563 404 l 0.25 m 0.50 h 0.25 lmh 46,399 0.03125 471 l 0.25 m 0.50 m 0.50 lmm 46,399 0.06250 471 l 0.25 m 0.50 l 0.25 lml 43,331 0.03125 404 l 0.25 l 0.25 h 0.25 llh 34,138 0.01563 228 l 0.25 l 0.25 m 0.50 llm 34,138 0.03125 228 l 0.25 l 0.25 l 0.25 lll 31,804 0.01563 151 A. Probability-weighted Present Value WITH NT2 42,817 1.00000 B. Present Values WITHOUT NT2: POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 hh 46,869 0.06250 h 0.25 m 0.50 hm 46,869 0.12500 h 0.25 l 0.25 hl 43,735 0.06250 m 0.50 h 0.25 mh 46,869 0.12500 m 0.50 m 0.50 mm 46,869 0.25000 5This m 0.50 l 0.25 ml experience also reflects extreme and unexpected events, such 43,735 0.12500 as the Asian economic crisis of l 0.25 h 0.25 lh 34,367 0.06250 1997, but that is not the primary consideration for the wide range l 0.25 m 0.50 lm adopted. 34,367 0.12500 l 0.25 l 0.25 ll 31,955 0.06250 B. Probability-weighted Present Value WITHOUT NT2 43,005 1.00000 Probability-weighted PV Savings (Cost) WITH NT2 188 (Result A minus Result B; 2003 USD million) Executive Summary vi The results of the economic cost-risk analysis are summarized in Table S-1.6 The analysis concludes that the probability-weighted accumulated present value of real resource savings to the region as a result of the development of NT2 is US$188 million in present value terms. This result is marginally lower than the Base Case present value of US$266 derived without incorporating probabilistic outcomes for key variables, but the result confirms project viability from an economic, real resource perspective. S-3 Results of the Commercial Assessment In parallel with the economic cost-risk analysis, a commercial cost-risk analysis is also performed, as presented in Chapter 6. The key differences between the economic and the commercial analyses relate to both the purpose of the analysis and the valuation of costs, as summarized in Table S-2. Table S-2.Comparison of Economic and Commercial Analyses Economic Commercial Issue Is the project an efficient Do the commercial arrangements badly Addressed allocation of real resources? distort economic value? Does the PPA appear commercially sustainable? Perspective Regional economy of Laos and Costs facing the power sectors of the Thailand two countries Valuation Real [constant] dollar cost of Nominal [current] dollar cost at real resources used for market prices incurred by the power investment and operation sector to provide electricity Discount rate 10% real 10.45% nominal, the project weighted average cost of capital Cost of NT2 Real investment cash flows PPA payments Taxes and Excluded Included royalties Sunk costs Excluded Included Environmental Included Excluded credit 6 As noted above, PROSCREEN modeling was limited to consideration of the downside risks to the NT2 project. In order to complete the full matrix, “Medium� scenario results have been used in the table to substitute for the results what would have occurred with the current set of High demand and High natural gas price assumptions, since these scenarios were not evaluated for the current study. Simple logic and the results of RELC/2004 confirm that this procedure understates the economic advantage of NT2, since scenarios with High demand and High natural gas prices would result in higher net savings attributable to NT2 than these proxies indicate. Executive Summary vii Notwithstanding the strongly positive economic preference for the project, the commercial analysis is relevant because taxes, royalties and payment arrangements create a large difference between the economic and the commercial cost of supplying electricity in both the "with NT2" and "without NT2" project scenarios. In these circumstances it is important to evaluate the risk of the commercial arrangements distorting the contracting parties’ shared perception of the project’s economic benefit to the region. Results of the commercial cost-risk analysis are reported in Table S-3. The risk- adjusted savings “with NT2� are estimated to be US$145 million.7 These results confirm our Base Case conclusion that NT2 is a viable investment project from a commercial perspective. Table S-3. Commercial Cost Risk Analysis Results A. Present Values WITH NT2: CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Savings by Case Probability Case Probability Case Probability Case Present Value Probability Scenario m 1.00 h 0.25 h 0.25 mhh 61,939 0.06250 227 m 1.00 h 0.25 m 0.50 mhm 61,939 0.12500 227 m 1.00 h 0.25 l 0.25 mhl 58,900 0.06250 161 m 1.00 m 0.50 h 0.25 mmh 61,939 0.12500 227 m 1.00 m 0.50 m 0.50 mmm 61,939 0.25000 227 m 1.00 m 0.50 l 0.25 mml 58,900 0.12500 161 m 1.00 l 0.25 h 0.25 mlh 43,886 0.06250 (32) m 1.00 l 0.25 m 0.50 mlm 43,886 0.12500 (32) m 1.00 l 0.25 l 0.25 mll 41,529 0.06250 (109) A. Probability-weighted Present Value WITH NT2 56,708 1.00000 B. Present Values WITHOUT NT2: POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 hh 62,166 0.06250 h 0.25 m 0.50 hm 62,166 0.12500 h 0.25 l 0.25 hl 59,060 0.06250 m 0.50 h 0.25 mh 62,166 0.12500 m 0.50 m 0.50 mm 62,166 0.25000 m 0.50 l 0.25 ml 59,060 0.12500 l 0.25 h 0.25 lh 43,854 0.06250 l 0.25 m 0.50 lm 43,854 0.12500 l 0.25 l 0.25 ll 41,420 0.06250 B. Probability-weighted Present Value WITHOUT NT2 56,854 1.00000 Probability-weighted PV Savings (Cost) WITH NT2 145 (Result A minus Result B; 2003 USD million) S-4 Conclusion Economic and Commercial assessments of the project conclude that the decision to purchase NT2 power offers significant savings to the regional power system. The economic evaluation, based on a probability-weighted real cost-risk analysis of downside risks, indicates a real savings (i.e., in present value terms at 2003 prices) on the order of US$188 million will accrue to the region over the lifetime of the plant. 7 As previously explain for the economic cost-risk assessment, modeling was limited to consideration of the downside risks to the NT2 project, completing the matrix with a procedure which understates the net advantage of NT2. See footnote 6. Executive Summary viii Actual savings might be even higher under possible future conditions, such as higher- than-expected demand growth or higher-than-expected gas prices. More importantly, however, the decision to purchase a major source of energy at fixed price is robust to a wide range of behavior for the key 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 fuel price volatility, a feature of energy markets in recent decades that is expected to persist. As with any risk-return trade- off, the project is also subject to reduced net benefits if future economic conditions are adverse from the perspective of NT2, i.e., lower-than-expected demand and gas prices. The commercial analysis, based on market costs expressed in current prices, suggests that the decision to purchase NT2 power will result in a nominal savings in present value terms on the order of US$145 million. This result indicates that the project remains commercially viable even after large real resource benefits accruing to the region in the economic analysis are paid by project sponsors directly to the government of Lao PDR in the form of taxes, duties, and royalties, and indirectly through the funding of environmental and social programming. Introduction 9 1 INTRODUCTION 1.1 Background Nam Theun 2 (NT2) is a planned hydroelectric project of a thousand megawatts8 in the Lao PDR to be developed by a private company (NTPC). The Government of Laos (GOL) is a 25 percent shareholder in NTPC. Upon anticipated commencement of commercial operation in 2009 (FY2010), NTPC will sell fixed amounts of power at pre-negotiated prices to the Electricity Generating Authority of Thailand (EGAT). While NT2 will be operated and maintained by NTPC, the facility will be under the full dispatch control of EGAT. The World Bank has supported the GOL in the development of the NT2 Project. In fact, 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 is a complement to an earlier study with the same name, the Regional Economic Least- Cost Analysis of June 2004 (RELC/2004),9 developed in cooperation with the Electricity Authority of Thailand (EGAT), utilizing EGAT’s least-cost planning tools. That study assessed the economic viability of NT2 from a regional10 perspective through a structured “cost-risk� analysis that evaluated the project in light of alternative outlooks on demand, natural gas prices and NT2 construction costs. The study was conducted solely from an economic perspective. Rapidly changing events subsequent to the completion of RELC/2004 led The World Bank to conclude that the earlier results should be completely reassessed. Most significantly, NT2 costs have increased since early 2004, and the world has experienced a dramatic increase in fossil fuel prices. Both of these changes potentially impact the viability of the project. Moreover, the Bank concluded that it would be useful to conduct, along with the economic analysis, a parallel commercial analysis on a totally consistent basis. According to the Bank’s operational guidelines, the economic 8 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 of the installed turbines. EGAT, however, designates the plant as 920 MW, the estimated minimum monthly 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 of system reliability, so that EGAT can be certain of this minimum level of delivery. The contract permits EGAT to request more than 100 percent of this capacity with permission from NTPC. For purposes of this study, which adopts a regional perspective, NT2 is defined as a 995 MW plant (i.e., 920 MW delivered to Thailand plus 75 MW Lao domestic load). The contract is priced and largely defined in terms of GWh, hence the MW accounting definition is not important for purposes of this analysis. 9 Robert Vernstrom, Regional Economic Least-Cost Analysis, Bangkok, June 2004. The World Bank financed and supervised the study. Throughout this document, the original study is referenced as RELC/2004, while the present study is referenced as RELC. 10 Throughout this document, the word “regional� refers Lao PDR and Thailand. Introduction 10 analysis is intended “…to determine whether the project creates more net benefits to the economy than other mutually exclusive options for the use of the resources in question...� and will “…help meet economically efficient demand at the least economic cost.� The parallel commercial analysis is intended to determine if the agreed commercial arrangements for the project badly distort the economic values and if the agreement appears to be commercially sustainable. The current study reports the findings of the revised and updated analysis conducted to achieve these expanded objectives. Briefly, the study includes a thorough comparison of the real resource cost to the regional economy of power sector development “with� and “without� NT2. Results incorporate a probabilistic “cost- risk� assessment of this comparison over a range of project uncertainties, including capital costs, future gas prices, and Thai load growth. In addition to the real economic assessment, a commercial assessment (at nominal prices) is also reported. The Terms of Reference presented in Appendix A1 detail the Bank's requirements for the 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 for calculating the probability-weighted present value (PV) costs of either implementing or not implementing NT2 for commercial operation in FY2010, 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 the suggested probabilities of occurrence for Base Case, Low and High estimates of these variables. The difference between the probability weighted PV cost of implementing the project in FY2010 versus not implementing it at all is the decision criteria for this analysis. A lower net present value (NPV) “with NT2� would indicate that the project is an acceptable economic investment for the regional power market. In addition to the real resource cost analysis outlined above, the study also includes a commercial assessment of the project under which the economic values are converted to commercial values and expressed in nominal US dollars, in order to assess the possible emergence of risks to the commercial sustainability of NT2 in the regional power market. 1.3 Organization of the Report This study is above all a careful review of anticipated electricity demand and supply in the region, and of the role of NT2 in meeting future requirements. The next two chapters present the basic demand and supply assumptions adopted for the analysis. Chapter 2 reports on the methods used to forecast the power Introduction 11 market, 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 begins with 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 of future planning uncertainties. Chapter 6 reports a parallel least-cost analysis from a commercial perspective. This analysis is based on the same underlying assumptions as the economic analysis reported in Chapter 5, except that nominal market prices are used instead of real resource costs. Chapter 7 presents a summary of results, and the conclusion of the study. System Demand Assumptions 12 2 S YSTEM D EMAND A SSUMPTIONS Load forecasting in Thailand is a collaborative effort of the major stakeholders. The Thailand Load Forecast Sub-committee (TLFS)11 considers all methodological issues, and reviews the work of participating agencies before integrating results into a national load forecast. The methodologies applied in forecasting have been developed and refined for over a decade, originally with international consulting assistance funded by CIDA, the Canadian development agency. In fact, methods are continuously evolving, as the TLFS strives to refine its techniques with each succeeding forecast. The most recent load forecast of the TLFS was issued in January 2004, and adopted for EGAT’s 2004 Power Development Plan. Reflecting recent GOT optimism regarding prospects for economic growth, this forecast projects more rapid growth in electricity consumption than the immediately preceding forecast of August 2002. RELC/2004 revealed that more rapid expansion of the power sector tends to increase the viability of NT2; hence, to provide a more severe Base Case test of the project's economic merit and reduce the risk of overstating Base Case demand, it was decided to conduct the current study based on the more conservative demand forecast of August 2002. Appendix A2 provides a comparison of the two forecasts. However, this report relies entirely on the lower August 2002 forecast. Section 2.1 presents an overview of the forecasting methodology. Section 2.2 is a review of historical forecasting performance. Finally, Section 2.3 recommends Base Case, 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 the appropriate technique varying by  distribution company (MEA in greater Bangkok, and PEA in the rest of the country)  customer class (i.e., residential, small and large business, industrial, etc.), and  forecast horizon (i.e., short-term or long-term). 11The committee is comprised of representatives from EPPO (formerly NEPO), EGAT, MEA, PEA, DAEDE (formerly DEDP), NESDB, the National Statistics Office (NSO), the Federation of Thai Industries, the Thailand Chamber of Commerce, the Association of Thai Power Generators, and the Thailand Development and Research Institute (TDRI). System Demand Assumptions 13 Four methods are used for energy forecasting. Two of these methods might be described 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 on macroeconomic trends. There is also an independent method for forecasting peak demand. These methods are briefly summarized in the following paragraphs.  End-Use Model. Consumption for residential customers throughout Thailand is derived from comprehensive surveys of dwelling types by income, and appliance utilization in each. Forecasts depend on growth in number of households, appliance saturation, and expected appliance efficiency improvement.  Floor Space Model. Short-term (less than 5 years) consumption for large business (commercial customers > 30 kW) in the MEA service territory is forecast based on available data on floor space by type of building. Data on building stock is adjusted for factors such as demolition, construction deferral, occupancy rate, etc. Total consumption is then calculated from survey data on energy use within each type of building. Again, factors are applied to incorporate efficiency improvement into the forecast.  Energy Intensity Model. Gross domestic product (GDP) is carefully disaggregated by region and by business sector so that energy consumption relationships by sector can be evaluated. Total consumption is derived based on historical consumption per unit of gross regional product (GRP), and the forecast growth in GRP by sector. The energy intensity model is used where “first hand� sources (e.g., Board of Expansion data, and surveys of available floor space) are unavailable, especially for longer-term forecasting.  Econometric Regression. When class consumption patterns are not attributed to clearly identifiable relationships (e.g., appliance usage, floor space, sector energy intensity), econometric regression is used to define the relationship. The method is particularly applied to small business, and to other classes in which users have widely diverse consumption characteristics.  Peak Demand Model. The TLFS has developed substantial load research data by customer group over recent years through extensive surveys, and applies this information to project demand from energy forecasts developed using the foregoing methods. The number of customers within each class is forecast based on regression analysis, and daily load curves derived from the load research data are used to forecast coincident and non-coincident peak for each customer group. Peak losses are also forecast 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 System Demand Assumptions 14 Growth in electricity demand is highly correlated to medium and long-term economic growth prospects (especially economic growth per consuming unit, e.g. per household or per unit of industrial output). Each of the methods used by the TLFS consider income, 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 floor space model directly measures economic expansion among large businesses. The energy intensity model relates energy requirements to anticipated growth in value added by business sector. Economic regression analysis typically incorporates an income term (e.g., gross regional product by business sector) into its forecast equations. 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 Same approach, by region (e.g., BOI, applications for service, targeted surveys) Long-term: Energy intensity model (energy intensity per unit of value added) Large Business Short-term: Floor Space model Energy intensity model by (>30 kW) Long-term: Energy intensity business sector by region model by business sector Small Business Econometric regression Same approach, by region Other Classes Econometric regression Same approach Peak Demand Daily load curves by customer Same approach group applied to regression- derived customer forecasts by class. System coincident peak derived from coincident peak of each class. Notes: (1) All methods incorporate adjustments for efficiency improvement over time; e.g. end-use models assume progressive improvement in efficiency of household appliances, and energy intensity 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 crucial factor in their accuracy. The Government of Thailand (GOT), through its National Economic and Social Development Board (NESDB), forecasts anticipated national GDP, but typically only for five years (i.e., the next national plan). For long-term trends, the TLFS has relied on the Thailand Development and Research Institute (TDRI) to project economic growth and to disaggregate the national GDP forecast by region and by business sector. TDRI was hired to develop these trends for the System Demand Assumptions 15 September 1998 forecast, and is revising economic projections which will be applied in future load forecasts. TDRI applies a very complex model to develop these results.12 Table 2. National GDP Growth Assumptions Sep-97 Sep-98 Forecasts Assumptions 1/ Sep-01 Year 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. National economic projections applied for recent load forecasts are compared in Table 2. 12 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-year national plans. The model is very large and requires considerable time to readjust and calibrate a new forecast series. The most time-consuming part of the projection process, however, is to allocate the 15-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 establish baseline information for each regional forecast. The TLFS requires long tem economic projections 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 response to alternative views of economic growth. Given the difficulty that all economists have experienced in forecasting national (and international) economic growth in recent years, this slow response time could be disadvantageous. System Demand Assumptions 16 The August 2002 load forecast adopted the Sep-98 (MER) economic outlook for the period following NESDB’s near-term prediction (i.e., 2006-11). The TLFS noted that the 4.7% average annual GDP growth under MER for the Ninth Plan (2001-06) was very close to the NESDB’s projection of 4.6% for the same period. Furthermore, the TLFS believed that the average long term annual growth rate of 4.7% assumed in the Sep-98 (MER) was still a reasonable estimate. Therefore, the committee decided to adopt the NESDB short-term and MER long-term economic outlooks for the Aug-02 load forecast.13 Recent economic growth trends – and medium-term forecasts – are more optimistic than the foregoing assumptions reflect. Actual 2003 growth will be approximately 6 percent; the GOV is projecting 2004 growth of about 8 percent. The World Bank is cautiously optimistic, expecting 6 percent growth in 2004, but expressing several concerns regarding the sustainability of high growth in the medium-term. Specifically, the Bank notes that private consumption has been the chief driver of recent expansion, and that private investment's contribution to growth has been less than in previous economic recoveries and remains lower than that of many other countries in the region. Corporate access to credit has been constrained by a cautious banking sector and slow structural reforms. Export growth has been relatively strong, however, an appreciating exchange rate, capacity constraints, and growing competition in the region could restrain this growth. 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 legal reform, has been limited. In summary, World Bank economists argue that Thailand will need to improve its competitiveness and productivity in order to convert the current recovery into sustained high growth over the medium-term. Price Considerations in the Forecast The load forecasting methodologies do not explicitly consider price as an independent variable in forecasting demand. However, the impacts of historical price changes are captured in the forecasts. For example, surveys for the end-use forecasts reflect price changes through adjustments in appliance usage and saturation. Floor space models capture changes in energy use per unit of floor space which may have occurred in part 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 each class load forecast, the August 2002 Base Case is further adjusted downward to reflect the impact of a group of on-going electric energy conservation programs being 13While it is beyond the scope of the current study to produce a new load forecast, it should be noted that recent economic performance of Thailand has exceeded forecasts, and analysts are generally optimistic regarding medium-term economic growth prospects. System Demand Assumptions 17 undertaken by various GOT agencies, including EPPO (formerly NEPO), DAEDE (formerly DEDP), and EGAT. Table 3 summarizes the complete package of conservation activities; this package represents the official plan of the GOT adopted by the Cabinet. The final lines of the table show the conservation program included in the Aug-02 Base Case forecast. (The forecast excludes 2,516 GWh of conservation savings achieved by FY2002; TLFS has assumed that this conservation is already reflected in base year consumption data.) In fact, the TLFS has been very concerned about the effect of energy efficiency improvement on future electricity demand, and established a special working group to make a detailed assessment of the various conservation-related programs. The findings of that group indicated that official estimates were probably too high, for the following reasons:  Only about 15% of the planned electricity demand reduction in the next 10 years is expected to come from mandatory programs where the set targets are reasonable. The remaining 85% reduction in electricity demand is anticipated to come from numerous voluntary programs. The success of these programs will depend on their implementation procedures and consumer willingness to participate. These factors are not yet clearly defined.  Several programs have missed implementation deadlines, and many are expected to face further delay. Other programs (e.g., switching street lighting off late at night) have faced opposition from highway safety engineers, and may not be implemented. After considerable debate, the TLFS decided to reduce the amount of conserved electricity by nearly 30% in the year 2011 for the Aug-02 load forecast. (An even greater cut was considered, but it was decided to give the programs an opportunity to achieve targeted progress. A more critical evaluation will be incorporated into subsequent load forecasts.) The forecast incorporates a total conservation savings of 982 MW by 2011. System Demand Assumptions 18 Table 3. Integrated National Electricity Conservation Program Responsible Planned Conservation Savings (GWh) Program Agency 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. The conservation program outlined in Table 3 is part of a 10-year master plan developed by responsible GOT agencies, which emphasized technical/economic potential rather than financial/legal constraints.14 Table 4 presents an informal “order of magnitude� alternative view of conservation potential based on the Consultant’s discussions with conservation planners. This alternative scenario is presented for discussion purposes only, intended to crudely quantify the widely held opinion that the program in Table 3 may be unduly optimistic with regard to potential savings. The alternative view in Table 4 suggests that only half 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 forecast currently used by EGAT almost certainly assumes greater conservation than the electricity sector will actually achieve over the forecast period.15 14Most of the funding for energy conservation will come from the “ENCON Fund’, which is financed through a targeted tax on petroleum products of THB 0.40 per liter. 15 Unlike some of the other programs, EGAT’s own DSM Program has been proceeding according to plan. The program is funded directly by EGAT (vs. the ENCON Fund), and conservation savings are projected to exceed the level forecast in the consolidated national conservation plan (Table 3). In Table 4, we have adopted EGAT’s forecast of DSM savings through FY2006, and have conservatively assumed no increases thereafter. System Demand Assumptions 19 Table 4. National Conservation Program – Alternative View Responsible Planned Conservation Savings (GWh) 1/, 2/ Program Agency 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. EPPO is currently developing a more realistic program guided on funding and other limitations. As of the publication of this study, a conservation action plan is not yet finalized. Significantly, however, EPPO reports Cabinet-level approval for a major reduction in national energy consumption, expressed as a target energy elasticity of 1.0 versus the current level of 1.3 or more (see Section 2.2). Although this is a worthwhile objective, it is perhaps premature to presume the schedule for meeting of this goal, given that no action plan is in place, and no performance record exists from which to define a realistic pace for achieving the target. It is important to put these conservation savings in perspective. The total savings are significant – 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’s national demand growth (even when assuming a low demand forecast); hence, they do 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 and 6 summarize the Energy Requirements and Peak Demand projections from many of these forecasts, excluding those prepared immediately before and after the onslaught of the Asian economic crisis in July 1997. The crisis, with its profound impact on the Thai economy, including electricity consumption, rendered earlier forecasts irrelevant for future planning.16 Even the first “post-crisis� forecast (September 1997) proved naively optimistic in its outlook for economic recovery. (Thai forecasters, like economists 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. 16 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 in 2011 to exceed 42,000 MW, 45% more than the August 2002 forecast. System Demand Assumptions 20 Table 5. Historical Energy Requirements Forecasts (GWh) Forecasts by Publication Date Fiscal Actual Jun-93 Dec-94 Oct-95 Sep-98 Feb-01 Aug-02 Year 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% The forecast of September 1998 was much more successful at incorporating the potential implications of the crisis on electricity consumption. It included three scenarios 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 the Government of Thailand (NESDB), and incorporated conservation program planning. The dramatic changes in near-term expectations regarding national electricity requirements are obvious in Tables 5 and 6. But it is equally interesting to observe from the tables that expected average annual growth rates for medium to long-term projections show little variation. For the period 2001-06, the annual rate of growth in 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. For the period 2006-11, five forecasts project average annual generation growth between 5.7 and 6.3 percent. System Demand Assumptions 21 Table 6. Historical Peak Demand Forecasts (MW) Forecasts by Publication Date Fiscal Actual Jun-93 Dec-94 Oct-95 Sep-98 Feb-01 Aug-02 Year GWh 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% This similarity of result is surprising, given that each forecast started from a different base and with different macroeconomic expectations (the associated national GDP forecast, as reported in Table 2). Table 7 shows the simple income (GDP) elasticity of demand implied by each energy requirements forecast.17 These elasticities have typically ranged from 1.30 to 1.40, with many individual year elasticities falling outside this narrow band.18 Considering that income elasticity was not a basis for energy forecasting of many consumer categories, the implied elasticities are surprisingly stable across these recent forecasts.19 Interestingly, however, the highest of these forecasts (Sep-98 RER) had lower-than-average income elasticities, and the lowest forecast (Sep-98 LER) has somewhat higher-than-average income elasticities, in later forecast years. This confirms that income elasticities were not the basis for these forecasts. 17 Clearly, a far more meaningful elasticity measure would be income per consuming unit by customer class (e.g., electricity consumption growth per consuming unit of industrial value added per company or per commercial establishment). We have used a far less detailed approach, since our objective is only to confirm to reasonableness of the Base Case forecast. 18The TLFS has independently estimated income (GDP) elasticity of demand. We understand that these unpublished investigations estimated an average income elasticity of about 1.4. 19 The actual experience reported in Table 7 for the period 1995-2001 tells a somewhat different story; electricity demand appears to have been far more stable than the performance of the income variables, causing remarkable variance of the implied elasticity from year to year. System Demand Assumptions 22 Table 7. Implied Income Elasticity of Energy Requirements Forecasts Sep-98 Forecasts Assumptions Feb-01 Aug-02 Year Actual RER MER LER Base Base 1994 1.41 1995 1.51 1996 1.57 1997 n/m 1998 0.06 1999 n/m 2000 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 Table 8 summarizes forecast performance in terms of accuracy for each year after publication, excluding the “crisis years.� With few exceptions, demand and energy forecasts 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 early warning of the pending crisis.) This performance suggests that the short-term forecasting 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 assess the accuracy of Thailand’s forecasting models under a period of more stable market conditions. Table 8. Historical Forecast Accuracy 1 / Forecasts by Publication Date Years Jun-93 Dec-94 Oct-95 Sep-98 Feb-01 Forecast 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 Demand 1 -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 year after publication. Forecasts by Publication Date Years Jun-93 Dec-94 Oct-95 Sep-98 Feb-01 Forecast RER MER LER Base Energy Requirements Forecasts 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% System Demand Assumptions 23 2.3 Load Forecast Adopted for this Study The August 2002 Base Case load forecast20 is the planning basis for EGAT’s PDP 2003, and is used for the current study. It is a technically and methodologically sound basis for future system planning. Due to the unique regional perspective of the present study, there are differences between the Base Case forecast used in this report and the August 2002 load forecast. Specifically, the Base Case forecast includes Lao domestic load which is assumed 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 net generation and 75 MW of peak demand.21 Low and High demand forecasts, as requested by the World Bank, reflect a wide band of future loads. Based on the Bank's extensive experience with long-term load forecast accuracy around the world, the Bank specified the Low and High Case demand forecasts to be symmetrically keyed off the Base Case forecast using the following equations, reflecting the percentage gap between these forecasts that the Bank 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 Case growth 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 energy requirements 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 forecast years. Table 9 summarizes all three forecast scenarios adopted for this study. The average annual growth rates of these scenarios range from a Low of about 3.4 percent to a High of nearly 9 percent. This wide band subsumes the range of futures that have been projected in the recent past: (i) the GOT's very optimistic economic growth and energy conservation targets, (ii) the World Bank's more cautious growth perspective coupled with slower energy elasticity improvement, and (iii) the slower 20 For readers who would like to review the August 2002 forecast in greater detail, complete results by customer class for MEA, PEA, and direct customers of EGAT are reported in Appendix A2. 21 A necessary corollary of this assumption is that Laos’ alternative to NT2 for meeting this portion of its demand would be import of electricity from Thailand. Further, this load increment is presumed to mirror 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 and possible introduction of TOU tariffs to flatten the curve), modeling of the future Lao system would be speculative at best. System Demand Assumptions 24 growth outlook that drives the Base Case forecast. The volatility of recent economic prognostications highlights the futility of projecting long-term economic performance with accuracy; it is reassuring to know that the current analysis incorporates consideration of this uncertainty. Note that the forecasts presented in the table exclude station use in order to conform to the requirements of the model (“PROSCREEN II�) used for least-cost expansion planning. Net generation and net peak forecasts are shown; these forecasts are on the order of 2 percent lower than the Base Case forecast reported in Tables 5 and 6. Table 9. Recommended Load Forecast for this Study RECOMMENDED LOAD FORECAST (net, including Lao Load) 1/,2/ Gross Energy Requirement (GWh) Peak Demand (MW) High Base Low High Base Low 2002 - 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, the energy and demand assumed to be fully absorbed from NT2 project output. System Supply Assumptions 25 3 S YSTEM S UPPLY A SSUMPTIONS This Chapter of the report describes the existing power system and the options available for system expansion in order to provide for the demand growth identified in Chapter 2. Section 3.1 summarizes the existing power system. Section 3.2 describes candidates for system expansion, including their capital and operating costs. Assumed fuel prices for the system are presented in Section 3.3. Section 3.4 is a preliminary screening analysis of thermal expansion candidates that illustrates their competitive advantages at different utilization factors. Finally, Section 3.5 discusses the non-thermal alternative 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 for defining the existing system, committed additions and retirements. All tables and calculations reported in this and subsequent chapters of the report assume the same base as PDP 2003.22 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 the total. These units are predominantly gas-fired, although more than 2000 MW of lignite 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 the table, this segment, too, is predominantly gas-fired thermal. Large thermal units – whether oil, lignite, or gas-fired, including purchased power from IPPs and SPPs – have an availability factor of at least 80 percent. (Detailed data by plant is presented in Appendix A4.) Thailand’s hydro capacity is almost entirely reservoir storage. (The exception is 136 MW Pak Mun Dam.) Dependable hydro generation, exogenously estimated using historical records from each site, represents the level of energy assumed to be available by month at the 90 percent confidence level. Capacity factors are relatively low. Lao imports represent purchases of energy from Theun Hinboun and Huay Ho hydroelectric plants whose collective capacity factor is about 65 percent. 22 It should be noted, however, that there are minor discrepancies between actual and planned installed capacity as of end-FY2003 due to minor delays and adjustments in scheduled plant additions (see Appendix A4). System Supply Assumptions 26 Table 10. Installed and Purchased Capacity (as of March 2003) No. of Installed Capacity Plant / Fuel Type Plants 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. Table 11 summarizes committed plant additions from March 2003.23 The table is divided into four groups – EGAT plants, IPPs, SPPs, and NT2 – with a total capacity of nearly six thousand MW including NT2. The first three plants listed are under construction and scheduled to commence commercial operation in FY2003-04. The second group (3,447 MW) includes three IPP plants whose firm contracts have faced long delays due to multiple factors including the Asian economic slowdown and concerted environmental opposition; these issues have been resolved and schedules are now considered firm. The third group (197 MW) includes SPP plants (90 MW maximum plant capacity) under contract for commissioning in the next three years. (Only plants approved by the Energy Conservation Fund as of March 2003 are included.) 23The study assumes installed capacity of 25,697 MW as of September 2003, equal to September 2002 installed capacity of 23,530 plus 2,167 MW added in FY2003; the FY2003 additions are divided between Table 10 (1,848 MW) and Table 11 (319 MW). System Supply Assumptions 27 Table 11. Committed Plant Additions (after March 2003) Capacity EGAT Planned Plant MW Commissiong Date 1/ 1. EGAT Projects 1,307 - Lam Takhong Pumped Storage 500 FY2003-04 - Krabi Thermal #1 300 FY2003-04 - Lan Krabu GT 122 FY2003-04 - Khanom CC 385 FY2007 2. IPP Contracts 1/ 3,447 - BLCP Power - Unit 1 673 FY2007 - BLCP Power - Unit 2 673 FY2007 - Gulf Power 700 FY2008 - Union Power Development - Unit 1 700 FY2008 - Union Power Development - Unit 2 700 FY2009 3. SPP Contracts 2/ 197 - Phase I Contracts 69 FY2003-05 - Phase II Contracts (Renewables) 128 FY2003-05 4. Nam Theun 2 Hydro 3/ 995 FY2010 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. Capacity EGAT expansion plan, Nam Theun 2 is also a committed plant in EGAT’s generationPlanned Plant MW Commissiong Date 1/ scheduled for commercial operation in FY2010. Although the plant is included in the expansion candidate for purposes of totals reported in Table 11, NT2 is treated as an 1,307 1. EGAT Projects - Lam Takhong Pumped study. the economic analysis in this Storage 500 FY2004 - Krabi Thermal #1 300 FY2004 - Lan RetirementsKrabu GT for scheduled - Khanom CC the period FY2003-14 24 122 FY2004 12. We are summarized in Table 385 FY2007 hasten to add that this retirement schedule is a drastic oversimplification, reflecting mainly IPP “planned life� for each plant type.25 It 3,447 2. the Contracts 1/ is EGAT policy to assume fixed unit - planning - Unit 1 673 FY2007 lives forBLCP Power purposes. However, should units be performing well as they - BLCP Power - Unit 2 673 FY2007 approach their planned retirement date, a plant-specific study is undertaken to - Gulf Power 700 FY2008 - Union Power extending - Unit 1 determine whetherDevelopment the service life would be cost-effective, given any 700 FY2008 - investment for reconditioning. requiredUnion Power Development - Unit 2 700 FY2009 4. SPP Contracts 2/ 197 - Phase I Contracts 69 FY2003-05 - Phase II Contracts (Renewables) 128 FY2003-05 5. Nam Theun 2 Hydro 3/ 995 FY2010 24 As TOTAL 4/ in the following chapter, FY2003-14 is the 4,950 period for our analysis. explained planning 1/ Includes committed an exception, scheduled after March 2003 in FY2007 when a far The Khanom Thermal plant isplants with planned CODfor early retirement as reported 25 more efficient gas-fired combined cycle plant is expected to be available in the South. 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. System Supply Assumptions 28 Table 12. Schedule of Retirements (FY2003-14) Unit Capacity Planned Retirement Schedule Plant by Type No(s). MW Date(s) Age at retirement 1. Thermal 2,030 - South Bangkok 1-2 2x200 Sep-2006, 2007 36 3-5 3x310 Sep-2009, 2010, 2012 35 1/ - Khanom Thermal 1-2 2x75 Jan-07 26,18 2/ - Bang Pakong 1 550 Sep-13 30 1/ 2. Combined Cycle 760 - Bang Pakong 1-2 2x380 Sep-2007, 2008 25 3/ 3. Gas Turbine 140 - Lan Krabu various 140 depends on available gas 30+ TOTAL 4/ 2,790 1/ Under PDP 2003, these units are to be "repowered" (I.e., reconditioned for service as after this date). 2/ Early retirement due to availability of lower cost generation. 3/ Retired due to environmental emissions. 4/ Total excludes Lan Krabu EGAT has concluded that life extension is economically justified for thermal capacity at South Bangkok (units 3 through 5), and Bang Pakong;26 these reconditioned units are included in PDP 2003. The current study evaluates these four retiring thermal units as candidates for reconditioning (see Section 3.2). Only two retiring plants are not considered for reconditioning – Bank Pakong Combined Cycle (units 1 and 2) due to excess environmental emissions, and Khanom Thermal (units 1 and 2) in the South due to the availability of significantly lower cost energy. 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 to meet future capacity requirements. These are: (i) oil-fired steam thermal, (ii) coal-fired steam thermal, (iii) gas-fired combined cycle, and (iv) gas turbines. The study also considers reconditioning of a group of large thermal units scheduled for retirement during the study period (i.e., South Bangkok Thermal and Bang Pakong Thermal). All of these candidates are summarized in Table 13. The capital costs, lives, and operating cost assumptions for each candidate have been reviewed and approved by the World Bank based on both (i) discussions regarding EGAT’s recent experience, and (ii) the Bank’s own experience with large power projects in other countries. In particular, the Bank wished to have the study reflect evidence of a spread of US$200/kW between the cost of gas turbine (GT) and combined-cycle (CCGT) capacity to reflect EPC cost differences (including development cost margins). Hence, Bank-recommended values of US$310/kW for GT capacity and US$510/kW for CCGT capacity have been adopted. 26Parallel investigations by EGAT have concluded that life extension is not justified for South Bangkok units 1-2 or the combined cycle units at Bang Pakong. System Supply Assumptions 29 Table 13. Candidate Power Plants for the Study (2003 Prices) Capacity Capital Cost Life Heat Rate Fixed O&M Var. O&M FOR Maintenance Type MW US$/kW 1/ years Btu/kWh $/kW-yr $/MWh 2/ % weeks Oil-fired Thermal 700 792 30 8,870 19.56 0.597 6.0% 6 Coal-fired Thermal 3/ 700 1,100 30 9,560 24.49 0.983 7.0% 6 Combined Cycle 4/ 700 510 25 7,050 18.00 7.000 4.5% 3 Gas Turbine 5/ 230 310 15 11,000 10.46 4.200 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 -4 Thermal 19.0% 23.5% 34.5% 13.5% 9.5% Combined Cycle 23.0% 48.0% 29.0% Gas Turbine 41.6% 49.6% 8.8% 2/ Relatively higher VOM assumed for CCGT and GT, based on experience reported by IPP developers in the region. 3/ VOM includes limestone for FGD 4/ 2GT multi-shaft assumed 5/ 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. 3.3 Fuel Price Projections Fuel price forecasts for this study have been developed in cooperation with EGAT and the World Bank. In general, the Bank adopted EGAT’s assumptions for coal and lignite, 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 gas to be used in combined cycle gas turbines, since these are the most likely economic alternatives to NT2. The following discussion summarizes the methodology employed by the Bank in deriving natural gas prices. (Notwithstanding the unique characteristics of gas markets, other petroleum products have been valued in a similar manner.) A more comprehensive discussion of the analysis is presented 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 System Supply Assumptions 30  the estimated LRMC of gas transmission on a postage stamp basis. Although the World Bank does not have access to individual gas contracts, it is understood that the gas pricing structure, valid for the duration of the contract, is specified in Thai Baht, incorporating an indexation formula which adjusts the price over 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 CPI index and the exchange rate adjuster are offsetting in future price projections (based on purchasing power parity method of exchange rate projection). When working in US$ prices, therefore, the only non-offsetting element of the index is the HFO adjuster, 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 sales price, plus a postage-stamp pipeline toll. Moving from the commercial value of natural gas to an economic value further requires removal of all transfers – royalties and taxes – from the commercial price and the substitution of the commercial pipeline tolls with estimated incremental variable operating costs for pipeline transportation, insofar as the infrastructure is a sunk cost from an economic perspective. Finally, resulting nominal economic natural gas values are converted into real values by deflating the nominal series by the MUV index.27 Base Case fuel price projections adopted for this study are summarized in Table 14. High and Low scenario fuel price projections are reported in Appendix A3. It is possible that natural gas prices facing Thailand beyond 2014 could be higher than those projected up to 2014. Much depends on future demand, domestic discovery volumes and related costs and the longer-term costs of imported gas, the extent of such cost escalation being extremely difficult to project. Long-term values have low present value; nevertheless we have avoided projecting cost escalation over the very long term in order to minimize the risk of over-stating NT2's comparative worth. 27The MUV index is more formally identified as the United Nations’ Index of Unit Value of Manufactured Exports from the G-% industrial countries to developing country markets expressed in U.S. dollars. System Supply Assumptions 31 Table 14. Base Case Fuel Price Forecasts Real Economic Prices - Base Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 2.55 2.55 2.55 3.39 6.10 1.21 1.54 2004 2.56 2.65 2.55 4.48 8.68 1.20 2.33 2005 2.51 2.60 2.49 4.06 7.88 1.19 2.22 2006 2.41 2.50 2.40 3.58 6.93 1.17 2.00 2007 2.37 2.46 2.36 3.43 6.65 1.15 1.77 2008 2.33 2.42 2.32 3.28 6.37 1.14 1.66 2009 2.31 2.41 2.30 3.26 6.33 1.12 1.54 2010 2.30 2.39 2.29 3.25 6.29 1.11 1.54 2011 2.29 2.38 2.28 3.23 6.26 1.10 1.55 2012 2.28 2.37 2.27 3.24 6.28 1.08 1.56 2013 2.27 2.37 2.27 3.25 6.30 1.06 1.57 2014 2.27 2.36 2.27 3.26 6.32 1.05 1.58 Average Annual Growth (%) 2003-2014 -1.1% -0.7% -1.1% -0.4% 0.3% -1.3% 0.2% Nominal Commercial Prices - Base Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 2.95 2.95 2.95 3.56 8.54 1.21 1.56 2004 3.63 3.63 3.63 5.11 11.43 1.20 2.49 2005 3.48 3.48 3.48 4.57 10.46 1.20 2.34 2006 3.34 3.34 3.34 4.02 9.48 1.19 2.11 2007 3.32 3.30 3.32 3.89 9.25 1.19 1.89 2008 3.30 3.30 3.30 3.76 9.01 1.19 1.78 2009 3.32 3.34 3.32 3.77 9.02 1.18 1.67 2010 3.34 3.37 3.33 3.77 9.04 1.19 1.67 2011 3.36 3.38 3.34 3.78 9.05 1.19 1.69 2012 3.38 3.42 3.37 3.82 9.12 1.18 1.72 2013 3.40 3.46 3.39 3.86 9.20 1.18 1.74 2014 3.42 3.50 3.41 3.90 9.27 1.18 1.76 Average Annual Growth (%) 2003-2014 1.4% 1.6% 1.3% 0.8% 0.8% -0.2% 1.1% 3.4 Thermal Candidate Plant Screening Analysis The Study TOR requests a preliminary screening analysis based on real economic costs in order to confirm the expectation that natural gas-fired units are the primary alternatives to NT2. The analysis has been prepared for the candidate generating units summarized in Table 13, assuming the fuel price forecasts from Table 14. Each candidate has been evaluated 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 cost of one kWh from each source as a function of the rate of capacity utilization.28 Note that the long-term economic value of natural gas reported in Table 15 rises to US$3.65/mmbtu, considerably above the 2014 value of US$2.27/mmbtu reported in Table 14. This value represents the World Bank’s current view of the long-term 28Because plant capacities have already been adjusted for the effect of forced outages and maintenance, each effective kW can be used up to 100 percent of the time. System Supply Assumptions 32 economic price of natural gas in Thailand. It was derived after a long and careful review of current and prospective demand and supply conditions facing the Thai natural gas market. The US$3.65/mmbtu consists of US$3.50 for gas (whether imported LNG or piped gas from the region) and US$0.15/mmbtu for inland gas transmission, roughly equivalent to US$20/bbl crude oil. The screening curve uses these higher values to demonstrate that natural gas-fired capacity will remain the least-cost thermal option for base load operation even if a long-term “backstop� value of natural gas is assumed. Table 15 shows that gas turbines are the clear thermal choice for capacity utilization below 25 percent (i.e., peaking duty). Gas-fired combined cycle appears to be the clear choice for higher capacity utilization. Even at very high capacity factors, the cost of combined cycle is at or below the cost of coal-fired units. Oil appears to be non-competitive at the real fuel prices adopted for the current study. For purposes of the least-cost analysis presented elsewhere in this report, the long- term value of natural gas has been fixed at its 2014 level (see Table 14 and Appendix A3) in recognition of the uncertainty surrounding the extent and timing of dependence on more costly sources of natural gas in Thailand. 3.5 NT2 – The Alternative Expansion Candidate Contractually, in the EGAT-NTPC power purchase agreement (PPA), NT2 is treated as three separate transactions:  the first transaction is a firm power purchase of 4406 GWh per year (allocated to peak-period hours [6 a.m. to 10 p.m.] and according to expected monthly generation) at the Primary Energy Tariff (“PE�) specified in the contract;  the second transaction is a purchase of 948 GWh annually during off-peak hours at the Secondary Energy 1 Tariff (“SE1�) specified in the contract; this transaction is treated as non-firm so that PROSCREEN does not record a further increment to installed capacity; and  a third transaction (not required, but at the option of EGAT) is a purchase of an additional 282 GWh at the Secondary Energy 2 Tariff (“SE2�). System Supply Assumptions 33 Table 15. Screening Analysis of EGAT Candidate Plants OIL COAL COMB.CYC GT Economic Fuel Prices (Constant US$/mmbtu) Plant 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 4.48 2.33 2.56 Maintenance (wks) 6 6 3 2 3 4.06 2.22 2.51 Availability factor 0.83 0.82 0.90 0.87 4 3.58 2.00 2.41 Heat rate (Btu/kWh) 8,870 9,560 7,050 11,000 5 3.43 1.77 2.37 6 3.28 1.66 2.33 Cap.Cost ($/kW) 792 924 510 310 7 3.26 1.54 2.31 Expend.Profile (%) 8 3.25 1.54 2.30 -4 9.5% 9.5% 9 3.23 1.55 2.29 -3 13.5% 13.5% 10 3.24 1.56 2.28 -2 34.5% 34.5% 29.0% 6.8% 11 3.25 1.57 2.27 -1 23.5% 23.5% 48.0% 49.6% 12 3.26 1.58 2.27 0 19.0% 19.0% 23.0% 41.6% 13 3.26 1.58 2.26 Levelized Cap.Cost 104.39 121.79 65.35 44.62 14 3.26 1.58 3.65 Fixed O&M ($/kW-yr) 19.56 24.49 18.00 10.46 15 3.26 1.58 3.65 Variable O&M ($/kWh) 0.00060 0.00096 0.00700 0.00420 16 3.26 1.58 3.65 Levelized Fuel ($/kWh) 0.03083 0.01657 0.01883 0.03208 17 3.26 1.58 3.65 Fuel Price Sensitivity 1.00 1.00 1.00 1.00 18 3.26 1.58 3.65 Discount rate 10% 19 3.26 1.58 3.65 20 3.26 1.58 3.65 21 3.26 1.58 3.65 22 3.26 1.58 3.65 23 3.26 1.58 3.65 24 3.26 1.58 3.65 25 3.26 1.58 3.65 26 3.26 1.58 3.65 27 3.26 1.58 3.65 28 3.26 1.58 3.65 29 3.26 1.58 3.65 30 3.26 1.58 3.65 Levelized Cost of Generation Candidate Units ($/kWh) $0.15 $0.10 US$ per kWh $0.05 $0.00 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Ulilization of Effective kW Oil Coal Combined Cycle Gas Turbine System Supply Assumptions 34 For purposes of the current study, total planned generation is allocated by month based on a review of historical data (1953-99) provided by NTPC, as summarized in the following chart: NT2 GWh by Month (1953-99) PE SE1 SE2 Jan 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 For the economic [real resource] analysis presented in Chapter 5, Base Case investment and operating costs of the NT2 project are based on real cash flow data derived from the project lenders’ financial model, excluding transfers and sunk costs, but including incremental sponsor development costs that reflect use of real resources For the commercial evaluation at nominal market prices presented in Chapter 6, negotiated PPA payments per kWh purchased are taken as the project cost rather than actual developer cash flows, since NT2 generation is being purchased at that agreed price. Costs for associated transmission in Thailand and Laos are also included in each analysis. Even when these costs are not borne by the project sponsor (as is the case with associated transmission in Thailand), these investments represent real resource costs required to deliver NT2 energy from the powerhouse to end-users. Methodology for the Study 35 4 M ETHODOLOGY FOR THE S TUDY The primary focus of the current study is an economic analysis to determine whether the NT2 Project has a satisfactory economic cost-risk profile in the context of the regional power market. The main distinguishing characteristics of this second stage analysis are threefold:  all values reflect real economic resource costs (to the greatest extent feasible);  the scope of work includes both the Thai and Laotian electricity markets; and  the risk analysis consists of an integrated multi-event probabilistic framework that produces one overall quantitative result showing whether implementing the NT2 project in October 200929 would be an acceptable economic investment for the power sector. Section 4.1 introduces the least-cost generation expansion planning methodology adopted for this study. Section 4.2 describes the cost-risk framework used to determine the Study outcome. 4.1 The Least Cost Planning Methodology 4.1.1 The PROSCREEN II Model PROSCREEN II, the least-cost generation expansion planning model currently used by EGAT, has been adopted for use in this study.30 This model is widely used by utilities 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 and load shape) which define capacity requirements to maintain a specified level of system reliability; 29Sensitivity analysis evaluated alternative start-dates, and concluded that Oct-09 (i.e., the beginning of FY2010) is the least-cost. 30Indeed, without the full support of EGAT generation planners, this study would not have been possible. Methodology for the Study 36  assemble the necessary data on unit operating characteristics, fuel costs, sale and purchase arrangements for evaluation of alternative generation resource plans, and calculate the production cost and reliability associated with these plans; and  determine the least-cost plan for meeting system demand under a prescribed set of constraints by simulating the operation of the utility to determine the cost and reliability effects of alternative system resource additions. 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 by excluding transfer payments (taxes, duties, and subsidies). This policy is consistent with a gradual industry-wide trend away from traditional economic analysis as utilities move toward privatization and away from government subsidies and preferential treatment. As noted in Chapter 1, however, this study is a regional evaluation of expansion options using real resource costs, and therefore cost assumptions diverge from values currently assumed for EGAT planning.31 For the interested reader, a more complete explanation of how PROSCREEN works is presented in Appendix A5. 4.1.2 How PROSCREEN is Applied in this Study To 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 at negotiated 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 of monthly dependable generation;  Lao imports from Theun Hinboun and Huay Ho plants;  SPP contracts (and commitments), assuming a capacity factor of 80 percent. 31The World Bank has outlined detailed requirements in the TOR (see Appendix A1) regarding modeling approach, and specified a large number of input assumptions. Further, the Bank recognizes the unique perspective of a study based on real regional resource costs, and acknowledges that the methods and values used in this study for its purposes are completely without prejudice to different ones that EGAT may consider as more appropriate for its own operating context and requirements. Methodology for the Study 37 With the exception of EGAT’s own hydro capacity, each of these resources is modeled as a separate transaction, defined from contractual purchase price and operating constraints.  NT2 is treated as two transactions ("PE" and "SE1"; see Section 3.5) with an October 2009 starting date (FY2010) when it is included in the analysis.  Thermal resources, including both EGAT’s existing thermal capacity and available IPP capacity, are economically dispatched based on cost. IPPs are not required to run, but in general are dispatched, since they are relatively low-cost gas-fired units.32  Implicit in this modeling approach is the assumption (based on recent studies) that the Lao alternative to NT2 for meeting that portion of its demand in the CR-2 region would be import of thermal-fired electricity from Thailand.33 4.2 Cost-Risk Analysis Modeling Framework As specified in the TOR, the study outcome is to be determined by means of the results profile shown in Table 16 (the “Cost-Risk Framework�). This profile provides for calculating the probability-weighted present value (PV) costs of either implementing or not implementing NT2 for commercial operation in FY2010, 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 the suggested probabilities of occurrence for Base Case, Low and High estimates of these variables. The difference between the probability-weighted PV cost of implementing the project in FY2010 versus not implementing it at all is the decision criteria for this analysis. A lower net present value (NPV) “with NT2� indicates that the project is an acceptable economic investment for the regional power market. In addition to the real resource cost analysis outlined above, the study also includes a commercial assessment of the project under which the economic values are converted to commercial values and expressed in nominal US dollars, in order to assess the commercial sustainability of NT2 in the regional power market. This effort parallels the analytical framework shown in Table 16, although construction cost is not included as a cost-risk variable for the commercial evaluation because a power purchase agreement has already been negotiated and signed.34 32Thermal capacity at Krabi is dispatched without regard to cost, as transmission constraints necessitate its use for reliability in the South. 33Power System Development Plan for Lao PDR – Final Report, Maunsell Limited in association with Lahmeyer GmbH, August 2004. The study offers a strategic plan for the power sector for the period 2005-2020. 34Moreover, fixed-price construction contracts including contingencies have already been negotiated, and developer costs incpororate premiums for risk (see Section 5.1.3). Methodology for the Study 38 The specific steps undertaken to complete the cost-risk analysis are summarized in the following paragraphs: Table 16. The Cost-Risk Framework A. Present Values WITH NT2: CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 h 0.25 hhh 0.01563 h 0.25 h 0.25 m 0.50 hhm 0.03125 h 0.25 h 0.25 l 0.25 hhl 0.01563 h 0.25 m 0.50 h 0.25 hmh 0.03125 h 0.25 m 0.50 m 0.50 hmm 0.06250 h 0.25 m 0.50 l 0.25 hml 0.03125 h 0.25 l 0.25 h 0.25 hlh 0.01563 h 0.25 l 0.25 m 0.50 hlm 0.03125 h 0.25 l 0.25 l 0.25 hll 0.01563 m 0.50 h 0.25 h 0.25 mhh 0.03125 m 0.50 h 0.25 m 0.50 mhm 0.06250 m 0.50 h 0.25 l 0.25 mhl 0.03125 m 0.50 m 0.50 h 0.25 mmh 0.06250 m 0.50 m 0.50 m 0.50 mmm 0.12500 m 0.50 m 0.50 l 0.25 mml 0.06250 m 0.50 l 0.25 h 0.25 mlh 0.03125 m 0.50 l 0.25 m 0.50 mlm 0.06250 m 0.50 l 0.25 l 0.25 mll 0.03125 l 0.25 h 0.25 h 0.25 lhh 0.01563 l 0.25 h 0.25 m 0.50 lhm 0.03125 l 0.25 h 0.25 l 0.25 lhl 0.01563 l 0.25 m 0.50 h 0.25 lmh 0.03125 l 0.25 m 0.50 m 0.50 lmm 0.06250 l 0.25 m 0.50 l 0.25 lml 0.03125 l 0.25 l 0.25 h 0.25 llh 0.01563 l 0.25 l 0.25 m 0.50 llm 0.03125 l 0.25 l 0.25 l 0.25 lll 0.01563 A. Probability-weighted Present Value WITH NT2 #VALUE! 1.00000 B. Present Values WITHOUT NT2: POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 hh 0.06250 h 0.25 m 0.50 hm 0.12500 h 0.25 l 0.25 hl 0.06250 m 0.50 h 0.25 mh 0.12500 m 0.50 m 0.50 mm 0.25000 m 0.50 l 0.25 ml 0.12500 l 0.25 h 0.25 lh 0.06250 l 0.25 m 0.50 lm 0.12500 l 0.25 l 0.25 ll 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)  Determine Base Case, Low, and High real economic values for the three key uncertainties – (i) project cost, (ii) growth rate of electricity demand, and (iii) the economic value of natural gas – expected to have the most significant potential impact on the economic decision to develop NT2.  Define a probability of occurrence for each state (Base Case, Low, and High) of each variable. In fact, these probabilities are specified in the project TOR, and shown in Table 16. It should be noted that the probabilities were selected based on judgment – backed by World Bank Methodology for the Study 39 studies from other projects – about relationship between extent of variance and its probability of occurrence, as well as the presumption that the base case should have a higher probability of occurrence while High and Low values should have high-enough probabilities so that they have a measurable impact on cost-risk analysis results.  Run the PROSCREEN expansion planning model under Economic Base Case assumptions with NT2 as a candidate competing for a place in the least- cost expansion plan from its earliest expected commercial operation date of FY2010. This initial analysis added NT2 to the system in October 2009, i.e., it specified that the least-cost expansion plan included NT2 commencing operation in October 2009. This date was therefore fixed for all subsequent "with NT2" model runs to conform to the logic of the decision matrix (the decision being whether to develop NT2 for commercial operation in October 2009 or not to do so).35  Run the PROSCREEN expansion planning model with NT2 commencing commercial operation in October 2009 (FY2010) for all combinations of the above-defined uncertainties. The PROSCREEN “objective function� (i.e., basis for comparison of results) is the present value of future investment and operating costs over the Study Period. The expansion plan with the lowest NPV is the preferred alternative.  Re-run each of the defined scenarios without NT2 so that demand must be served from alternative resources.  Calculate the probability-weighted present value of costs for the “with NT2� and “without NT2� scenario groups.  Subtract the probability-weighted result “with NT2� from the result “without NT2� to determine the Study outcome.  Repeat the above analysis, converting all real economic values in the least- cost planning runs to nominal commercial values (i.e., using market prices including inflation). Whereas the economic assessment defines the project cost as the real resources utilized in constructing and operating NT2, the commercial assessment defines the project cost according to the commercial terms set forth in the power purchase agreement To complete the Cost-Risk Framework, a total of 18 scenario runs are required (9 “with NT2� and 9 “without NT2�), or 36 model runs to complete the framework from both the economic and commercial perspectives. These scenarios are formed from combinations of two planning 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 are expanded to 27 scenarios in the economic assessment by combining manually the three cases for the construction cost of NT2 with the results 35The sensitivity of results to a delay in commercial operation date was also evaluated, as reported in Chapter 5. Methodology for the Study 40 of the other scenarios. (High and low project cost is not evaluated in the commercial runs because the commercial arrangement is a fixed-price PPA.) For each scenario, the combined probability is simply the product of the probabilities of each of its components. For example, the probability of the “with NT2� Base Case or “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� scenario assuming all “high� outcomes (“hhh�) is 0.015625 (0.25 x 0.25 x 0.25). When all scenarios are considered, of course, the probabilities for the "with NT2" and "without NT2" scenario groups each sum to 1.00. A complete cost-risk analysis – requiring 18 PROSCREEN model runs by EGAT system planners – was prepared for the RELC/2004 study. Although the World Bank wished to update that economic analysis to incorporate current information (i.e., current perspectives on Thai fuel prices and the most recent data on NT2 capital cost) and to conduct a parallel commercial analysis of equivalent scope, it was considered unnecessary (and unreasonable!) to request twice the original support (i.e., 36 model runs, each requiring considerable set-up and run time) from the EGAT System Planning Division. It was therefore decided to focus the cost-risk analysis for the current study only on the downside risks to NT2. Specifically, the analysis was limited to the base case and those cases which could be expected to pose the greatest test to project viability, i.e., conditions of lower than expected demand, lower than expected fuel prices, and higher than anticipated NT2 capital costs. Chapters 5 and 6, which present these economic and commercial analyses, explain the specific Base Case, Low, and High values adopted for each variable in the cost-risk analyses. Economic Evaluation 41 5 E CONOMIC E VALUATION The objective of this chapter is to evaluate whether NT2 is a part of the least-cost generation expansion plan for meeting future regional electricity needs when it is evaluated using the real economic cost of the resources required. The cost-risk analytical framework outlined in Chapter 4 is applied to give a comprehensive, probabilistic answer to this question which systematically incorporates the range of uncertainties – construction costs, load growth, fuel prices – assumed in this study to face 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-risk analysis. Section 5.4 discusses the sensitivity of results to changes in specific variables. 5.1 Economic Planning Assumptions 5.1.1 Basic Economic Assumptions The World Bank has specified the following economic basis for the real resource analysis of NT2:  All costs exclude internal fiscal transfers (e.g. taxes, duties, and subsidies)  All values are expressed in constant US dollars of 200336  The discount rate is 10% real  The MUV index (a UN index of the unit value of manufactured exports from G-5 industrial countries to developing country markets, expressed in US dollars) is used as the price deflator to restate future year prices in real 2003 US dollars; the MUV index averages 0.7 percent per annum through 2015.  A fixed exchange rate of 40 Thai Baht per US dollar was used for planning purposes. 36RELC/2004 was conducted at 2003 prices. Given low inflation expectations, it was decided not to restate all PROSCREEN assumptions to 2004 prices; this adjustment would require substantial additional work for no difference of consequence in the results. Economic Evaluation 42 5.1.2 System Characteristics In general, system characteristics adopted for the current analysis follow EGAT’s Power Development Plan for 2003 (PDP2003) as published in April 2003. Characteristics common to both the Economic and Commercial runs of PROSCREEEN, as detailed in Chapter 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 and 300 GWh.  The reliability criterion is a reserve margin of 15 percent, EGAT’s current reserve criterion to assure system reliability.  The existing system corresponds to the summary in Table 10.  All “committed plants� as identified in Table 11 are presumed to commence commercial operation according to schedule.  The schedule for plant retirements follows the assumptions detailed in Table 12.  NT2 (995 MW) is added to the system in October 2009 (FY2010) in the “with NT2� scenarios.37  All other plants – including plants proposed for reconditioning and all generic expansion options (see Table 13) – are modeled as candidates which much compete for a place in the least cost economic plan. (Note that candidates for “reconditioning� – South Bangkok thermal (units 3-5) and Bang Pakong (unit 1) – are only permitted to enter the expansion plan in the year following scheduled retirement.)  Generation of existing plants and selected candidates is dispatched by PROSCREEN according to the following rules:  All non-thermal generation – notably domestic hydro plants and Lao imports – is dispatched first, without regard to cost. With the exception of EGAT’s own hydro capacity, each of these resources is modeled as a separate transaction, defined from contractual purchase price and operating constraints.  NT2 energy is dispatched in two parts according to the monthly variation reported previously in Chapter 3, one to provide peak- period energy and a second to provide off-peak energy. Optional off-peak generation is not assumed. 37 Project-associated transmission works in Laos are included in the project cost. Project-associated incremental transmission costs for Thailand do not presume any other future hydro exports from Laos to Thailand, due to the uncertainty of these exports. Economic Evaluation 43  All thermal generation – the majority of the entire system – is subject to economic dispatch, and run only when it is lowest cost. Exceptions are small power producers (SPPs), which are assumed to run at an 80 percent capacity factor.38 The cost of NT2 is evaluated differently in the Economic and Commercial analyses. The following section discusses the NT2 cost assumptions for the economic project assessment. 5.1.3 NT2 Planning Assumptions for the Economic Analysis As already noted, the Base Case economic analysis has been run in two modes – “with NT2� included in the expansion plan for commercial operation from October 2009 (FY2010), and “without NT2� in the plan.39 Base Case economic investment and operating costs of the NT2 project are based on real cash flow data derived from the lenders' financial model [version of December 2004], excluding transfers and sunk costs, but including incremental sponsor development costs that reflect use of real resources.40 The total capital cost of NT2 will be US$870 million, equivalent to a present value of US$600 million at 2003 prices. Associated transmission (including lines and substations, but excluding sunk costs) has a capital cost of US$135 million, equivalent to a present value of US$82 million. Table 17 summarizes the investment cost streams. Low and High estimates of construction costs for NT2 and associated transmission have been specified in the TOR to be ±30% of the expected construction cost used for the Base Case. These costs are reported at the bottom of Table 17. Operating costs for NT2 have likewise been derived from the project lenders’ financial model. The real annual cost of O&M is estimated as US$16.28 million per year. Both the investment and operating costs include substantial environmental and social costs to be borne by the project sponsors by agreement with GOL. 38This is a reasonable assumption given the high percentage of this output which is fossil fueled (predominantly by gas). 39As discussed in Section 4.2 above, the starting date was fixed based on a PROSCREEN run in which NT2, treated as a candidate, was added to the least cost plan in October 2009. FY2010 (Oct-09) is considered to be the earliest possible commercial operation date (COD); Section 5.3 reports the sensitivity of results to delayed starting dates. 40 For a commercial evaluation at market prices, negotiated PPA payments per kWh purchased are taken as the project cost rather than actual developer cash flows, since NT2 generation is being purchased at that agreed price. This valuation is also used for the commercial project assessment reported in the next chapter. Economic Evaluation 44 Table 17. Capital Costs of NT2 (constant US$2003, 10% discount rate) Discount NT2 Associated Transmission Total Fiscal Factor @ Cost PV of Cost Cost PV of Cost PV of Cost Year 10% USD million USD million USD million USD million USD million 2003 0.9535 2004 0.8668 73.0 63.28 1.4 1.2 2005 0.7880 161.0 126.9 6.3 5.0 2006 0.7164 206.5 147.9 6.1 4.4 2007 0.6512 208.7 135.9 28.8 18.8 2008 0.5920 126.8 75.1 69.2 41.0 2009 0.5382 94.5 50.8 15.6 8.4 2010 0.4893 - - 7.4 3.6 Base Case 870.4 599.9 135.0 82.4 682.3 High Case 130% 1,131.5 779.8 175.5 107.1 886.9 - increase 261.1 180.0 40.5 24.7 204.7 Low Case 70% 609.3 419.9 94.5 57.7 477.6 - decrease 261.1 180.0 40.5 24.7 204.7 The TOR requests that the Consultant determine whether there is any “systematic bias� in the estimated construction costs for NT2 (i.e., whether the Base Case estimated project cost reported here can be assumed to be the expected project cost). There is evidence that the Base Case project cost estimate is not systematically biased either positively or negatively:  As with planning for any large hydropower project, NT2 developer planning has included comprehensive activity scheduling to assure efficient project development at least cost. Moreover, NT2 project developers have relied on fixed-price bidding for key civil and electro-mechanical contracts. Faced with fixed prices, contract bidders necessarily undertake an evaluation of the risks they are undertaking. Further, these fixed-price contracts include both physical and price contingencies, further protecting the developer against a wide range of unforeseen cost overruns.  NT2 project developers have also employed sophisticated risk models to trace the linkages from randomly selected project activity delays, and their cumulative impact on the critical path to final project completion. In other words, complex models have been utilized to ascertain if randomly selected delays might cause subsequent delays that could not be mitigated so as to achieve targeted project deadlines. The Base Case project cost estimate includes a quantified estimate of the risk premium associated with such unanticipated delays. Thus, there is a risk “insurance� against unexpected cost overruns already incorporated into the Base Case cost estimates reported in Table 17. Economic Evaluation 45 5.2 Base Case Results Table 18 summarizes the results of the Base Case scenario “with NT2� included in the expansion plan from FY2010. (A detailed summary of these results is presented in Appendix A6.) A total of 15,706 MW are added to the system during the planning period. NT2, of course, accounts for 995 MW of new capacity, about 6 percent of the total. A further 4,792 MW represent capacity that is already committed (i.e., not competing for a place in the plan). All of the candidates selected to meet future load are gas- fired. Recommended additions include 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$26,628 million. After PROSCREEN calculates the end-effects of this expansion program in order to avoid any biases which might result from a short planning horizon, the estimated total PV of costs over the Study Period is US$46,603 million. Table 18. Base Case “with NT2� Fiscal Installed Committed Plant Planned Additions (including NT2) Reserve Year MW Addition Retirement CC GT Recondition Import Margin 2003 23,830 37.4% 2004 24,715 886 33.5% 2005 24,775 60 25.5% 2006 24,604 20 (191) 16.9% 2007 25,996 1,727 (335) 15.9% 2008 27,723 1,400 (373) 700 16.0% 2009 29,451 700 (373) 1,400 15.1% 2010 31,376 (310) 700 230 310 995 15.1% 2011 33,236 (310) 1,400 460 310 15.1% 2012 35,336 2,100 15.5% 2013 37,436 (310) 2,100 310 15.4% 2014 39,536 (550) 2,100 550 15.1% Total 39,536 4,792 (2,752) 10,500 690 1,480 995 Notes: CC - gas-fired combined cycle, GT - gas turbine. PRESENT VALUE OF COSTS (US$ million) With NT2 A. Planning Period (2003-2014) 26,628 B. End-Effects Period 19,976 C. Study Period (A + B) 46,603 Table 19 presents results of an expansion planning model run identical to the one specified for Table 18 except that NT2 is not included. The table shows the recommended expansion plan in the absence of the 995 MW from NT2. This case requires a total of 11,200 MW of combined cycle plant over the Planning Period, with 1,150 MW of gas turbine plant and the same reconditioning – a net increase of 1,160 MW. Economic Evaluation 46 Table 19. Base Case “without NT2� Fiscal Installed Committed Plant Planned Additions (excluding NT2) Reserve Year MW Addition Retirement CC GT Recondition Import Margin (%) 2003 23,830 37.4% 2004 24,715 886 33.5% 2005 24,775 60 25.5% 2006 24,604 20 (191) 16.9% 2007 25,996 1,727 (335) 15.9% 2008 27,723 1,400 (373) 700 16.0% 2009 29,451 700 (373) 1,400 15.1% 2010 31,551 (310) 2,100 310 15.7% 2011 33,411 (310) 1,400 460 310 15.7% 2012 35,271 1,400 460 15.3% 2013 37,371 (310) 2,100 310 15.2% 2014 39,701 (550) 2,100 230 550 15.6% Total 39,701 4,792 (2,752) 11,200 1,150 1,480 - Notes: CC - gas-fired combined cycle, GT - gas turbine. PRESENT VALUE OF COSTS (US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 26,628 26,724 B. End-Effects Period 19,976 20,145 C. Study Period (A + B) 46,603 46,869 PV of Savings with NT2 A. Planning Period (2003-2014) 97 B. End-Effects Period 169 C. Study Period (A + B) 266 % of total cost 0.57% Savings (Cost) Due to Selecting Nam Theun 2 Difference in Accumulated Present Value (US$ million) 240 200 160 US$ million 120 80 40 0 -40 2010 2015 2020 2025 2030 2035 with NT2 without NT2 The middle panel of Table 19 compares the PV of total costs required for each of the Base Case generation expansion plans, both “with� and “without� NT2. Assuming that all assumptions adopted for the Base Case analysis prove correct, the estimated Economic Evaluation 47 PV of total costs over the Study Period is US$46,603 million when NT2 is included in the plan, and US$46,869 million when NT2 is excluded. The graph at the bottom of Table 19 charts the annual cumulative benefits associated with the decision to proceed with NT2. Each point on the “without NT2� line represents the annual accumulated difference in costs over the “with NT2� case. (A positive difference indicates a real resource savings associated with developing NT2, while negative numbers would indicate a real resource cost.) The chart suggests that the decision to purchase NT2 power will produce a significant savings over the study horizon. The accumulated present value of savings to the region over the entire Study Period totals US$266 million at 2003 prices.41 While small in relation to the cost of the entire expansion plan, these savings are equivalent to almost 40 percent of the total economic cost of NT2 development. 5.3 Cost-Risk Analysis The Base Case tells us that NT2 should be included in the region’s least cost generation expansion plan assuming that the assumptions adopted for decision- making are correct. The objective of cost-risk analysis is to determine whether the same decision is justified given the high probability that future events will diverge from the Base Case assumptions. As specified by the World Bank, the study outcome is determined by means of the results profile shown in Table 1 (the “Cost-Risk Framework�). This profile provides for calculating the probability-weighted present value (PV) costs of either implementing or not implementing NT2 for commercial operation in FY2010, given the interplay of several major uncertain factors – project cost, long-term demand for electricity, and long-term economic value of natural gas as well as the suggested probabilities of occurrence for Base Case, Lower and Higher estimates of these variables. The difference between the probability weighted PV cost of implementing the project in FY2010 versus not implementing it at all is the decision criteria for this analysis. A lower net present value (NPV) “with NT2� would indicate that the project is an acceptable economic investment for the regional power market. The key decision variables for this study are defined in the study TOR (see Appendix A1). They are:  Capital cost of NT2. The World Bank has specified a cost range of +30 percent (High capital cost) and –30 percent (Low capital cost); these values are reported in Table 17.  Regional demand forecast. The World Bank has specified a very wide range in order to reflect accumulated international experience with load forecast 41The US$ 266 million represents a ‘savings� since the least-cost plan without NT2 would come at greater total cost. Economic Evaluation 48 accuracy over time; the regional High and Low demand forecasts are summarized in Table 10.  Natural gas price forecast.42 The World Bank has developed its own fuel price projections, with particular emphasis on the price of natural gas since it is the most competitive alternative fuel. The Base Case projections are presented in Table 15; High and Low scenarios are reported in Appendix A3.43 For each of these three key variables, the TOR specifies base case, low case and high case assumptions, as well as the probabilities of occurrence associated with each. Base case assumption values are assigned a 50 percent probability of occurrence, while the Low 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 represent all probable outcomes “with NT2�, and 9 possible scenarios to represent all possible outcomes “without NT2�. A complete cost-risk analysis – requiring 18 PROSCREEN model runs by EGAT system planners – was prepared for the RELC/2004 study. Although the World Bank wished to update that economic analysis to incorporate current information (i.e., current perspectives on Thai fuel prices and the most recent data on NT2 capital cost) and to conduct a parallel commercial analysis of equivalent scope, it was considered unnecessary (and unreasonable!) to request twice the original support (i.e., 36 model runs, each requiring two or more hours of set-up and run time) from the EGAT System Planning Division. It was therefore decided to focus the cost-risk analysis for the current study only on the downside risks to NT2. Specifically, the analysis was limited to the base case and those cases which could be expected to pose the greatest test to project viability, i.e., conditions of lower than expected demand, lower than expected fuel prices, and higher than anticipated NT2 capital costs. Section 5.3.1 reports the impact of these individual variables on the least-cost expansion plan. Section 5.3.2 then presents their collective impact in the resulting cost-risk analysis. 42 Since natural gas is the primary fuel alternative to NT2, this report uses the terms "natural gas price forecast" and "fuel price forecast" interchangeably; readers should be reminded that either term refers to the complete sets of fossil fuel forecasts (Base Case, High, and Low) presented in Appendix A3. 43The high and low variance is based one standard deviation around the WB's oil price forecast for that portion of the gas value determined by movement of international oil prices. Economic Evaluation 49 5.3.1 Sensitivity Analysis This section reports the sensitivity of the Base Case results to changes in the values of individual variables. As noted above, these sensitivities involve variables that can be expected to delineate the downside risk to the project:  Sensitivity to a lower demand forecast  Sensitivity to a lower forecast for natural gas and other fuels  Sensitivity to changes is NT2 capital cost Sensitivity to a Lower Demand Forecast The spread between the base and low demand forecasts adopted for this study is dramatic: By FY2012, the Low Case is only 75 percent of the Base Case. Not surprisingly, system expansion requirements are reduced as a result. Table 20 compares the expansion plans required under the two load forecasts. The table suggests that savings "with NT2" would be substantially reduced with lower-than-expected demand (US$24 million vs. US$266 in the Base Case). This result follows from the fact that new gas-fired generation is not required in the “with NT2� case, and not until FY2014 in the “without NT2� case. With lower demand, a non-NT2 scenario allows for slower accumulation of generation capacity than a scenario in which NT2 is committed for FY2009 regardless of the demand level. Sensitivity to Lower Natural Gas Prices Differences between high and low fuel price forecasts adopted for the study are not as dramatic as the spread noted for the demand forecast. This result is due to the fact that the value of natural gas in the Thai power market is only partially influenced by the oil price range. (The prices adopted for these sensitivity scenarios are reported in Appendix A3.) When scenarios are run with low fuel prices, gas remains the fuel of choice for incremental capacity both “with NT2� and "without NT2". As might be expected, the low gas price scenario results in lower total Study Period savings (US$226 million) than in the Base Case scenario (US$266 million). The difference can be attributed entirely to reduced gas prices, since capacity additions mirror the Base Case in both “with NT2� and “without NT2� cases. Table 21 compares the Base Case results with the expected savings from NT2 assuming lower fuel prices. Economic Evaluation 50 Table 20. Sensitivity of Results to Lower Demand LOW DEMAND SCENARIO Fiscal Installed Planned Additions (including NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 28,346 310 995 2011 28,346 310 2012 28,346 2013 28,346 310 2014 28,346 550 Total 28,359 - - 1,480 995 Fiscal Installed Planned Additions (excluding NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 27,351 310 2011 27,351 310 2012 27,351 2013 27,351 310 2014 28,281 700 230 550 Total 28,281 700 230 1,480 - Notes: CC - gas-fired combined cycle, GT - gas turbine. PRESENT VALUE OF COSTS Low Demand (US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 21,953 21,877 B. End-Effects Period 12,390 12,490 C. Study Period (A + B) 34,343 34,367 PV of Savings with NT2 A. Planning Period (2003-2014) (76) B. End-Effects Period 100 C. Study Period (A + B) 24 % of total cost 0.07% Savings (Cost) Due to Selecting Nam Theun 2 Difference in Accumulated Present Value (US$ million) 240 200 160 US$ million 120 80 40 0 -40 -80 2010 2015 2020 2025 2030 2035 with NT2 Economic Base Case Low Demand Economic Evaluation 51 Table 21. Sensitivity of Results to the Price of Natural Gas LOW GAS PRICE SCENARIO Fiscal Installed Planned Additions (including NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,376 700 230 310 995 2011 33,236 1,400 460 310 2012 35,336 2,100 2013 37,436 2,100 310 2014 39,536 2,100 550 Total 39,536 10,500 690 1,480 995 Fiscal Installed Planned Additions (excluding NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,551 2,100 310 2011 33,411 1,400 460 310 2012 35,271 1,400 460 2013 37,371 2,100 310 2014 39,701 2,100 230 550 Total 39,701 11,200 1,150 1,480 - Notes: CC - gas-fired combined cycle, GT - gas turbine. PRESENT VALUE OF COSTS Low Gas Price (US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 24,838 24,909 B. End-Effects Period 18,699 18,826 C. Study Period (A + B) 43,536 43,735 PV of Savings with NT2 A. Planning Period (2003-2014) 72 B. End-Effects Period 127 C. Study Period (A + B) 199 % of total cost 0.46% Savings (Cost) Due to Selecting Nam Theun 2 Difference in Accumulated Present Value (US$ million) 240 200 160 US$ million 120 80 40 0 -40 2010 2015 2020 2025 2030 2035 with NT2 Economic Base Case Low Gas Price Economic Evaluation 52 Sensitivity to Changes in NT2 Capital Cost Sensitivity analyses reflecting changes in the load forecast and in fuel prices require completely new runs of the PROSCREEN model for both the “with NT2� and “without NT2� cases, since modifying these parameters will impact the entire system expansion plan. Changes in the capital cost of NT2, however, only affect the cost of a single plant, so reliable estimates of the resulting impact on the least-cost system expansion plan can be 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 Low capital cost scenarios. (The required adjustments are summarized in Table 17.) Table 22 compares the Base Case results with the expected savings from NT2 assuming 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 net benefit to the regional economy (US$61 million). These higher costs, coupled with either low demand or low gas prices, would eliminate this real net benefit. Table 22. Sensitivity to Changes in NT2 Capital Cost PRESENT VALUE OF COSTS With NT2 Without NT2 (US$ million) BASE CASE LOW HIGH A. Planning Period (2003-2014) 26,628 26,628 26,628 26,724 B. End-Effects Period 19,976 19,771 20,181 20,145 C. Study Period (A + B) 46,603 46,399 46,808 46,869 PV of Savings with NT2 A. Planning Period (2003-2014) 97 97 97 B. End-Effects Period 169 374 (36) C. Study Period (A + B) 266 471 61 % of total cost 0.57% 1.01% 0.13% Note: NT2 capital cost adjustments for the high and low cases has been allocated entirely to the End-Effects Period; PROSCREEN would allocate these adjustments to the Planning Period as well. 5.3.2 Cost-Risk Analysis Results The results of the economic cost-risk analysis are summarized in Table 23. As previously noted, the framework is incomplete, since High demand and High gas price scenarios have not been prepared. The review of downside risks represents only 56 percent of a complete cost-risk assessment. However, it must be noted that the scenarios excluded would be expected to record greater net benefits “with NT2� than the reported cases. For example, either higher demand or higher fuel costs would provide greater net benefits than the Base Case.44 44 This conclusion is both logical and confirmed by the results for these cases in RELC/2004. Economic Evaluation 53 Table 23. Economic Cost Risk Analysis Results A. Present Values WITH NT2: CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Savings by Case Probability Case Probability Case Probability Case Present Value Probability Scenario h 0.25 h 0.25 h 0.25 hhh - - h 0.25 h 0.25 m 0.50 hhm - - h 0.25 h 0.25 l 0.25 hhl - - h 0.25 m 0.50 h 0.25 hmh - - h 0.25 m 0.50 m 0.50 hmm 46,808 0.06250 61 h 0.25 m 0.50 l 0.25 hml 43,741 0.03125 (6) h 0.25 l 0.25 h 0.25 hlh - - h 0.25 l 0.25 m 0.50 hlm 34,548 0.03125 (181) h 0.25 l 0.25 l 0.25 hll 32,214 0.01563 (259) m 0.50 h 0.25 h 0.25 mhh - - m 0.50 h 0.25 m 0.50 mhm - - m 0.50 h 0.25 l 0.25 mhl - - m 0.50 m 0.50 h 0.25 mmh - - m 0.50 m 0.50 m 0.50 mmm 46,603 0.12500 266 m 0.50 m 0.50 l 0.25 mml 43,536 0.06250 199 m 0.50 l 0.25 h 0.25 mlh - - m 0.50 l 0.25 m 0.50 mlm 34,343 0.06250 24 m 0.50 l 0.25 l 0.25 mll 32,009 0.03125 (54) l 0.25 h 0.25 h 0.25 lhh - - l 0.25 h 0.25 m 0.50 lhm - - l 0.25 h 0.25 l 0.25 lhl - - l 0.25 m 0.50 h 0.25 lmh - - l 0.25 m 0.50 m 0.50 lmm 46,399 0.06250 471 l 0.25 m 0.50 l 0.25 lml 43,331 0.03125 404 l 0.25 l 0.25 h 0.25 llh - - l 0.25 l 0.25 m 0.50 llm 34,138 0.03125 228 l 0.25 l 0.25 l 0.25 lll 31,804 0.01563 151 A. Probability-weighted Present Value WITH NT2 41,576 0.56250 B. Present Values WITHOUT NT2: POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 hh - h 0.25 m 0.50 hm - h 0.25 l 0.25 hl - m 0.50 h 0.25 mh - m 0.50 m 0.50 mm 46,869 0.25000 m 0.50 l 0.25 ml 43,735 0.12500 l 0.25 h 0.25 lh - l 0.25 m 0.50 lm 34,367 0.12500 l 0.25 l 0.25 ll 31,955 0.06250 B. Probability-weighted Present Value WITHOUT NT2 41,737 0.56250 Probability-weighted PV Savings (Cost) WITH NT2 162 (Result A minus Result B; 2003 USD million) Taking all evaluated potential outcomes into account, a system expansion plan featuring the commissioning of NT2 in October 2009 is the correct decision from an economic least-cost perspective. Even when only downside risks are evaluated, the probability-weighted PV of total savings over the entire Study Period is estimated to be US$162 million, equivalent to US$0.006 per kWh sold from the NT2 project. A review of the cost-risk matrix indicates that NT2 capital cost is the variable having the greatest impact on results. High capital costs decrease the savings by US$205 million when other variables are held constant (i.e., from US$266 to US$ 61 million), while Low capital costs increase savings by US$205 million. Low demand reduces savings by substantially, to US$24 million. Despite the symmetry of input assumptions, results for a High demand case would not be symmetrical Economic Evaluation 54 around the Base Case. Since NT2 is fully utilized in the Base Case, there is limited opportunity for increased benefits due to an increase in system load. A Low natural gas price reduces total savings by US$67 million, although the net benefit “with NT2� is still significant (US$199 million). Only combinations of adverse future conditions from the perspective of NT2 (high capital costs, low demand and/or low gas prices) produce unfavorable results. Collectively, these events have a relatively low probability of occurrence. Reaching a conclusion based on an incomplete cost-risk results matrix may be a cause for concern given even a low probability of negative outcomes. That concern is mitigated in the case of this analysis by the fact that the omitted scenarios contain assumptions that favor the NT2 project. Nevertheless, for sake of completeness, we have completed the entire cost-risk framework based on the very conservative assumption that every “High� demand or gas price scenario will achieve savings identical to its closest “Medium� counterpart scenario (e.g., the “High demand, High gas price� scenario is assigned the savings of the “Medium demand, Medium gas price� scenario) even though we know, both intuitively and from our modeling for RELC/2004, that these scenarios would be expected to produce additional savings. This approach is mathematically equivalent to assigning a 75 percent probability to the “Medium� results and a “zero� percent probability to future events would prove advantageous to NT2 (i.e., construction cost at the low cost estimate, demand at the high load forecast, and natural gas price at the high fuel price forecast). Results of this cost-risk sensitivity test are reported in Table 24. The risk-adjusted real resource savings “with NT2� are estimated to be US$188 million. These results confirm our Base Case conclusion that NT2 is a viable investment project from an economic perspective, and suggest that the net benefits accruing from the inclusion of NT2 in the least-cost plan appear to be relatively robust even after consideration of downside risks to the project. Economic Evaluation 55 Table 24. Economic Cost-Risk Sensitivity Test A. Present Values WITH NT2: CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Savings by Case Probability Case Probability Case Probability Case Present Value Probability Scenario h 0.25 h 0.25 h 0.25 hhh 46,808 0.01563 61 h 0.25 h 0.25 m 0.50 hhm 46,808 0.03125 61 h 0.25 h 0.25 l 0.25 hhl 43,741 0.01563 (6) h 0.25 m 0.50 h 0.25 hmh 46,808 0.03125 61 h 0.25 m 0.50 m 0.50 hmm 46,808 0.06250 61 h 0.25 m 0.50 l 0.25 hml 43,741 0.03125 (6) h 0.25 l 0.25 h 0.25 hlh 34,548 0.01563 (181) h 0.25 l 0.25 m 0.50 hlm 34,548 0.03125 (181) h 0.25 l 0.25 l 0.25 hll 32,214 0.01563 (259) m 0.50 h 0.25 h 0.25 mhh 46,603 0.03125 266 m 0.50 h 0.25 m 0.50 mhm 46,603 0.06250 266 m 0.50 h 0.25 l 0.25 mhl 43,536 0.03125 199 m 0.50 m 0.50 h 0.25 mmh 46,603 0.06250 266 m 0.50 m 0.50 m 0.50 mmm 46,603 0.12500 266 m 0.50 m 0.50 l 0.25 mml 43,536 0.06250 199 m 0.50 l 0.25 h 0.25 mlh 34,343 0.03125 24 m 0.50 l 0.25 m 0.50 mlm 34,343 0.06250 24 m 0.50 l 0.25 l 0.25 mll 32,009 0.03125 (54) l 0.25 h 0.25 h 0.25 lhh 46,399 0.01563 471 l 0.25 h 0.25 m 0.50 lhm 46,399 0.03125 471 l 0.25 h 0.25 l 0.25 lhl 43,331 0.01563 404 l 0.25 m 0.50 h 0.25 lmh 46,399 0.03125 471 l 0.25 m 0.50 m 0.50 lmm 46,399 0.06250 471 l 0.25 m 0.50 l 0.25 lml 43,331 0.03125 404 l 0.25 l 0.25 h 0.25 llh 34,138 0.01563 228 l 0.25 l 0.25 m 0.50 llm 34,138 0.03125 228 l 0.25 l 0.25 l 0.25 lll 31,804 0.01563 151 A. Probability-weighted Present Value WITH NT2 42,817 1.00000 B. Present Values WITHOUT NT2: POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 hh 46,869 0.06250 h 0.25 m 0.50 hm 46,869 0.12500 h 0.25 l 0.25 hl 43,735 0.06250 m 0.50 h 0.25 mh 46,869 0.12500 m 0.50 m 0.50 mm 46,869 0.25000 m 0.50 l 0.25 ml 43,735 0.12500 l 0.25 h 0.25 lh 34,367 0.06250 l 0.25 m 0.50 lm 34,367 0.12500 l 0.25 l 0.25 ll 31,955 0.06250 B. Probability-weighted Present Value WITHOUT NT2 43,005 1.00000 Probability-weighted PV Savings (Cost) WITH NT2 188 (Result A minus Result B; 2003 USD million) Commercial Assessment 57 6 C OMMERCIAL A SSESSMENT The objective of this chapter is to evaluate whether NT2 is part of the region’s least- cost generation expansion plan for meeting the future electricity needs when this plan is evaluated at nominal market prices (versus the real resource costs discussed in Chapter 5). The cost-risk analytical framework outlined in Chapter 4 is applied to give a single answer that incorporates uncertainties associated with future load growth and fuel prices. Section 6.1 summarizes the basic assumptions adopted for system expansion planning at nominal market prices. Section 6.2 presents Base Case results, and Section 6.3 reports the results of the commercial cost-risk analysis. 6.1 Commercial Planning Assumptions 6.1.1 Basic Commercial Assumptions The World Bank has specified the following basis for the commercial analysis of NT2:  All costs represent market prices; as such they include internal fiscal transfers (e.g. taxes, duties, and subsidies)  All values are expressed in nominal (i.e., current year) US dollars  The discount rate is 10.45% nominal, the estimated weighted average cost of capital.  The MUV Index (a UN index of the unit value of manufactured exports from G-5 industrial countries to developing country markets, expressed in US dollars) is used as the price inflator to restate any constant US dollar costs or revenues into their future year nominal equivalents; the MUV index averages 0.7 percent per annum through 2015.  An exchange rate of 40 Thai Baht per US dollar was used for planning purposes. 6.1.2 System Characteristics As previously noted in the economic analysis of Chapter 5, system characteristics adopted for the current study follow EGAT’s Power Development Plan for 2003 (PDP2003) as published in April 2003. Characteristics common to both the Commercial Assessment 58 Economic and Commercial runs of PROSCREEEN, as detailed in Chapter 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 and 300 GWh.  The reliability criterion is a reserve margin of 15 percent, EGAT’s current reserve criterion to assure system reliability.  The existing system corresponds to the summary in Table 10.  All “committed plants� as identified in Table 11 are presumed to commence commercial operation according to schedule.  The schedule for plant retirements follows the assumptions detailed in Table 12.  NT2 (995 MW) added to the system in October 2009 (FY2010) in the “with NT2� scenarios.  All other plants – including plants proposed for reconditioning and all generic expansion options (see Table 13) – are modeled as candidates which much compete for a place in the least cost economic plan. (Note that candidates for “reconditioning� – South Bangkok thermal (units 3-5) and Bang Pakong (unit 1) – are only permitted to enter the expansion plan in the year following scheduled retirement.)  Generation of existing plants and selected candidates is dispatched by PROSCREEN according to the following rules:  All non-thermal generation – notably domestic hydro plants and Lao imports – is dispatched first, without regard to cost. With the exception of EGAT’s own hydro capacity, each of these resources is modeled as a separate transaction, defined from contractual purchase price and operating constraints.  NT2 energy is dispatched as two transactions, one to provide peak- period energy at the Primary Energy tariff (“PE�), and a second to provide off-peak energy at the Secondary Energy tariff (“SE1�). Optional off-peak generation is not assumed.  All thermal generation – the majority of the entire system – is subject to economic dispatch, and run only when it is lowest cost. Exceptions are small power producers (SPPs), which are assumed to run at an 80 percent capacity factor.45 45This is a reasonable assumption given the high percentage of this output which is fossil fueled (predominantly by gas). Commercial Assessment 59 6.1.3 The Cost of NT2 The cost of NT2 is evaluated differently in the Economic and Commercial analyses. In the commercial analysis, NT2 is modeled as a power purchase based on the actual PPA tariff over a 25-year period. The 995 MW plant is available from FY2010 (October 2009). The power purchase tariff for each tariff period is set by contract at a specific annual value. There is no escalation formula; rather, the starting tariff is escalated by a fixed annual factor of approximately 1.038 percent in order to achieve the negotiated levelized tariff over the life of the project. Rates have a Thai Baht component; for our analysis these have been re-stated in dollar-terms at the study exchange rate (40 THB/US$). Actual tariffs are not reported here for the sake of confidentiality.46 Additionally, the cost of each kWh is increased by US$0.00615, the estimated levelized cost of incremental transmission investments required to deliver all planned Lao hydro purchases from the Thai border to the nearest 500 kV line (for transmission to the Bangkok metropolitan area).47 The commercial analysis in PROSCREEN requires additional assumptions, as explained in the following section. 6.1.4 Private Sector Commercial View Our commercial analysis at nominal prices must reflect market-based financial conditions. The majority of national generating capacity is already privatized, and it is presumed that all future capacity will be developed by the private sector. The appropriate planning criteria for commercial decision-making is a weighted average cost of capital, discount rate, and levelized fixed charge rates which reflect the costs of private developers who will be competing for these projects. Were candidates defined based on a lower cost of capital they would likely appear less expensive in comparison with projects developed by the private sector, such as NT2 and committed IPPs. For this study, the weighted average cost of capital (WACC) has been calculated as follows: Component Share Rate (%) Weight Debt (before tax) 0.70 8.5% 6.0% Equity 0.30 15.0% 4.5% 10.45% 46Confidentiality is an issue of some importance to this Study; power purchase tariffs of negotiated IPPs have been withheld from the Consultant as per contractual agreement with developers regarding confidentiality. We understand and respect this concern. 47 As clarified by EGAT transmission planners, the levelized cost is based on transmitting 3,300 MW from agreed border crossing points to Tha Tako (near Nakhorn Sawan), the closest 500 kV connection point. Specifically three 500kV double-circuit lines are included: (i) Tha Tako – Chayaphum, (ii) Chayaphum – Udorn – Nong Khai, and (iii) Chayaphum – Roi Et – Mukdahan. Planned additional reinforcement investments are excluded from the calculations. Commercial Assessment 60  Debt and equity shares (70:30) are a compromise. Our discussions with investment bankers indicate that most large power projects will be financed on project basis (i.e., with no recourse to the developer), and hence not highly leveraged (e.g., 1.5:1). However, once up and running for several years, it is not uncommon for these projects to be refinanced at higher leverage (e.g., 2.5 or 3:1)  The cost of debt before tax is assumed (rather than the more commonly encountered tax shield adjustment in the WACC formula) upon the specific recommendation of the authors of PROSCREEN.48  The assumed cost of debt (8.5 percent) is higher than some readers might expect for two reasons. First, this is a rate for long-term analysis, and so it should reflect more than current short-term borrowing rates. Second, rates typically quoted in the market are variable rates which can fluctuate with market conditions (e.g., LIBOR+X); a power project must typically “swap� (at a cost!) into a fixed rate to assure predictable cash flow.  Equity returns are in the range 16–18 percent before tax according to investment bankers. We have picked the middle of the scale, i.e., 15 percent after tax. Further, we have adopted the above WACC (10.45 percent) as the discount rate for the analysis. Finally, we have calculated the levelized fixed charge rate for candidate additions as recommended by the authors of PROSCREEN: LEVELIZED FIXED CHARGE RATE by project life Gas Combined Coal / Oil Turbine Cycle Thermal life (yrs): 15 25 30 WACC ) 1/ 0.1045 0.1045 0.1045 + Sink.Fund Depreciation ) 0.0304 0.0095 0.0056 + Levelized Income Tax 2/ 0.0169 0.0186 0.0196 + Other Taxes 3/ 0.0050 0.0050 0.0050 = 0.1568 0.1376 0.1347 1/ Sum of these two items is equal to the capital recovery factor. 2/ Levelized tax calculated as recommended by PROSCREEN: = (Cap Recovery Factor - Applicable Depreciation) x (1 - debt share x debt cost / WACC) x (tax rate / (1 - tax rate)) assuming a 35 percent tax rate 3/ A notional amount to reflect additional costs such as property and other taxes, insurance, etc. 48It is unclear whether this recommendation is due to uncertainty regarding the tax benefit, or whether it is accounted for internally within the model. Commercial Assessment 61 6.2 Commercial Base Case Results The economic analysis presented in Chapter 5 concludes that NT2 – when analyzed from the perspective of real resource costs – will generate substantial savings to the region – on the order of US$266 million. The objective of the commercial risk analysis is to determine the project's commercial sustainability after transfer payments imposed on the project beyond the real resource costs are also considered. Examples of these transfers include taxes, duties, and royalties. Commercial costs also include developer sunk costs at the time of analysis. Further, the analysis is based on commercial terms of capital recovery at current prices. Table 25 summarizes the results of the Commercial Base Case scenario with NT2 included in the expansion plan from FY2010. A total of 15,706 MW are added to the system during the planning period. In addition to NT2 (995 MW), this total includes 4,792 MW of committed capacity, (i.e., not competing for a place in the plan). All of the candidates selected to meet future load are gas-fired. Recommended additions include 10,500 MW of combined cycle plant, 690 MW of gas turbines, and 1,480 MW of reconditioned thermal plants – the same program recommended in the economic Base Case analysis. The PV of total cost over the Study Period is US$61,939 million when NT2 is included in the expansion plan. Table 25 also presents results of a planning model run in which NT2 is not included in the plan. This case requires two more combined cycle units (1400 MW) in FY2010, but one less in FY2012; it also requires additional gas turbine units FY2011 and FY2014. The estimated PV of total costs over the Study Period is US$62,166. In summary, the Base Case commercial analysis suggests that the decision to purchase NT2 power will have a net benefit on the order of US$227 million. This result indicates that the large real resource benefits accruing to the region from development of NT2 in the economic analysis is slightly reduced when the above- noted transfer payments associated with the project are treated as project costs. Under Base Case commercial assumptions, however, the project remains viable from a purely commercial perspective. The economic analysis indicates that NT2 has a clear benefit to the region. The Base Case commercial result confirms this conclusion. Commercial Assessment 62 Table 25. Commercial Base Case Fiscal Installed Committed Plant Planned Additions (including NT2) Reserve Year MW Addition Retirement CC GT Recondition Import Margin 2003 23,830 37.4% 2004 24,715 886 33.5% 2005 24,775 60 25.5% 2006 24,604 20 (191) 16.9% 2007 25,996 1,727 (335) 15.9% 2008 27,723 1,400 (373) 700 16.0% 2009 29,451 700 (373) 1,400 15.1% 2010 31,376 (310) 700 230 310 995 15.1% 2011 33,236 (310) 1,400 460 310 15.1% 2012 35,336 2,100 15.5% 2013 37,436 (310) 2,100 310 15.4% 2014 39,536 (550) 2,100 550 15.1% Total 39,536 4,792 (2,752) 10,500 690 1,480 995 Fiscal Installed Committed Plant Planned Additions (excluding NT2) Reserve Year MW Addition Retirement CC GT Recondition Import Margin (%) 2003 23,830 37.4% 2004 24,715 886 33.5% 2005 24,775 60 25.5% 2006 24,604 20 (191) 16.9% 2007 25,996 1,727 (335) 15.9% 2008 27,723 1,400 (373) 700 16.0% 2009 29,451 700 (373) 1,400 15.1% 2010 31,551 (310) 2,100 310 15.7% 2011 33,411 (310) 1,400 460 310 15.7% 2012 35,271 1,400 460 15.3% 2013 37,371 (310) 2,100 310 15.2% 2014 39,701 (550) 2,100 230 550 15.6% Total 39,701 4,792 (2,752) 11,200 1,150 1,480 - Notes: CC - gas-fired combined cycle, GT - gas turbine. PRESENT VALUE OF COSTS (US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 33,740 33,829 B. End-Effects Period 28,199 28,337 C. Study Period (A + B) 61,939 62,166 PV of Savings with NT2 A. Planning Period (2003-2014) 89 B. End-Effects Period 138 C. Study Period (A + B) 227 % of total cost 0.37% Savings (Cost) Due to Selecting Nam Theun 2 Difference in Accumulated Present Value (US$ million) 240 200 160 US$ million 120 80 40 0 -40 2010 2015 2020 2025 2030 2035 with NT2 without NT2 Commercial Assessment 63 6.3 Cost-Risk Analysis As specified in the TOR, the study outcome is determined by means of the results profile shown in Table 16 (the “Cost-Risk Framework�) according to the methodology described in Section 4.2. The results of the economic cost-risk analysis based on real resource costs are presented in Section 5.3, and summarized in Table 23. A cost-risk analysis has also been prepared as part of the commercial evaluation. The framework is identical to that shown in Table 16, and the objective remains the same – to determine whether the same decision is justified if future events diverge from the Base Case assumptions. The commercial cost-risk analysis considers only two key decision variables – the demand forecast and the price of natural gas – since the commercial value reflecting NT2 cost has been fixed through a firm power purchase agreement.  The demand forecast for the Base Case, High and Low scenarios is described in Section 2; it is the same forecast applied for the economic assessment.  As discussed in Section 3.3, the World Bank has developed its own fuel price projections, with particular emphasis on the price of natural gas since it is the most competitive alternative fuel. The Base Case commercial projections are presented in Table 14; High and Low scenarios are reported in Appendix A3. The TOR specifies the probability of each assumption value. Each “expected� (i.e., Base Case) assumption has a probability of 50 percent in the cost-risk matrix, with the High and Low assumptions assigned a probability of 25 percent each. (As noted earlier, a combination of experience, judgment and – when available – historical evidence went into the selection of these probabilities.) For reasons noted in Section 5.3, it was not possible to prepare separate PROSCREEN models for all possible scenarios in the cost-risk framework. It was therefore decided to focus the cost-risk analysis for the current study only on the downside risks to NT2. Specifically, the analysis was limited to the base case and those cases which could be expected to pose the greatest test to project viability, i.e., conditions of lower than expected demand, lower than expected fuel prices. Section 6.3.1 reports the impact of these individual variables on the least-cost expansion plan. Section 6.3.2 then presents their collective impact in the resulting commercial cost-risk analysis. 6.3.1 Sensitivity Analysis This section reports the sensitivity of the Base Case results to changes in the values of individual variables. As noted above, these sensitivities involve variables that can be expected to delineate the downside risk to the project: Commercial Assessment 64  Sensitivity to a lower demand forecast  Sensitivity to a lower forecast for natural gas and other fuels Sensitivity to a Lower Demand Forecast The spread between the base and low demand forecasts adopted for this study is dramatic: By FY2012, the Low Case is only 75 percent of the Base Case. Not surprisingly, system expansion requirements are reduced as a result. Table 26 summarizes the expansion plans required under the Low load forecast, and the graph compares this result with the Base Case results reported in Table 25. Table 26 suggests that lower-than-expected demand “with NT2� would come at a cost (US$32 million vs. US$266 savings in the Base Case) equal to about 3 percent of the total stream of PPA payments for NT2 power over twenty-five years. This result follows from the fact that new gas-fired generation is not required in the “without NT2� case until FY2014. With perfect knowledge confirming dramatically lower- than-expected demand for electricity in the region, NT2 could be delayed beyond its scheduled FY2010 COD. Sensitivity to Lower Natural Gas Prices Differences between high and low fuel price forecasts adopted for the study are not as dramatic as the spread noted for the demand forecast. (The prices adopted for these sensitivity scenarios are reported in Appendix A3.) Although natural gas prices have recently reached historical levels, long-term forecasts do not presume that this trend will continue unabated. In Thailand, the price of gas is closely linked to the demand for electricity, as the power sector accounts for over 70 percent of total natural gas demand. With low demand, supplies of domestic gas will be more than sufficient to meet domestic requirements at least over the planning period. When scenarios are run with low fuel prices, gas remains the fuel of choice for incremental capacity both “with NT2� and "without NT2". Details of the Low natural gas price scenarios are presented in Table 27. Under the assumption of low gas prices, the decision to develop NT2 results in a PV savings of US$161 million, about 30 percent less than the Base Case result (US$227 million). Savings can be attributed directly to fuel costs, since expansion plans for the low gas price sensitivity are identical to the Base Case. Commercial Assessment 65 Table 26. Sensitivity of Results to Lower Demand LOW DEMAND SCENARIO Fiscal Installed Planned Additions (including NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 28,346 310 995 2011 28,346 310 2012 28,346 2013 28,346 310 2014 28,346 550 Total 28,346 - - 1,480 995 Fiscal Installed Planned Additions (excluding NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 27,351 310 2011 27,351 310 2012 27,351 2013 27,351 310 2014 28,281 700 230 550 Total 28,281 700 230 1,480 - Notes: CC - gas-fired combined cycle, GT - gas turbine. PRESENT VALUE OF COSTS Low Demand (US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 26,723 26,612 B. End-Effects Period 17,163 17,242 C. Study Period (A + B) 43,886 43,854 PV of Savings with NT2 A. Planning Period (2003-2014) (112) B. End-Effects Period 80 C. Study Period (A + B) (32) % of total cost -0.07% Savings (Cost) Due to Selecting Nam Theun 2 Difference in Accumulated Present Value (US$ million) 240 200 160 120 US$ million 80 40 0 -40 -80 -120 2010 2015 2020 2025 2030 2035 with NT2 Commercial Base Case Low Demand Commercial Assessment 66 Table 27. Sensitivity of Results to Lower Natural Gas Prices LOW GAS PRICE SCENARIO Fiscal Installed Planned Additions (including NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,376 700 230 310 995 2011 33,236 1,400 460 310 2012 35,336 2,100 2013 37,436 2,100 310 2014 39,536 2,100 550 Total 37,495 10,500 690 1,480 995 Fiscal Installed Planned Additions (excluding NT2) Year MW CC GT Recondition Import 2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,551 2,100 310 2011 33,411 1,400 460 310 2012 35,271 1,400 460 2013 37,371 2,100 310 2014 39,701 2,100 230 550 Total 39,701 11,200 1,150 1,480 - Notes: CC - gas-fired combined cycle, GT - gas turbine. PRESENT VALUE OF COSTS Low Gas Price (US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 32,036 32,104 B. End-Effects Period 26,864 26,956 C. Study Period (A + B) 58,900 59,060 PV of Savings with NT2 A. Planning Period (2003-2014) 68 B. End-Effects Period 93 C. Study Period (A + B) 161 % of total cost 0.27% Savings (Cost) Due to Selecting Nam Theun 2 Difference in Accumulated Present Value (US$ million) 240 200 160 US$ million 120 80 40 0 -40 2010 2015 2020 2025 2030 2035 with NT2 Commercial Base Case Low Gas Price Commercial Assessment 67 Table 28. Commercial Cost-Risk Analysis A. Present Values WITH NT2: CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Savings by Case Probability Case Probability Case Probability Case Present Value Probability Scenario m 1.00 h 0.25 h 0.25 mhh - - m 1.00 h 0.25 m 0.50 mhm - - m 1.00 h 0.25 l 0.25 mhl - - m 1.00 m 0.50 h 0.25 mmh - - m 1.00 m 0.50 m 0.50 mmm 61,939 0.25000 227 m 1.00 m 0.50 l 0.25 mml 58,900 0.12500 161 m 1.00 l 0.25 h 0.25 mlh - - m 1.00 l 0.25 m 0.50 mlm 43,886 0.12500 (32) m 1.00 l 0.25 l 0.25 mll 41,529 0.06250 (109) A. Probability-weighted Present Value WITH NT2 54,984 0.56250 B. Present Values WITHOUT NT2: POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 hh - h 0.25 m 0.50 hm - h 0.25 l 0.25 hl - m 0.50 h 0.25 mh - m 0.50 m 0.50 mm 62,166 0.25000 m 0.50 l 0.25 ml 59,060 0.12500 l 0.25 h 0.25 lh - l 0.25 m 0.50 lm 43,854 0.12500 l 0.25 l 0.25 ll 41,420 0.06250 B. Probability-weighted Present Value WITHOUT NT2 55,101 0.56250 Probability-weighted PV Savings (Cost) WITH NT2 118 (Result A minus Result B; 2003 USD million) 6.3.2 Cost-Risk Analysis Results The results of the commercial cost-risk analysis are summarized in Table 28. As previously noted, the framework is incomplete, since High demand and High gas price scenarios have not been prepared. The review of downside risks represents only 56 percent of a complete cost-risk assessment. However, it must be noted that the scenarios excluded would be expected to record greater net benefits “with NT2� than the reported cases. Taking all evaluated potential outcomes into account, a system expansion plan featuring the commissioning of NT2 in October 2009 is the correct decision from an economic least-cost perspective. Even when only downside risks are evaluated, the probability-weighted PV of total savings over the entire Study Period is estimated to be US$118 million, equivalent to more than US$0.004 per kWh sold from the NT2 project. A Low natural gas price reduces total savings by US$105 million, although the net benefit “with NT2� is still significant (US$161 million). In contrast, Low demand would mean that the decision to develop NT2 in FY2010 would come at a cost of US$32 million. Results are least favorable for NT2 when combinations of adverse future conditions (e.g., low demand and low gas prices) are considered. Reaching a conclusion based on an incomplete cost-risk results matrix may be a cause for concern given even a low probability of negative outcomes. To address this Commercial Assessment 68 concern, we have completed the entire cost-risk framework based on the very conservative assumption that every “High� demand or gas price scenario will achieve savings identical to its closest “Medium� counterpart scenario (e.g., the “High demand, High gas price� scenario is assigned the savings of the “Medium demand, Medium gas price� scenario) even though we know, both intuitively and from our modeling for RELC/2004, that these scenarios would be expected to produce additional savings. This approach is mathematically equivalent to assigning a 75 percent probability to the “Medium� results and a “zero� percent probability to future events would prove advantageous to NT2 (i.e., construction cost at the low cost estimate, demand at the high load forecast, and natural gas price at the high fuel price forecast). Results of this cost-risk sensitivity test are reported in Table 24. The risk-adjusted savings “with NT2� are estimated to be US$145 million. These results confirm our Base Case conclusion that NT2 is a viable investment project from a commercial perspective. Table 29. Commercial Cost-Risk Sensitivity Test A. Present Values WITH NT2: CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Savings by Case Probability Case Probability Case Probability Case Present Value Probability Scenario m 1.00 h 0.25 h 0.25 mhh 61,939 0.06250 227 m 1.00 h 0.25 m 0.50 mhm 61,939 0.12500 227 m 1.00 h 0.25 l 0.25 mhl 58,900 0.06250 161 m 1.00 m 0.50 h 0.25 mmh 61,939 0.12500 227 m 1.00 m 0.50 m 0.50 mmm 61,939 0.25000 227 m 1.00 m 0.50 l 0.25 mml 58,900 0.12500 161 m 1.00 l 0.25 h 0.25 mlh 43,886 0.06250 (32) m 1.00 l 0.25 m 0.50 mlm 43,886 0.12500 (32) m 1.00 l 0.25 l 0.25 mll 41,529 0.06250 (109) A. Probability-weighted Present Value WITH NT2 56,708 1.00000 B. Present Values WITHOUT NT2: POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million) Case Probability Case Probability Case Present Value Probability h 0.25 h 0.25 hh 62,166 0.06250 h 0.25 m 0.50 hm 62,166 0.12500 h 0.25 l 0.25 hl 59,060 0.06250 m 0.50 h 0.25 mh 62,166 0.12500 m 0.50 m 0.50 mm 62,166 0.25000 m 0.50 l 0.25 ml 59,060 0.12500 l 0.25 h 0.25 lh 43,854 0.06250 l 0.25 m 0.50 lm 43,854 0.12500 l 0.25 l 0.25 ll 41,420 0.06250 B. Probability-weighted Present Value WITHOUT NT2 56,854 1.00000 Probability-weighted PV Savings (Cost) WITH NT2 145 (Result A minus Result B; 2003 USD million) Conclusion 69 7 C ONCLUSION Economic and Commercial assessments of the project conclude that the decision to purchase NT2 power offers significant savings to the regional power system. The economic evaluation, based on a probability-weighted real cost-risk analysis of downside risks, indicates a real savings (i.e., in present value terms at 2003 prices) on the order of US$188 million will accrue to the region over the lifetime of the plant. Actual savings might be even higher under possible future conditions, such as higher- than-expected demand growth or higher-than-expected gas prices. More importantly, however, the decision to purchase a major source of energy at fixed price is robust to a wide range of behavior for the key 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 fuel price volatility, a feature of energy markets in recent decades that is expected to persist. As with any risk-return trade- off, the project is also subject to reduced net benefits if future economic conditions are adverse from the perspective of NT2, i.e., lower-than-expected demand and gas prices. The commercial analysis, based on market costs expressed in current prices, suggests that the decision to purchase NT2 power will result in a nominal savings in present value terms on the order of US$145 million. This result indicates that the project remains commercially viable even after large real resource benefits accruing to the region in the economic analysis are paid by project sponsors directly to the government of Lao PDR in the form of taxes, duties, and royalties, and indirectly through the funding of environmental and social programming. Terms of Reference 71 A1 Terms of Reference Terms of Reference for Determining the Economic Least-Cost Justification for the Nam Theun 2 Regional Hydro-electric Power Project [A] Context The World Bank has received the Thailand Power Scenario Study (TPSS)49 and acknowledges its valuable contribution to understanding the commercial rationale of the Nam Theun 2 (NT2) Project in the context of the Thai power system. Elements from the TPSS are adopted as indicated in this terms of reference (ToR), which describes the next stage of the economic due diligence the Bank requires50 to determine whether the project has a satisfactory economic cost-risk profile for the regional51 power market. The main distinguishing characteristics of this second stage analysis are threefold: (i) to the greatest extent feasible, all values reflect real economic resource costs, (ii) the scope of work includes both the Thai and Laotian electricity markets, and (iii) the risk analysis consists of an integrated multi-event probabilistic framework that produces one overall quantitative result showing whether implementing the NT2 project for 2009 would be an acceptable economic investment for the power sector. The Bank acknowledges that the full participation of the Electricity Generating Authority of Thailand (EGAT) is important to the conduct of this study. The Bank expects 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 a substantial commitment of EGAT’s human and computer resources over a relatively short period of time, the Bank is prepared to help the Consultant and EGAT accommodate operational constraints in this respect. [B] Study Outcome The study outcome will be determined by means of the results profile shown in Annex 1: “Cost-Risk Framework�. This profile provides for calculating the probability- weighted present value (PV) costs of either implementing or not implementing NT2 for 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 the suggested probabilities of occurrence for Base Case, Lower and Higher estimates of these variables. The difference between the probability weighted PV cost of 49“Thailand Power Scenario Study�, by Robert Vernstrom, consulting economist, Bangkok, March 2003. The World Bank financed and supervised this study. 50World Bank guidelines for the economic evaluation of investment operations, including electric power projects: OP 10.04 and GP 4.45. 51 “Regional� means Laos and Thailand in this Terms of Reference. Terms of Reference 72 implementing the project in 2009 versus that of not implementing it is the decision criteria for this analysis by showing whether the project is an acceptable economic investment for the regional power market. The following sections describe the Bank’s requirements for this stage of its economic due diligence. Because the Bank is specifying these requirements for the purpose of a real resource cost-based analysis, neither the Consultant nor EGAT would be held accountable for specific assumptions and values that the Bank requires or to which the Bank agrees. The Bank acknowledges that the methods and values used in this study for its purposes are completely without prejudice to different ones that EGAT may 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 to assume that the probability of under-achieving these values is negligible, and shall document evidence to support this assumption. 7. The scenarios with NT2 should include a carbon credit of $x per ton of carbon 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 project output would be fully absorbed under the low demand forecast. The duration of the run-out period for end effects will be till the year at which the residual value in that year would discount to an insignificant present value. The Bank will discuss with the consultant how the power system model neutralizes end effects before the model runs are undertaken. 9 . The EGAT plant retirement schedule is adopted, subject to reporting requirements described in Section [F]. [D] Variables [D.1] Demand Forecast: 1. The Base Case Demand Forecast used in the Thailand Power Scenario Study is 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 the project is commissioned. 2. For both countries the Low Case demand forecast will be keyed off the Base Case forecast using the following equation, reflecting the percentage gap Terms of Reference 73 between these forecasts the Bank considers appropriate by year 10 into the forecast 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 Case growth rate of demand. 3. The High Case load forecast will be symmetrical to that of the Low Case. The growth rate for the High Case (“grH�) will therefore be determined according to 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 economic investment and operating costs of the NT2 project based on data from the project lenders’ financial model. This cash flow series will exclude transfers and sunk costs, but include incremental sponsor development costs that reflect use of real resources. 2. The High Case for the construction cost of NT2 will be 30% above of the expected construction cost used for the Base Case. The Low Case for the construction 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 deployed using 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 to be revised accordingly. 2. The real economic costs of alternative generation capacity will also include private sector incremental development costs appropriate to those technologies. 3. The Bank recommends that there be a spread of about USD200/kW to appropriately reflect the EPC cost difference between GT and CCGT plant. 4 . The Bank will confirm with the consultant the actual EPC costs and development cost margins to be used for GT and CCGT capacity. 5. The Consultant will assume that Laos’ alternative to NT2 for meeting that portion 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 considers acceptable for oil product prices in the screening curve analysis, as well as the Base, Low and High natural gas price trajectories. Terms of Reference 74 2. The coal prices in the TPSS may be adopted, unless it seems appropriate to make some adjustment in relation to the assumptions for natural gas and oil product prices to be used in this study. [D.5] Transmission 1. The project-associated transmission works in Laos are included in the project cost. 2. The project-associated incremental transmission costs for Thailand need to be determined in co-operation with EGAT on a basis that does not include any other future hydro exports from Laos to Thailand, because of their uncertainty, notwithstanding the higher level of potential exports contained in the MoU between the two countries on power exports from Laos to Thailand. 3. If EGAT and the consultant believe that the non-NT2 options also require incremental generation-associated transmission works, the economic costs of these should be determined and included. [E] Modeling 1. The Consultant will use EGAT’s Proscreen Model as in the TPSS, subject to the custom parameter and variable assumptions made for this study. 2. Before the modeling begins, Bank staff will obtain from EGAT and the consultant, by verbal and documentary communication, a clear understanding of 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-electric reservoir management), (iii) dispatching optimization (stacking merit order and dispatching algorithm), and (iv) calculation of end effects. 3. In these model runs, NT2 and all other generation capacity on the regional power system – including existing capacity owned and operated by IPPs - will be subject to economic dispatch for meeting incremental demand and the specified amount of Laotian demand, without consideration of contractual take-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 comparison in a situation where the commissioning of NT2 is delayed for 24 months, the investment 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 Annex 1). The results of these tests should be reported to the Bank before commencing the model runs described below, to determine whether it would be appropriate to amend the cost-risk analysis framework (Annex 1). 5. To complete the Cost-Risk Framework (Annex 1), a total of 18 scenario runs will 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 used for each of these variables. Terms of Reference 75 6. The 9 scenarios run with NT2 will be expanded to 27 scenarios by combining manually the three cases for the construction cost of NT2 with the results of these scenarios. 7. The probabilities associated with the High, Medium and Low assumptions are stated in Annex 1. 8. A second set of model runs for these scenarios will be carried out under which the economic values are converted to commercial values, but expressed in real US dollars of 2003, using the same framework as in Annex 1, in order to assess the commercial sustainability of the NT2 Power Purchase Agreement against the underlying economic trends in the regional power market. [F] Reporting This study will serve a number of purposes eventually involving a considerable range of audiences within and outside of the World Bank. For this reason, it is essential that the reporting of this work be thorough and self-standing, so that the assumptions, methods and corresponding results are detailed, transparent and easily understandable. Without limitation to the generality of this requirement, the Bank stresses the importance of comprehensive documentation, in Annexes as appropriate, for certain key 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 be assumed 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; and 11. 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 to facilitate a clear understanding of the reasons for differences in total PV cost between scenarios. The Bank also requires production and value data for the dispatch of each plant at five year intervals in the MMM case, to better understand how the model handles the merit order, and the contribution in energy and cost of each operating facility. Terms of Reference 76 Annex 1: Cost-Risk Framework A B C D E F G H 1 Cost-Risk Analysis Matrix 2 [A] Present Values with NT2 3 Construction Cost Power Demand Gas Price Scenario 4 Value Probability Value Probability Value Probability Value Probability 5 h 0.25 h 0.25 h 0.25 hhh 0.01563 6 h 0.25 h 0.25 m 0.50 hhm 0.03125 7 h 0.25 h 0.25 l 0.25 hhl 0.01563 8 h 0.25 m 0.50 h 0.25 hmh 0.03125 9 h 0.25 m 0.50 m 0.50 hmm 0.06250 10 h 0.25 m 0.50 l 0.25 hml 0.03125 11 h 0.25 l 0.25 h 0.25 hlh 0.01563 12 h 0.25 l 0.25 m 0.50 hlm 0.03125 13 h 0.25 l 0.25 l 0.25 hll 0.01563 14 m 0.50 h 0.25 h 0.25 mhh 0.03125 15 m 0.50 h 0.25 m 0.50 mhl 0.06250 16 m 0.50 h 0.25 l 0.25 mhi 0.03125 17 m 0.50 m 0.50 h 0.25 mmh 0.06250 18 m 0.50 m 0.50 m 0.50 mmm 0.12500 19 m 0.50 m 0.50 l 0.25 mml 0.06250 20 m 0.50 l 0.25 h 0.25 mlh 0.03125 21 m 0.50 l 0.25 m 0.50 mlm 0.06250 22 m 0.50 l 0.25 l 0.25 mll 0.03125 23 l 0.25 h 0.25 h 0.25 lhh 0.01563 24 l 0.25 h 0.25 m 0.50 lhm 0.03125 25 l 0.25 h 0.25 l 0.25 lhl 0.01563 26 l 0.25 m 0.50 h 0.25 lmh 0.03125 27 l 0.25 m 0.50 m 0.50 lmm 0.06250 28 l 0.25 m 0.50 l 0.25 lml 0.03125 29 l 0.25 l 0.25 h 0.25 llh 0.01563 30 l 0.25 l 0.25 m 0.50 llm 0.03125 31 l 0.25 l 0.25 l 0.25 lll 0.01563 32 WGTD PV 1.00000 33 [B] Present Values Without NT2 34 Power Demand Gas Price Scenario 35 Value Probability Value Probability Value Probability 36 h 0.25 h 0.25 hhh 0.06250 37 h 0.25 m 0.50 hhm 0.12500 38 h 0.25 l 0.25 hhl 0.06250 39 m 0.50 h 0.25 hmh 0.12500 40 m 0.50 m 0.50 hmm 0.25000 41 m 0.50 l 0.25 hml 0.12500 42 l 0.25 h 0.25 hlh 0.06250 43 l 0.25 m 0.50 hlm 0.12500 44 l 0.25 l 0.25 hll 0.06250 45 WGTD PV 1.00000 46 47 Net PV with NT2 0.00000 Thailand Demand Forecast 77 A2 Thailand Demand Forecast This appendix provides details of Thailand’s official Aug-02 load forecast. This forecast, supplemented by Lao PDR domestic load to be served by NT2 (75 MW capacity and 300 GWh generation), is the Base Case load forecast for our regional study. Table A2-5 provides a comparison of the Aug-02 forecast with the more optimistic Jan-04 forecast adopted for EGAT’s 2004 Power Development Plan. 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 A2-5. Comparison of the Aug-02 and Jan-04 Forecasts Thailand Demand Forecast 78 Table A2-1. EGAT Total Generation Requirement Forecast Base Case_August 2002 Fiscal Peak Energy Load Year Increase Increase Factor MW GWh MW % GWh % % Actual 1991 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 Growth 1991-2001 - 821.15 7.20 - 5,452.40 7.68 - Forecast 2002 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 Growth 1992-1996 - 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 Thailand Demand Forecast 79 Table A2-2. EGAT Total Sales Forecast Base Case_August 2002 Fiscal Peak Energy Load Year Increase Increase Factor MW GWh MW % GWh % % Actual 1991 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 Growth 1992-1996 - 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 Thailand Demand Forecast 80 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 2 1 PEAK DEMAND (MW) 0 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 01 20 0 %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 Thailand Demand Forecast 81 Table A2-4. PEA 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 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 Thailand Demand Forecast 82 Table A2-5. Comparison of The August 2002 and January 2004 Forecasts Emergy Requirement (GWh) Peak Demand (MW) Year Aug-02 Jan-04 1/ Difference Aug-02 Jan-04 2/ Difference 2004 122,024 126,811 4,787 19,029 19,600 571 2005 130,232 136,784 6,552 20,295 21,143 848 2006 139,000 147,658 8,658 21,648 22,238 590 2007 147,835 158,212 10,377 23,020 23,844 824 2008 157,064 169,280 12,216 24,450 25,548 1,098 2009 168,004 180,942 12,938 26,143 27,352 1,209 2010 178,079 193,530 15,451 27,711 29,308 1,597 2011 188,446 206,674 18,228 29,321 31,344 2,023 2012 199,378 220,253 20,875 31,014 33,445 2,431 2013 211,146 234,672 23,526 32,842 35,673 2,831 2014 223,437 249,843 26,406 34,743 38,015 3,272 2015 236,364 265,788 29,424 36,754 40,478 3,724 Average Annual Growth (%) 2004-10 6.5% 7.3% 6.5% 6.9% 2010-15 5.8% 6.6% 5.8% 6.7% 2004-15 6.2% 7.0% 6.2% 6.8% 1/ Base case assuming medium economic growth (MEG) scenario. 2/ Includes "Peak Cut" of 500 MW per year from 2006 (GOT policy). Fuel Price Assumptions 83 A3 Fuel Price Assumptions This appendix includes the following tables: Table A3-1. Economic Fuel Prices Adopted for the Study (constant US$2003) Table A3-2. Commercial Fuel Prices Adopted for the Study (current US$) Following the tables is an appendix from the World Bank’s Project Apprasal Document for NT2 (January 2005) which outlines the methodology employed to develop the natural gas price projections adopted for the current study. Fuel Price Assumptions 84 Table A3-1. Economic Fuel Price Projections (constant US$2003) Real Economic Prices - Base Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 2.55 2.55 2.55 3.39 6.10 1.21 1.54 2004 2.56 2.65 2.55 4.48 8.68 1.20 2.33 2005 2.51 2.60 2.49 4.06 7.88 1.19 2.22 2006 2.41 2.50 2.40 3.58 6.93 1.17 2.00 2007 2.37 2.46 2.36 3.43 6.65 1.15 1.77 2008 2.33 2.42 2.32 3.28 6.37 1.14 1.66 2009 2.31 2.41 2.30 3.26 6.33 1.12 1.54 2010 2.30 2.39 2.29 3.25 6.29 1.11 1.54 2011 2.29 2.38 2.28 3.23 6.26 1.10 1.55 2012 2.28 2.37 2.27 3.24 6.28 1.08 1.56 2013 2.27 2.37 2.27 3.25 6.30 1.06 1.57 2014 2.27 2.36 2.27 3.26 6.32 1.05 1.58 Average Annual Growth (%) 2003-2014 -1.1% -0.7% -1.1% -0.4% 0.3% -1.3% 0.2% Real Economic Prices - Low Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 2.32 2.32 2.32 3.00 5.40 1.21 1.24 2004 2.21 2.31 2.20 3.80 7.36 1.20 2.03 2005 2.18 2.27 2.17 3.45 6.68 1.19 1.93 2006 2.11 2.20 2.10 3.03 5.89 1.17 1.75 2007 2.08 2.17 2.06 2.91 5.65 1.15 1.56 2008 2.04 2.14 2.03 2.79 5.41 1.14 1.46 2009 2.03 2.13 2.02 2.77 5.38 1.12 1.36 2010 2.02 2.11 2.01 2.76 5.35 1.11 1.36 2011 2.01 2.10 2.00 2.74 5.32 1.10 1.37 2012 2.00 2.10 1.99 2.75 5.34 1.08 1.38 2013 1.99 2.09 1.99 2.76 5.35 1.06 1.38 2014 1.99 2.08 1.99 2.77 5.37 1.05 1.39 Average Annual Growth (%) 2003-2014 -1.4% -1.0% -1.4% -0.7% -0.1% -1.3% 1.1% Real Economic Prices - High Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 2.81 2.81 2.81 3.92 7.04 1.21 1.85 2004 2.95 3.04 2.94 5.17 10.01 1.20 2.63 2005 2.87 2.96 2.86 4.68 9.07 1.19 2.50 2006 2.74 2.84 2.73 4.12 7.98 1.17 2.25 2007 2.69 2.78 2.68 3.95 7.65 1.15 1.99 2008 2.64 2.73 2.63 3.78 7.32 1.14 1.85 2009 2.62 2.72 2.61 3.76 7.28 1.12 1.72 2010 2.61 2.70 2.60 3.73 7.24 1.11 1.71 2011 2.59 2.69 2.58 3.71 7.20 1.10 1.73 2012 2.59 2.68 2.58 3.73 7.22 1.08 1.74 2013 2.58 2.67 2.58 3.74 7.25 1.06 1.75 2014 2.57 2.67 2.57 3.75 7.27 1.05 1.76 Average Annual Growth (%) 2003-2014 -0.8% -0.5% -0.8% -0.4% 0.3% -1.3% -0.5% 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 Fuel Price Assumptions 85 Table A3-2. Commercial Fuel Price Projections (current US$) Nominal Commercial Prices - Base Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 2.95 2.95 2.95 3.56 8.54 1.21 1.56 2004 3.63 3.63 3.63 5.11 11.43 1.20 2.49 2005 3.48 3.48 3.48 4.57 10.46 1.20 2.34 2006 3.34 3.34 3.34 4.02 9.48 1.19 2.11 2007 3.32 3.30 3.32 3.89 9.25 1.19 1.89 2008 3.30 3.30 3.30 3.76 9.01 1.19 1.78 2009 3.32 3.34 3.32 3.77 9.02 1.18 1.67 2010 3.34 3.37 3.33 3.77 9.04 1.19 1.67 2011 3.36 3.38 3.34 3.78 9.05 1.19 1.69 2012 3.38 3.42 3.37 3.82 9.12 1.18 1.72 2013 3.40 3.46 3.39 3.86 9.20 1.18 1.74 2014 3.42 3.50 3.41 3.90 9.27 1.18 1.76 Average Annual Growth (%) 2003-2014 1.4% 1.6% 1.3% 0.8% 0.8% -0.2% 1.1% Nominal Commercial Prices - Low Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 2.75 2.75 2.75 3.15 7.55 1.21 1.25 2004 3.29 3.29 3.29 4.33 10.02 1.20 2.17 2005 3.18 3.18 3.18 3.87 9.21 1.20 2.03 2006 3.07 3.07 3.07 3.41 8.39 1.19 1.84 2007 3.05 3.03 3.05 3.30 8.19 1.19 1.66 2008 3.04 3.04 3.04 3.19 8.00 1.19 1.56 2009 3.06 3.07 3.06 3.20 8.01 1.18 1.47 2010 3.08 3.11 3.07 3.20 8.02 1.19 1.48 2011 3.10 3.12 3.08 3.21 8.03 1.19 1.50 2012 3.12 3.16 3.10 3.25 8.10 1.18 1.52 2013 3.14 3.20 3.12 3.28 8.16 1.18 1.54 2014 3.16 3.24 3.14 3.32 8.23 1.18 1.56 Average Annual Growth (%) 2003-2014 1.2% 1.5% 1.2% 0.5% 0.8% -0.2% 2.0% Nominal Commercial Prices - High Case Fiscal Natural Gas - USD/mmbtu Hvy Oil 3.5% Diesel Lignite Import Coal Year Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu 2003 3.19 3.19 3.19 4.11 9.85 1.21 1.87 2004 3.97 3.97 3.97 5.90 12.83 1.20 2.82 2005 3.80 3.80 3.80 5.27 11.70 1.20 2.64 2006 3.63 3.63 3.63 4.63 10.58 1.19 2.37 2007 3.60 3.58 3.60 4.48 10.30 1.19 2.11 2008 3.58 3.57 3.57 4.33 10.03 1.19 1.99 2009 3.60 3.61 3.59 4.33 10.04 1.18 1.86 2010 3.62 3.64 3.61 4.34 10.05 1.19 1.86 2011 3.63 3.65 3.62 4.34 10.06 1.19 1.89 2012 3.66 3.70 3.64 4.39 10.15 1.18 1.91 2013 3.68 3.74 3.67 4.44 10.23 1.18 1.94 2014 3.70 3.78 3.69 4.48 10.32 1.18 1.97 Average Annual Growth (%) 2003-2014 1.4% 1.6% 1.3% 0.8% 0.4% -0.2% 0.5% Fuel Price Assumptions 86 Natural Gas Valuation An important component of the economic due diligence on the NT2 project is to determine whether NT2 is cost-effective for the Thai power system, as the project’s primary purpose and underlying bankability relates to the Thai power market. This cost-effectiveness is assessed by evaluating whether the project is least-cost for the duty-service envisaged. One of the most important determining factors is the value of natural gas that would be used in combined cycle gas turbines, as these are the most likely economic alternative to NT2. The long-term supply and demand outlook for natural gas, and its opportunity cost whether as an export or import commodity are key factors determining the appropriate principles for calculating its economic value. The industry has grown considerably and the long-term supply: demand picture has evolved over the past several decades. As well, because of the commercial interests at stake between buyers and sellers, competition for the market between sellers, the real uncertainty about future demand and supply conditions and the complexity of the contracting arrangements, this is an industry that doles out information very cautiously. The insights leading to the valuations presented in this note rely for the most part on verbally communicated confidential information from players active in the industry, some power sector documentation and some relevant oil price projections provided by the World Bank. While this is not the optimal basis for the purpose at hand, it was sufficient 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 its opportunity value as an export commodity or import requirement (border price basis). It may also be appropriate to include a depletion premium (also called a “user cost�). This reflects the possibility that an increased current use of the resource accelerates the time path to depletion, at which point a “backstop� price would be paid for the commodity that replaces it. The supply cost basis is appropriate where the potential supply of natural gas is very large relative to the market, with little likelihood over an economically meaningful time period that foregone economic export potential or heavy domestic use would trigger border 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 the data. Fuel Price Assumptions 87 Economic supply costs are the real costs incurred over time of finding, developing, producing and transporting the commodity, net of taxes and royalties. Border prices are 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 a price signal that tells consumers the present value consequences of an increase in their use of an exhaustible resource. It compensates the resource owner who may choose whether to leave the resource in the ground for future appreciation or produce it sooner. 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 consumption over that time and the likely cost of the backstop at depletion time. The more uncertain the basis of the supply, demand and cost projections, the lower the expected backstop value, the further off the expected depletion time and the flatter the marginal cost curves, the less the attention that should be focused on user costs. All of these factors indicate that user costs would be very difficult to compute with confidence for Thailand. On the whole, the industry is optimistic about both the resource base and demand growth. Evidence of this optimism is these companies’ continued commitment of resources to exploration and development as needed, the creation of long term joint arrangements between countries sharing resources in the Gulf of Thailand52, and a 2.4 billion dollar pipeline from the Gulf to the mainland (target of 2006). Existing transportation capacity is nearing saturation. The new line will almost double existing transportation capacity. This capacity should be fully utilized by 2015, based on projected demand growth of about 6% per year. The R/P ratio is now about 20. This is higher than the industry typically considers ideal, and is partly the result of conservatively regulated reservoir depletion rates, as well as strenuous effort to expand the industry over the past two decades. Given this comfortable supply position, the market will pace reserves additions; however there will be a rush between companies to reserve capacity in the new pipeline. This means developing new GPAs over the next few years and proving-up the necessary reserves as required. The industry views demand as driving new contracts. Producers use demand forecasts from PTT and EGAT to do their E&P planning. Hence supply will evolve to meet growing demand. Several sources say that supply costs have declined dramatically over the past twenty years with major advances in exploration and drilling technology. The latter is especially important for the Gulf of Thailand, which is geologically fractured. They suggest that future E&P costs should decrease very gradually in well-known areas, but costs 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 believe that aggregate supply costs in the future will remain about the same, increase moderately or decrease moderately. The supply from Myanmar is priced about 50% higher than that from Thailand, and has a 30% share in the market. This share varies 52 These include the Myanmar Thailand joint area and the Thai Kampuchea overlap – there is a dispute about resource sharing between the latter. Fuel Price Assumptions 88 from period to period, its value being uncertain over the long term it could decrease, increase or remain about the same, depending upon negotiations. Regarding demand, the power sector absorbs about 80% of consumption and the industrial sector the other 20%. The electricity vs. other industry share is likely to be sustained in a range of 70% to 80%. Assuming that power sector and industrial demand continue to grow at 6% per year over the long term, gas supply will be produced from known areas for many years to come, providing a reference point for pricing; but beyond 2014/2015, imported gas or as-yet undiscovered Thai gas will be relied upon increasingly to complement the supply requirement at marginal costs that are not now known. The basic market structure is one of monopoly buyer and competition between sellers. The majors are UNOCAL, TotalElfFina, PTT (now privatized) and Mitsui, with Amarada Hess and Chevron growing quickly. There are several other companies with a smaller presence in the E&P business. Stiff downward pressure on prices is exercised by a vigilant public, vigilant government and the monopoly buyer (PTT) having a window on the producing industry through its own 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 a concession, with regulated depletion rates (1 in 6000) to prevent reserves loss through accelerated depletion. Each concession has its own particular cost structure and 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 to the choice of valuation approach: i. there is apparent comfort in respect of long-term supply from domestic reserves and the MTJDA, with no issue of export opportunity cost; ii. a minority share of gas comes from Myanmar, it being expected that this share will vary moderately over time; the time period to depletion – if it ever happens – is far off; backstop values could be determined by imported LNG, more as yet undiscovered Thai gas or imports from neighboring countries – all at costs that are not now known; iii. there are competitive pressures characterizing the contracting process, such that the terms of the contracts can be said to reflect a market-based valuation of the cost recovery and remuneration levels needed to keep the producers in operation; iv. in general, there is uncertainty about the size of future reserves additions and their incremental costs, the predominant view in the industry being optimistic on supply and rather unclear about whether marginal cost will increase moderately or decrease moderately. Under these conditions, it seems most appropriate to base the economic value of natural gas on: Fuel Price Assumptions 89 i. the cost of discovery, development and production for local supply as evidenced in 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. valuation of gas transmission on a postage stamp basis including only the estimated recurrent operating costs of the transmission network, insofar as the capital costs of the existing infrastructure and the third line now under construction are sunk costs). Because each GPA differs and we do not have access to the individual contracts, it was necessary to create a “typical contract� the key elements of which industry interviewees claimed to be representative of the average. The basic pricing structure, valid for the duration of the contract, is as follows. In the contracts, the current gas price payable to producers is specified in THB. It is the result 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 price of 3.5%S HFO Singapore, (ii) a petroleum industry machinery inflation index reflecting USD inflation, (iii) the Thai CPI reflecting Thai domestic inflation, (iv) an exchange rate adjuster and (v) a constant. Given that our numeraire in this project analysis is USD, the machinery index, the Thai CPI index and the exchange rate adjuster would be offsetting in future price projections using the PPP method of exchange rate projection. When working in USD prices rather than THB prices, the only necessary element 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%. In the economic valuation PTT's tolls are replaced with an estimated incremental recurrent operating cost of transmission services. The pen-ultimate step for moving from commercial value to economic value is to remove transfers from the commercial price, these being royalties and taxes. The royalty rate for new reserves is 12.5% of the producers’ selling price. The actual amount of income tax producers pay in total or per mmbtu of gas sold cannot be known without access to company accounts, and we have no such access. An approximation of the income tax load is made by taking the difference between the projected producer selling price net of royalties from the foregoing steps, deducting an advised producer EDP cost, the residual being gross profit, of which 50% is deducted in taxes. These deductions of income taxes and royalties are made only for the Thai portion of gas supply, because Myanmar is beyond the welfare boundary of the analysis. At the welfare boundary Thailand faces a border price, and any embedded taxes and royalties going to the Government of Myanmar are included in economic costs facing Thailand, therefore not deducted. The final calculation is to convert the nominal economic natural gas values into real values by deflating the nominal series with the MUV index. This is the index the World Bank uses for converting hydrocarbon prices between real and nominal values. Fuel Price Assumptions 90 Low and High Value Projections: The gas value projections for the low and high 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 recalculated using high and low price projections for the World Bank Crude Mix. The high and low price projections are calculated on the basis of one standard deviation from the base price projection. Secondly, the Myanmar share is decreased or increased moderately in the low and high price projections respectively, according to the range of conceivable Myanmar share mentioned by industry participants. Thus, the low price trajectory reflects the combined impact of a lower valued international hydrocarbon market along with a more plentiful outlook for Thai supply at no increase in marginal cost, hence less involvement of costlier Myanmar border values, while the high trajectory reflects the reverse. We believe that the range so created accounts for the two key uncertainties going forward: (i) the future value of world oil, and (ii) the degree of future Thai exposure to (costlier) imported natural gas. The valuation methodology described above was calibrated to 2004 actual commercial values (i.e. excluding adjustments from commercial to economic value), in order to have an accurate basis upon which to project both commercial and economic values based on the assumptions discussed above. The commercial values of natural gas for the commercial analysis includes taxes and royalties and they include actual or anticipated pipeline tolls with capital charges. There is some sensitivity of the gas prices to the electricity demand forecast, mainly because changes in volumes affect unit transmission costs. The natural gas price projections extend from 2004 to 2014, being the final year of electric power system expansion modeled in the least-cost analysis. For the end effects period 2014-2034, in the economic analysis the value achieved by 2014 is sustained in real terms; for the commercial analysis, which is conducted in nominal values, from 2014 the price of natural gas is inflated by 1.23 percent per year. This reflects a judgment that international background inflation will be no less than this value, and it maintains the inflation of the natural gas price in step with the inflation of NT2's tariff in the PPA. Of course, if the commercial value of natural gas were to increase at higher rates, this would make NT2 more advantageous. The assumptions used in these projections are modest. The year to year projected natural gas prices used in the cost risk analysis are as follows: Fuel Price Assumptions 91 Table 7.3 Economic values of Natural Gas – Thailand ECONOMIC VALUES Base Demand Low Demand High Demand Year Base Val Low Val High Val Base Val Low Val High Val Base Val Low Val High Val 2003 2.39 2.27 2.63 2.49 2.16 2.73 2.38 2.05 2.62 2004 2.42 2.09 2.79 2.52 2.19 2.88 2.41 2.08 2.78 2005 2.37 2.06 2.71 2.46 2.15 2.81 2.36 2.05 2.70 2006 2.28 1.99 2.59 2.37 2.09 2.69 2.27 1.98 2.58 2007 2.24 1.96 2.54 2.33 2.06 2.64 2.23 1.95 2.53 2008 2.20 1.93 2.49 2.30 2.03 2.59 2.19 1.92 2.48 2009 2.19 1.92 2.48 2.28 2.02 2.57 2.18 1.91 2.47 2010 2.18 1.91 2.47 2.27 2.01 2.56 2.17 1.90 2.46 2011 2.16 1.90 2.45 2.26 2.00 2.55 2.15 1.89 2.44 2012 2.16 1.89 2.45 2.25 1.99 2.54 2.15 1.88 2.43 2013 2.15 1.89 2.44 2.24 1.98 2.53 2.15 1.89 2.44 2014 2.14 1.88 2.43 2.24 1.97 2.53 2.14 1.88 2.43 COMMERCIAL PRICES Base Demand Low Demand High Demand Year Base Pr Low Pr High Pr Base Pr Low Pr High Pr Base Pr Low Pr High Pr 2003 3.37 3.25 3.54 3.37 3.05 3.54 3.37 3.05 3.54 2004 3.63 3.29 3.97 3.63 3.29 3.97 3.63 3.29 3.97 2005 3.48 3.18 3.80 3.48 3.18 3.80 3.48 3.18 3.80 2006 3.34 3.07 3.63 3.34 3.07 3.63 3.34 3.07 3.63 2007 3.32 3.05 3.60 3.30 3.03 3.58 3.32 3.05 3.60 2008 3.33 3.07 3.60 3.33 3.07 3.60 3.32 3.06 3.60 2009 3.35 3.09 3.62 3.36 3.10 3.64 3.34 3.08 3.61 2010 3.36 3.10 3.64 3.40 3.13 3.67 3.35 3.09 3.63 2011 3.38 3.12 3.65 3.41 3.14 3.68 3.36 3.10 3.64 2012 3.40 3.14 3.67 3.45 3.18 3.72 3.38 3.12 3.66 2013 3.42 3.16 3.70 3.49 3.22 3.76 3.41 3.14 3.68 2014 3.44 3.17 3.72 3.53 3.26 3.81 3.42 3.16 3.70 Fuel Price Assumptions 92 Detailed Plant Data (Existing System) 93 A4 Detailed Plant Data (Existing System) This appendix includes the following tables:  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 Detailed Plant Data (Existing System) 94 Table A4-1. Existing Installed Generating Capacity (as of Sep-03) Plant Type Fuel Installed Capacity Total Capacity Type (MW) (MW) A. Hydroelectric Plant - Bhumibol - (6x82.2)+115+171 779.2 Sirikit - 4x125 500.0 Ubolratana - 3x8.4 25.2 Sirindhorn - 3x12 36.0 Chulabhorn - 2x20 40.0 Kaeng Krachan - 1x17.5 17.5 Nam Pung - 2x3 6.0 Srinagarind - (3x120)+(2x180) 720.0 Bang Lang - 3x24 72.0 Tha Thung Na - 2x19 38.0 Vajiralongkorn - 3x100 300.0 Pak Mun - 4x34 136.0 Huai Kum - 1x1.06 1.1 Ban Santi - 1x1.275 1.3 Mae Ngat - 2x4.5 9.0 Rajjaprabha - 3x80 240.0 Miscellaneous - 0.429 0.4 Total 2,921.7 B. Thermal Power Plant South Bangkok Oil/Gas (2x200)+(3x310) 1,330.0 Mae Moh Lignite (3x75)+(4x150)+(6x300) 2,625.0 Bang Pakong Oil/Gas (2x550)+(2x600) 2,300.0 Total 6,255.0 C. Combined Cycle Power Plant Bang Pakong Block 1-2 Gas 2x[(4x60.7)+(137.5)] 760.6 Block 3-4 Gas 2x[(2x104)+(1x99)] 614.0 Nam Phong Block 1-2 Gas 2x[(2x121)+(1x113)] 710.0 South Bangkok Block 1 Gas (2x110)+(1x115) 335.0 Block 2 Gas (2x202)+(1x220) 624.0 Wang Noi Block 1-2 Gas 2x[(2x223)+(1x205)] 1,302.0 Block 3 Gas (2x236)+(1x257) 729.0 Total 5,074.6 D. Gas Turbine Power Plant Lan Krabu Gas (4x14)+(2x16)+(4x20) 168.0 Nong Chok 1-2 Diesel 3x122 366.0 Surat Thani Gas 2x122 244.0 Total 778.0 E. Diesel Mae Hong Son Diesel 1x6 6.0 Total 6.0 F. Renewable Energy Source Total 0.534 0.5 G. Purchased Power Khanom Thermal Oil/Gas 2x75 150.0 Khanom CC Gas (4x112)+(1x226) 674.0 Rayong CC Block 1-4 Gas 4x[(2x103)+(1x102)] 1,232.0 Ratchaburi Thermal Gas 2x720 1,440.0 Ratchaburi CC Block 1-3 Gas 3x[(2x230)+(1x265)] 2,175.0 Tri Energy Gas (2x224)+(1x252) 700.0 Independent Power Gas (2x230)+(1x240) 700.0 Bo Win Power Gas (2x356.5) 713.0 Eastern Power&Electric Gas 350 350.0 SPP - 1837.2 1,837.2 Theun Hinboun Hydro - 2x115 214.0 Houay Ho Hydro - 2x75 126.0 EGAT-TNB Tie Line - 300 300.0 Total 10,611.2 Grand 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. Detailed Plant Data (Existing System) 95 Table A4-2. Existing Hydro Power Plant Data Power Plant Est. Life Commission Monthly Dependable Hydro Capacity (MW) and Energy (MWh) (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). Detailed Plant Data (Existing System) 96 Table A4-3. Existing and Committed Small Power Producers (as of Sep-03) Power Plant Type of Date of Small Producers Project 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Location Fuel Purchase 1 Glow SPP Public Co.,Ltd (1) Rayong Gas 1 Apr. 96 90 2 Glow SPP Public Co.,Ltd (2) Rayong Gas 1 Oct. 96 90 3 TPT Utility Co.,Ltd Rayong Coal 1 Feb. 97 10 4 National Petrochemical Public Co.,Ltd Rayong Gas 1 Apr. 97 32 5 Glow SPP 1 Co.,Ltd (1) Rayong Gas 3 Feb. 98 55 6 Thai Oil Power Co.,Ltd. Chon Buri Gas 1 Apr. 98 41 7 Defence Energy Chiang Mai Heavy Oil 26 Jun. 98 9 8 Gulf Cogeneration Co.,Ltd Sara Buri Gas 3 Sep. 98 90 9 Amata-EGCO Power Co.,Ltd Chon Buri Gas 17 Sep. 98 90 10 Glow SPP 1 Co.,Ltd (2) Rayong Gas 18 Sep. 98 55 11 Bangkok Cogeneration Co.,Ltd Rayong Gas 4 Feb. 99 90 12 National Power Supply Co.,Ltd (1) Pra Chin Buri Coal 12 Mar. 99 90 13 Glow SPP 2 Co.,Ltd (1) Rayong Gas 29 Mar. 99 60 14 Saha Cogen (Chon Buri) Co.,Ltd Chon Buri Gas 19 Apr. 99 90 15 Thai Power Supply Co.,Ltd (1) Cha Choeng Sao Rice Husk 21 Apr. 99 25 16 Glow SPP 2 Co.,Ltd (2) Rayong Gas 26 Apr. 99 60 17 Thai Power Supply Co.,Ltd (2) Cha Choeng Sao Rice Husk 7 May. 99 6.4 18 Rojana Power Co.,Ltd Ayutthaya Gas 26 May. 99 90 19 National Power Supply Co.,Ltd (2) Pra Chin Buri Coal 12 Jul. 99 90 20 Samutprakarn Cogeneration Co.,Lld Samut Prakarn Gas 23 Aug. 99 90 21 Glow SPP 3 Co.,Ltd (1) Rayong Coal 1 Sep. 99 90 22 Glow SPP 3 Co.,Ltd (2) Rayong Coal 20 Mar. 00 90 23 Thai National Power Co.,Ltd Rayong Gas 4 Oct. 00 90 24 Nong Khae Cogeneration Co.,Ltd Sara Buri Gas 12 Oct. 00 90 25 Laem Chabang Power Co.,Ltd Chon Buri Gas 16 Jul. 01 60 26 Bio-Mass Power Co.,Ltd Chainat Rice Husk 9 Sep. 01 5 27 Amata Power Co.,Ltd Chon Buri Gas 28 Sep. 01 90 28 T.L.P. Cogeneration Co.,Ltd Rayong Gas 28 Jan. 03 60 29 Roi Et Green Co.,Ltd Roiet Rice Husk 29 May. 03 8.8 30 Siam Power Co.,Ltd Rayong Gas 1 Jan 06 60 31 Gulf Electric Public Co.,Ltd (Yala) Yala Wood Chip 1 Jun 04 20.2 32 Country Electric Co.,Ltd Lopburi Rice Husk - 15 33 Mitr Phol Sugar Corp.,Ltd Suphan Buri Bagasse/Wood - 25 34 Gulf Electric Public Co.,Ltd (Trang) Trang Wd Chp Plm Shll - 20.2 35 A.A. Pulp Mill (2) Co.,Ltd Pra Chin Buri Black Liquor - 25 36 Advance Agro Public Co.,Ltd Chon Buri Rice Hsk Wd Chp - 50 37 Korach Industry Co.,Ltd Nakhon Ratchasima Bagasse - 8 38 United Farmer& Industry Co.,Ltd Chaiyaphum Bagasse/wood - 29 39 A.T. Bio Power Co.,Ltd Phichit Rice Husk - 20 40 Mitr Kalasin Sugar Co.,Ltd Kalasin Bagasse - 8 41 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 -Renewable energy 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. Detailed Plant Data (Existing System) 97 Table A4-4. Schedule of Planned Plant Retirements Power Plant Rating Year(s) of Year of Planned Life (MW) Commissioning Retirement (Years) Thermal Plant South 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 25 Krabi #1 300 2003 2033 30 Combined Cycle Plant Bang 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 Plant Lan Krabu 2x16+2x14 1969-70 Depending on gas availability Lan Krabu 4x20 1981 Depending on gas availability Nong Chok 3x122 1995 2016 21 Surat 2x122 2001 2016 15 1/ Candidates for reconditioning. 2/ Retirement advanced due to planned availability of lower cost resources in South. How PROSCREEN Works 99 A5 How PROSCREEN Works PROSCREEN selects the least-cost plan by identifying the expansion scenario with the lowest present value over a user-specified period (the “objective function�). To achieve this objective requires a user manual over a foot thick and model input specification of several hundred pages. While it is beyond the scope of the current study to explain these details, the following paragraphs attempt to describe the methodology in layman’s terms. PROSCREEN divides the “Study Period� into two parts:  the “Planning Period�, defined for the current study as FY2003-14, in which decisions regarding system operation and expansion are analyzed annually and sub-annually (i.e., for user-defined seasons). The duration of the Planning Period has been selected based on preliminary model runs indicating (i) that NT2 is a least-cost addition to the Base Case expansion plan as of October 2009 (FY2010), and (ii) that NT2 would be fully absorbed into the regional power system by that date under the Low demand forecast (see Chapter 2).  The “End Effects Period� in which sophisticated programming techniques analyze differences between alternatives (e.g., due to different lives and operating characteristics) beyond the Planning Period horizon. Without end 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 represents the 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 first stage, operation of hydro generation, transactions (i.e., IPP purchases), and economic operation of pumped storage is simulated. The result of this first stage is the seasonal thermal load duration curve. In the second stage, the expected operation of the thermal units within the year is simulated based on a probabilistic technique. The results are production costs and the associated level of reliability.  Dispatch of non-thermal resources. Resources are dispatched to meet system load (modeled as typical weekly load shapes) without regard to cost in the following order:  Transactions (e.g. contract purchases) are dispatched either according to an hourly profile or designated shape (e.g., peak- How PROSCREEN Works 100 shaving, valley-filling, etc.). Although many SPPs are thermal, they are all treated as must-run transactions.  Hydro generation is dispatched simply as monthly generation which contributes to meeting system load, peak-shaving where possible. Available monthly hydro generation is exogenously determined by EGAT. (While PROSCREEN permits more complex modeling of hydro resources, these capabilities are not used by EGAT, since hydro makes up a relatively small portion of the total system.)  Pumped Storage is dispatched when (and if) off-peak pumping for on-peak generation is economically justified.  Dispatch of thermal resources. Each in-service thermal unit is dispatched according to standard probabilistic production costing procedures. Any “must-run� units are dispatched first, followed by enough other units in economic order53 to meet system load and resource requirements. Evaluating Expansion Alternatives PROSCREEN uses a mathematical approach called “dynamic programming� to determine the combination of sequential, interrelated decisions which produce the desired least-cost result. Specifically, for each year of the Planning Period, all combinations of expansion alternatives are evaluated; each combination (known as a “state�) that meets user-defined goals (i.e., to provide required capacity and target reserve margin) is defined as a feasible state. A feasible state includes:  Capital costs expressed as the economic carrying cost associated with each candidate in the state; and  Production costs derived from a complete probabilistic dispatch of the total system including both existing and candidate units. The present value of capital and production costs determines the accumulated cost of each feasible state. For the next year, each of these “origin states� becomes a starting point for generating additional states which are feasible in the current year. Again, all possible combinations 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 through the Planning Period, with the objective function value for each year equal to the objective function value for the “origin state� plus the present value of production and capital cost from the current state. After the last year of the Planning Period is analyzed, end-effects are considered to account for differences in operating characteristics, fuel costs, O&M costs, and the 53 As modified to reflect fuel contract and availability constraints. How PROSCREEN Works 101 lives of the alternatives resources beyond the Planning Period. The End Effects Period total 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 the specified End Effects Period. (Since EGAT adopts the model option of an infinite End Effects Period, this calculation is analogous to a perpetuity.) Production costs equal the 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 of the Planning Period) and time-weighted inputs for fuel and operating costs. Economic Base Case with NT2 – Detail 103 A6 Economic Base Case with NT2 – Detail This appendix includes the following tables:  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 Economic Base Case with NT2 – Detail 104 Table A6-1. Demand and Supply Balance – Economic Base Case with NT2 2003 2004 2005 2006 2007 2008 LOADS - 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 21,332 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 4,521 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 - - - 145 243 228 PUMPING ENERGY - - - (207) (348) (325) NET TRANSACTIONS 15,820 16,430 16,856 16,992 16,942 16,892 THERMAL 91,436 98,021 105,606 114,054 122,952 132,360 EMERGENCY ENERGY - - - - 2 4 SYSTEM LOAD FACTOR 0.73 0.73 0.73 0.73 0.73 0.73 Economic Base Case with NT2 – Detail 105 2009 2010 2011 2012 2013 2014 LOADS - 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 16,752 18,909 21,009 23,405 26,029 GAS - Thermal 4,521 4,225 3,929 3,929 3,632 3,108 HFO (Heavy Fuel Oil) 287 287 287 287 287 287 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 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 278 100 86 51 40 69 PUMPING ENERGY (397) (143) (123) (74) (57) (98) NET TRANSACTIONS 16,842 22,171 22,109 22,071 22,021 21,971 THERMAL 143,423 148,504 159,014 170,049 181,948 194,375 EMERGENCY ENERGY 3 1 1 - - - SYSTEM LOAD FACTOR 0.73 0.73 0.73 0.73 0.73 0.73 Economic Base Case with NT2 – Detail 106 Table A6-2. System Costs by Plant Group – Economic Base Case with NT2 (US$ 000) 2003 2004 2005 2006 2007 2008 OPERATING COSTS THERMAL COST - TOTAL TOTAL FUEL COST 1/ 1,601,057 1,771,588 1,901,271 2,027,558 2,149,007 2,249,831 VAR. O&M COST 55,007 58,049 62,536 71,634 81,144 97,019 FIXED 0&M COST 368,831 381,972 381,971 376,866 400,463 417,695 THERMAL COST ($/MWh) 22 23 22 22 21 21 HYDRO COST - TOTAL TOTAL VAR COST 6,933 6,933 6,933 7,609 8,068 7,995 TOTAL FIXED COST 49,845 57,472 57,472 57,472 57,472 57,472 TRANSACTION PURCHASES 513,864 535,738 551,482 557,671 557,671 557,671 EMERGENCY ENERGY COST - - - 559 3,279 5,911 TOTAL SYSTEM COST 2,595,538 2,811,751 2,961,667 3,099,370 3,257,106 3,393,595 SYSTEM COST ($/MWh) 23 24 23 23 23 22 AVG. MARGINAL COST ($/MWh) 22 22 23 30 39 43 FIXED COSTS TOTAL CAPITAL COST2/ - - - - - 45,808 TOTAL COST TOTAL UTILITY COST 2,595,538 2,811,751 2,961,667 3,099,370 3,257,106 3,439,403 PRESENT VALUE OF COST 2,595,538 2,556,138 2,447,658 2,328,602 2,224,647 2,135,598 ACCUM. PRESENT VALUE 2,595,538 5,151,675 7,599,334 9,927,937 12,152,584 14,288,183 1/ See attached table of fuel usage by type. 2/ Capital costs for each addition discounted to the year of commissioning. Economic Base Case with NT2 – Detail 107 (US$ 000) 2009 2010 2011 2012 2013 2014 OPERATING COSTS THERMAL COST - TOTAL TOTAL FUEL COST 1/ 2,395,015 2,474,167 2,647,856 2,819,880 3,004,989 3,183,045 VAR. O&M COST 125,022 132,516 173,563 233,052 297,620 376,656 FIXED 0&M COST 458,520 478,517 508,781 546,959 585,137 623,315 THERMAL COST ($/MWh) 21 21 21 21 21 22 HYDRO COST - TOTAL TOTAL VAR COST 8,229 7,399 7,335 7,173 7,119 7,255 TOTAL FIXED COST 57,472 57,472 57,472 57,472 57,472 57,472 TRANSACTION PURCHASES 557,671 566,509 566,509 566,562 566,509 566,509 EMERGENCY ENERGY COST 4,264 856 741 368 306 315 TOTAL SYSTEM COST 3,606,194 3,717,438 3,962,257 4,231,467 4,519,152 4,814,567 SYSTEM COST ($/MWh) 22 21 21 22 22 22 AVG. MARGINAL COST ($/MWh) 37 28 28 26 25 24 FIXED COSTS TOTAL CAPITAL COST2/ 137,424 347,862 463,674 601,098 741,829 884,422 TOTAL COST TOTAL UTILITY COST 3,743,618 4,065,300 4,425,932 4,832,565 5,260,982 5,698,990 PRESENT VALUE OF COST 2,113,175 2,086,142 2,064,730 2,049,479 2,028,336 1,997,461 ACCUM. PRESENT VALUE 16,401,358 18,487,500 20,552,230 22,601,710 24,630,046 26,627,508 1/ See attached table of fuel usage by type. 2/ Capital costs for each addition discounted to the year of commissioning. Economic Base Case with NT2 – Detail 108 Table A6-3. Fuel Use by Type – Economic Base Case with NT2 2003 2004 2005 2006 2007 2008 GENERATION (GWh) GAS - Combined Cycle 70,572 74,726 76,619 77,642 79,500 90,080 GAS - Thermal 5,084 6,317 11,357 18,280 17,176 14,203 HFO (Heavy Fuel Oil) - 1,141 1,835 1,963 2,012 1,835 DIESEL 33 41 48 444 561 637 LIGNITE 15,747 15,796 15,747 15,747 15,747 15,796 COAL - Imported - - - - 7,905 9,738 TNB (tie line) - - - 21 61 75 THERMAL CAPACITY BY FUEL 1/ GAS - Combined Cycle 11,691 11,691 11,691 11,691 12,071 13,798 GAS - Thermal 5,048 5,048 5,048 4,856 4,665 4,521 HFO (Heavy Fuel Oil) - 287 287 287 287 287 DIESEL 597 597 597 597 597 597 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported - - - - 1,347 1,347 TNB (tie line) 300 300 300 300 300 300 FUEL BURNED (mmBtu) GAS - Combined Cycle 535,298 566,192 582,540 592,564 605,896 677,615 GAS - Thermal 50,068 61,487 108,820 174,300 163,722 135,567 HFO (Heavy Fuel Oil) - 11,659 17,543 18,631 19,043 17,551 DIESEL 306 383 453 4,132 5,377 6,058 LIGNITE 164,813 165,323 164,813 164,813 164,813 165,323 COAL - Imported - - - - 77,767 95,804 TNB (tie line) - - 3 248 719 887 TOTAL FUEL COST (US$ 000) GAS - Combined Cycle 1,279,362 1,381,507 1,398,095 1,398,451 1,405,679 1,565,291 GAS - Thermal 119,662 150,029 261,168 411,348 379,835 313,159 HFO (Heavy Fuel Oil) - 31,946 45,260 45,087 43,229 40,544 DIESEL 2,610 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 7.59 7.58 7.60 7.63 7.62 7.52 GAS - Thermal 9.85 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 9.27 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 18.13 18.49 18.25 18.01 17.68 17.38 GAS - Thermal 23.54 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 79.09 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 0.11 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. Economic Base Case with NT2 – Detail 109 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. Economic Base Case with NT2 – Detail 110 Table A6-4. Fuel Type by Individual Plant – Economic Base Case with NT2 Code THERMAL Unit CAPACITY FUEL FUEL COMM'N RETIREM'T No. UNIT No. MW CLASS YEAR YEAR Existing Gas-fired C-C - with some Diesel support 1 LKB 1 232 DGLKB GCC 1970 2050 2 NPO_CC 1 347.2 DGNP GCC 1992 2017 3 NPO_CC 2 347.2 DGNP GCC 1994 2019 Existing Gas-fired C-C Plant 4 BPK_CC 1 372.7 GAS_MIX GCC 1983 2007 5 BPK_CC 2 372.7 GAS_MIX GCC 1983 2008 6 BPK_CC 3 300.9 GAS_MIX GCC 1992 2016 7 BPK_CC 4 300.9 GAS_MIX GCC 1992 2017 8 SB_CC 1 328.1 GAS_MIX GCC 1994 2019 9 SB_CC 2 610.3 GAS_MIX GCC 1998 2022 10 WN_CC 1 632.5 GAS_MIX GCC 1997 2023 11 WN_CC 2 632.5 GAS_MIX GCC 1998 2023 12 WN_CC 3 708.3 GAS_MIX GCC 1998 2023 16 RY_CC 1 301.8 GAS_MIX GCC 1992 2015 17 RY_CC 2 301.8 GAS_MIX GCC 1992 2015 18 RY_CC 3 301.8 GAS_MIX GCC 1992 2015 19 RY_CC 4 301.8 GAS_MIX GCC 1993 2015 20 KN_CC 1 165.1 GAS_MIX GCC 1995 2016 21 KN_CC 2 165.1 GAS_MIX GCC 1995 2016 22 KN_CC 3 165.1 GAS_MIX GCC 1995 2016 23 KN_CC 4 165.1 GAS_MIX GCC 1995 2016 24 RB_CC 1 725 GAS_MIX GCC 2002 2027 25 RB_CC 2 725 GAS_MIX GCC 2002 2027 26 RB_CC 3 725 GAS_MIX GCC 2003 2027 27 IPT 1 700 GAS_MIX GCC 2000 2025 28 EPEC 1 350 GAS_MIX GCC 2003 2022 29 TECO 1 700 GAS_MIX GCC 2000 2020 30 Bowin 1 713 GAS_MIX GCC 2003 2027 Existing Gas- and Oil-fired Thermal Plant 31 SB_TH 1 191.2 GAS_TH GTH 1971 2005 32 SB_TH 2 191.2 GAS_TH GTH 1972 2006 33 SB_TH 3 296.4 GAS_TH GTH 1974 2009 34 SB_TH 4 296.4 GAS_TH GTH 1976 2010 35 SB_TH 5 296.4 GAS_TH GTH 1978 2012 36 NB_TH 1 71.9 HOIL_2S HFO 1961 2001 37 NB_TH 2 71.9 HOIL_2S HFO 1963 2001 38 NB_TH 3 83.8 HOIL_2S HFO 1969 2001 39 BPK_TH 1 524.2 GAS_TH GTH 1983 2013 40 BPK_TH 2 524.2 GAS_TH GTH 1984 2014 41 BPK_TH 3 571.9 GAS_TH GTH 1992 2021 42 BPK_TH 4 571.9 GAS_TH GTH 1993 2021 44 KA_TH1 1 287.4 HOIL_2S HFO 2004 2033 45 PPB_TH 1 71.9 GAS_TH GTH 1981 2007 46 PPB_TH 2 71.9 GAS_TH GTH 1989 2007 47 RB_TH 1 720 GAS_TH GTH 2000 2025 48 RB_TH 2 720 GAS_TH GTH 2001 2025 Existing Lignite-fired Thermal Plant 49 MM_TH 1 69 LIGN_MM LIGN 1978 2002 50 MM_TH 2 69 LIGN_MM LIGN 1979 2002 51 MM_TH 3 69 LIGN_MM LIGN 1981 2002 52 MM_TH 4 138 LIGN_MM LIGN 1984 2014 53 MM_TH 5 138 LIGN_MM LIGN 1984 2014 54 MM_TH 6 138 LIGN_MM LIGN 1985 2015 55 MM_TH 7 138 LIGN_MM LIGN 1985 2015 56 MM_TH 8 276 LIGN_MM LIGN 1989 2018 57 MM_TH 9 276 LIGN_MM LIGN 1990 2019 58 MM_TH 10 276 LIGN_MM LIGN 1991 2021 59 MM_TH 11 276 LIGN_MM LIGN 1991 2021 60 MM_TH 12 276 LIGN_MM LIGN 1995 2024 61 MM_TH 13 276 LIGN_MM LIGN 1995 2025 Economic Base Case with NT2 – Detail 111 Code THERMAL Unit CAPACITY FUEL FUEL COMM'N RETIREM'T No. UNIT No. MW CLASS YEAR YEAR Committed Gas-fired C-C Plant (IPPs) 62 UPDC 1 700 GAS_MIX GCC 2008 2032 63 UPDC 2 700 GAS_MIX GCC 2009 2033 64 GULF 1 700 GAS_MIX GCC 2008 2032 Committed Coal-fired Plant (IPPs) 66 BLCP 1 673.3 COAL_IND COAL 2007 2031 67 BLCP 2 673.3 COAL_IND COAL 2007 2031 Existing Diesel-fired GT Plant 68 NC_GT 1 119.4 DIESEL DISE 1995 2015 69 NC_GT 2 119.4 DIESEL DISE 1995 2015 70 NC_GT 3 119.4 DIESEL DISE 1995 2015 71 NC_GT 4 119.4 DIESEL DISE 1995 2000 72 SRTGT 1 119.4 DIESEL DISE 2001 2016 73 SRTGT 2 119.4 DIESEL DISE 2001 2016 Existing tie with Malaysia 74 TNB_300 1 300 TNB TNB 2002 2050 75 TNB OLD 1 80 TNB TNB 1994 2002 Committed Gas-fired C-C Plant 114 KNCCD2 1 380.2 GAS_MIX GCC 2007 2031 ECONOMIC BASE CASE - Recommended Additions (including Reconditioning) 229 CC700 229 700 GAS_NEW GCC 2014 2038 230 CC700 230 700 GAS_NEW GCC 2014 2038 231 CC700 231 700 GAS_NEW GCC 2014 2038 232 BKT1 232 524.2 GAS_TH GTH 2014 2028 233 CC700 233 700 GAS_NEW GCC 2013 2037 234 CC700 234 700 GAS_NEW GCC 2013 2037 235 CC700 235 700 GAS_NEW GCC 2013 2037 236 SBT5 236 296.4 GAS_TH GTH 2013 2027 237 CC700 237 700 GAS_NEW GCC 2012 2036 238 CC700 238 700 GAS_NEW GCC 2012 2036 239 CC700 239 700 GAS_NEW GCC 2012 2036 240 GT230 240 230 DIESEL DISE 2011 2025 241 GT230 241 230 DIESEL DISE 2011 2025 242 CC700 242 700 GAS_NEW GCC 2011 2035 243 CC700 243 700 GAS_NEW GCC 2011 2035 244 SBT4 244 296.4 GAS_TH GTH 2011 2025 245 GT230 245 230 DIESEL DISE 2010 2024 246 CC700 246 700 GAS_NEW GCC 2010 2034 247 SBT3 247 296.4 GAS_TH GTH 2010 2024 248 CC700 248 700 GAS_NEW GCC 2009 2033 249 CC700 249 700 GAS_NEW GCC 2009 2033 250 CC700 250 700 GAS_NEW GCC 2008 2032 CANDIDATE ADDITIONS (including Reconditioning) 121 O700 1 700 HOIL_2S HFO 123 C700 1 700 COAL_IND COAL 127 CC700 1 700 GAS_NEW GCC 130 GT230 1 230 DIESEL DISE 157 SBT3 3 296.4 GAS_TH GTH 158 SBT4 4 296.4 GAS_TH GTH 159 SBT5 5 296.4 GAS_TH GTH 160 BKT1 1 524.2 GAS_TH GTH 161 BKT2 2 524.2 GAS_TH GTH 164 MM4 4 138 LIGN_MM LIGN 171 RYC1 1 301.8 GAS_MIX GCC