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Electricity PricingTheory and Case Studies

Mohan Munasinghe and Jeremy J. Warford

Published for the World BankThe Johns Hopkins University PressBaltimore and London

Copyright C 1982 by The International Bankfor Reconstruction and Development / THE WORLD BANK1818 H Street, N.W., Washington, D.C. 20433, U.S.A.All rights reservedManufactured in the United States of AmericaThe Johns Hopkins University PressBaltimore, Maryland 21218, U.S.A.

The views and interpretations in this book are the authors' and should not be attrib-uted to the World Bank, to its affiliated organizations, or to any individual acting intheir behalf.

The five maps in this book have been prepared exclusively for the convenience ofreaders; the denominations used and the boundaries shown do not imply, on the partof the World Bank and its affiliates, any judgment on the legal status of any territoryor any endorsement or acceptance of such boundaries.

Library of Congress Cataloging in Publication DataMunasinghe, Mohan, 1945-

Electricity pricing.

Bibliography: p. 368Includes index.

1. Electric utilities-Asia, Southeastern-Rates. I. Warford, Jeremy J. [1. Title.HD9685.A77S66 338.4'336362 8147613ISBN 0-8018-2703-5 AACR2

Contents

Preface xiii

Definitions xvii

Part One. Theory I

Chapter 1. Objectives and. Pricing Framework 3Background 3Purpose of the Study 7Structure of the Study 8Objectives of an Electric Power Tariff 10Tariffs Based on Long-Run Marginal Costs 11Developing Practical Tariff Structures 12Summary 13

Chapter 2. Economics of Marginal Cost Pricing 15Basic Marginal Cost Theory 15Capital Indivisibilities and Peak Load Pricing 17Extensions of Simple Models 19

Chapter 3. Prerequisites for Marginal Costing 25Load Forecasting 27System Planning 34Shadow Pricing 42

Chapter 4. Strict Long-Run Marginal Cost 52Cost Categories and Pricing Periods 52Marginal Capacity Costs 53Marginal Energy Costs and Losses 57Customer Costs 58Hydroelectric Systems 59

Chapter 5. Adjusting the Strict Long-Run Marginal Cost 66Second-Best Considerations 66Subsidized or Lifeline Prices 67Optimal Electricity Pricing in a Distorted Economy 69Financial Viability 73Other Objectives and Constraints 76Metering, Billing, ancd Customer Comprehension 79

Chapter 6. Recent Experience with Modem Pricing Structures 83Types of Tariff Structures 83Recent Empirical Evidence 87

v

Vi CONTENTS

Part Two. Case Studies 97

Chapter 7. Overview of the Case Studies 99Institutional, Technical, and Physical Characteristics 99System Losses 101System Planning 102Financial Viability 102Divergences from the Strict LRMC 103Special Metering 104Market Distortions 104Second-Best and Political Considerations 105Governmental Attitudes toward Reforms 105

Chapter 8. Indonesia 107Organization of the Sector 109Computation of the Strict LRMC for Java 116Adjustment of the Strict LRMC 128Policy Issues and Conclusions 138

Chapter 9. Pakistan 140Organization of the Sector 140Computation of the Strict LRMC 145Adjustment of the Strict LRMC 158Policy Issues-and Conclusions 165

Chapter 10. Philippines 167Organization of the Sector 167Computation of the Strict LRMC 174Adjustment of the Strict LRMC 188Policy Issues and Conclusions 198

Chapter 11. Sri Lanka 205Organization of the Sector 205Computation of the Strict LRMC 211Adjustment of the Strict LRMC 217

Chapter 12. Thailand 223

Organization of the Sector 223Computation of the Strict LRMC 231Adjustment of the Strict LRMC 236Policy Issues and Conclusions 240

Appendixes 249

Appendix A. Seminar Participants 251

Appendix B. Power Sector Statistics for Developing Countries 259

CONTENTS vii

Appendix C. Allocation of Capacity and Energy Costsbetween Peak and Off-peak Consumers 327

Appendix D. STLRMC: A Simple Computer Program forEstimating Strict Long-Run Marginal Costs 331

Calculation of Loss Multipliers 331Calculation of Marginal T&D Capacity Cost 333Calculation of Marginal Energy Cost 334Calculation of Marginal Generation Capacity Cost 335Shadow Pricing 336Listing of the STLRMC Program 338Sample Outputs from the STLRMC Program for the WAPDA

System in Pakistan 357

References 368

Index 375

TABLES

1-1. Worldwide Electricity Statistics, 1978 41-2. Power Sector Capacity, Investment, and Commercial Energy

Requirements in the Developing Countries, 1981 to 1990 6

4-1. Marginal Generating Costs in an All-Hydro System 626-1. Examples of Peak Load Tariffs 888-1. Forecasts of Future Generation Requirements 1118-2. Demand and Loss Forecast at Time of System Peak for

Java 1128-3. Incremental Demand Forecast at Time of System Peakfor

Java 1128-4. Average and Peak Loss Factors for Energy and Power at Time of

System Peak for .ava 1148-5. Generation Capacity Costfor Java (Saguling Hydro Plant First

Unit of 175 Megawatts) 1188-6. Calculation of Generation Capacity Costs for Java 1208-7A. Transmission Capacity Costs Based on the EHV/HV Investment

Plan 1218-7B. Distribution Capacity Costs Based on the MV and LV Investment

Plan 1228-8. Summary of Incremental Capacity Costs for Java 1248-9. Summary of Peak Capacity Costs for Java 1248-10. Calculation of Operation and Maintenance Costs for

Java 1268-11. Summary of Operation and Maintenance Costs for Java 127

viii CONTENTS

8-12. Energy Generation Cost Calculation for Table 8-13 1288-13. Energy and Fuel Cost 1298-14. Strict LRMC for Java 1308-15. Equivalent Strict LRMC for Java 1328-16. Typical New Tariff 1369-1. Maximum Demand, Generation, and Sales, 1970-71 to

1976-77 141 19-2. Forecast of Maximum Demand, Generation, and Sales, 1977-78 to

1982-83 1439-3. WAPDA Generation Expansion Program 1449-4. Costs of Generation Capacity at the Busbar 1489-5. WAPDA Investment Program, 1980 to 1990 1499-6. Projected System Peak Demand at EHV/HV, MV, and LV,

1979 to 1990 1509-7. Incremental Peak Demand at EHV/HV, MV, and LV,

1979 to 1990 1529-8. Marginal Energy Costs 1539-9. WAPDA System Loss Factors, 1979 to 1990 1549-10. Customer Costs 1569-11. Capacity Costs 1569-12. Summary of Strict Long-Run Marginal Capacity and Energy Costs

(DP) 1579-13. Summary of Main Features of the Existing WAPDA

Tariffs 1609-14. LRMC and Proposed New WAPDA Power Tarifffor

1980-81 162

10-1. NPC System Operations for 1977 17210-2. Physical Targets in NPC'S Power Expansion Program,

1978 to 1987 17210-3. Annual Incremental Capacity Cost at the HV Levelfor

NPC 17610-4. Incremental Energy-Related Costs at the HV Levelfor

NPC 17710-5. Marginal Cost Structure for NPC 17810-6. Annual Incremental Capacity Cost for Private Electric

Utilities 18110-7. Annual Incremental Energy-Related Costs for Private Electric

Utilities 18110-8. Annual Incremental Customer-Related Costs at the LV Level for

Private Electric Utilities 18210-9. Marginal Cost Structure at the LV Levelfor Private Electric

Utilities, from the Utilities' Viewpoint 182

CONTENTS ix

10-10. Marginal Cost Structure Cost Allocation for Private ElectricUtilities, from the Economy's Viewpoint 183

10-11. Annual Incremental Capacity Cost at the LV Level for ElectricCooperatives 184

10-12. Incremental Energy-Related Costs at the LV Levelfor ElectricCooperatives 185

10-13. Annual Incremental Customer-Related Costs for ElectricCooperatives 186

10-14. Private Marginal Cost Structure at the LV Levelfor ElectricCooperatives, from the Cooperatives' Viewpoint 187

10-15. Private Marginal Cost Structure at the LV Level for ElectricCooperatives, from the Economy's Viewpoint 187

10-16. Average Electricity Tariffs in 1978 18910-17. Financial Cost Structure of Energy Sales for NPC, 1978 19110-18. Financial Cost Structure of Energy Sales for Private Electric

Utilities, 1978 19210-19. Financial Cost Structure of Energy Salesfor Electric

Cooperatives, 1978 19310-20. Average Tariffsfor NPC, 1978 19410-21. Allocation of Chargesfor NPC 19510-22. Average Tariffs fbr Private Electric Utilities, 1978 19610-23. Allocation of Charges for Private Utilities 19610-24. Average Tariffsfor Electric Cooperatives, 1978 19710-25. Allocation of Charges for Electric Cooperatives 19711-1. CEB Energy and Power Balance 21011-2. Peaking Hydro Capacity Costs 21311-3. Load, Demand, and Loss Forecasts 21411-4. Incremental Load or Demand Forecast 21411-5. HV Transmission Investment Costs 21611-6. MV Distribution Investment Costs 21711-7. LV Distribution Investment Costs 21811-8. Incremental Costs Summary (at Source) 21911-9. Marginal Energy Costs 21911-10. Summary of Strict LRMC of Capacity and Energy (BP) 22011-11. Standard Costs for Service Connections 22011-12. Summary of Existing Tariff 22212-1. Number of Customers of the Electric Power Sector, by Type of

Customer 22712-2. Energy Consumption, by Type of Customer 22712-3. Sales of Power and Energy by EGAT to Consumers 23012-4. Marginal Capacity Costs for EGAT 23312-5. Marginal Capacity Costsfor MEA 23512-6. Marginal Capacity Costs for PEA 235

x CONTENTS

12-7. Consumer-Related Costs for MEA and PEA (with ShadowPrices) 236

12-8. Total Marginal Cost of EGAT, MEA, and PEA (without ShadowPrices) 237

12-9. Total Marginal Cost of EGAT, MEA, and PEA 23812-10. Adjusted Marginal Cost of EGAT, MEA, and PEA 24312-11. Average Upper and Lower Limit of Poverty Band of Representative

Households, Adjusted by 1977 Consumer Price Index 244

FIGURES2-1. Supply and Demand for Electricity Consumption 162-2. The Effect of Capital Indivisibilities on Price 182-3. Peak Load Pricing Model 192-4. Use of Price Feedback in Estimating Tariffs Based on

LRMC 202-5. Relation between Outage Costs, Supply Costs, and Total Costs at

the Optimum Reliability Level 22

3-1. Schematic of a Simple Electric Power System 283-2. Power and Energy Flows, Consumption, and Losses in a Typical

Power System 303-3. Size and Timing of Additional Generating Plants Needed to Meet

the Peak Demand for Power 383-4. Types of Generating Plants Needed to Meet the Annual Load

Duration Curve 39

4-1. Typical Annual Load Duration Curve 544-2. Forecast of Demandfor Peak Power 544-3. Annual Variation of New Water Flows into the Reservoir in an

All-Hydroelectric System 604-4. Typical Daily Load Duration Curves for a Mixed Hydro-Thermal

System 634-5. Imputed Value of Water in a Mixed Hydro-Thermal

System 64

5-1. Economic Basis for the Social or Lifeline Rate 685-2. Supply and Demand for Electricity 705-3. The Metering Decision to Implement a Two-Period Time-of-Day

Tariff 806-1. Structure of Increasing and Decreasing Block Tariffs 848-1. Typical Daily Load Curves for Java 1158-2. Typical Daily Load Duration Curves for Java 1168-3. Daily Load Profile for a LV Consumer 134

CONTENTS Xi

9-1. Daily Load Curve for December 20, 1978 1469-2. Annual Load Duration Curve for the WAPDA Grid System,

1979 147

11-1. Daily Load Curves for CEB, September 1978 20811-2. Synthesized Annual Load Duration Curve, 1978 20911-3. CEB Energy and P'ower Balance of Supply and Demand 21212-1. Characteristics of the EGAT System 22812-2. Diagram of the E(3AT System 23112-3. Flowchart for Calculation of the Strict LRMC 242C- 1. Plant Costs and Annual Load Duration Curve 328

MAPS1. Indonesia (Java): Principal Power Stations and Transmission Lines in

the PLN System 1082. Pakistan: Principal Power Stations and Transmission Lines in the

WAPDA System A1423. Philippines (Luzon Grid): Principal Power Stations and 230 KV.

Tranmission Lines in the NPC System 1684. Sri Lanka: Principal Power Stations and Tranmission Lines in the CEB

System 2065. Thailand: Principal Power Stations and Transmission Lines in the EGAT

System 224

Preface

THE RAPIDLY INCREASING COST OF ELECTRIC POWER in recent years hasbrought about a growing awareness of the importance of pricing policies inmaximizing the net economic benefits of consumption and avoiding waste.Although the theoretical lprinciples governing optimal pricing strategies havelong been understood, their practical application to the energy sector in gen-eral, and to electric power in particular, has not been seriously pursued untilrecently. Increasing unit costs, however, have provided the stimulus for achange in approach, and there is now a good deal of evidence that marginalcost pricing-hitherto thought to be a somewhat academic concept-is be-coming accepted as an important criterion that should be considered in deter-mining electric power tariffs. A previous World Bank publication, Electric-ity Economics, by Ralph Turvey and Dennis Anderson (1977), has helped toencourage this change in attitude.

The theory and practice of marginal cost pricing covers far too muchground to be dealt with in detail within a volume of this size. Accordingly,we have had to make two principal compromises. First, in the attempt tomaintain the balance between theory and practice, the methodology is devel-oped with the emphasis on its operational usefulness. The basic theory ofmarginal cost pricing is explained, but readers are referred to other sourcesfor the finer points that are more likely to be of interest to purists. Indeed,practitioners of marginal cost pricing and policymakers recognize that lackof data and other constraints will invariably limit the applicability of themore esoteric theoretical aspects, especially in developing countries.

The second and related compromise concerns the relative attention paid tothe two stages of tariff setting-first, the estimation of the strict long-runmarginal costs (LRMC) to meet the objective of economically efficient pric-ing, and next, the adjustments to the strict LRMC required to derive a realis-tic tariff schedule that satisfies other constraints, such as financial require-ments, social-subsidy considerations, fairness, and metering and billingdifficulties.

We feel that the adjustment process is at least as important as the calcula-tion of the strict LRMC in setting practical tariffs in developing countries.Regrettably, the past literature has concentrated mainly on the strict LRMC.Therefore, this book seeks only to explain and interpret clearly the existingtheoretical basis for estimating the strict LRMC and to outline a practicalmethodology for applying it. The principles and practice of adjusting the

xiii

XiV PREFACE

strict LRMC are, however, treated in greater detail, including the develop-ment of a new analytical framework for making economic second-best ad-justments and estimating subsidized lifeline prices for poor consumers.

This tradeoff between analytical rigor and practical applicability, on theone hand, and between calculating and adjusting the strict LRMC, on theother hand, are reflected in both the methodology and case study sections. Inthe final analysis, we have deliberately given more weight to practical issuesthat are of greater interest to tariff analysts and policymakers, who are likelyto be our principal audience.

This book consists of two parts. The first part contains a summary of theeconomic principles underlying marginal cost pricing for electric power, andemphasizes the importance of the adjustments that need to be made to thestrict LRMC to reflect the various economic, social, and engineering objec-tives and constraints that are actually faced by policymakers in the energysector. The second part consists of case studies prepared in collaborationwith the staff of power and energy authorities in five developing countries inAsia. These studies were associated with the first two seminars in a seriesthat is being conducted by World Bank staff in various parts of the world.

The case studies all follow a two-stage procedure in which the LRMC ofelectric power is used to weigh the costs and benefits of other policy objec-tives that might be addressed through the medium of power pricing. LRMCis therefore treated largely as a benchmark by which other economic and so-cial objectives may be consciously judged. It is our opinion that local under-standing of these factors is absolutely crucial for successful tariff setting.The pervasive effects of electricity pricing policies clearly indicate that thetraditional narrowly focused public utility approach, which concentrates al-most exclusively upon financial and engineering analysis to the detriment ofeconomic and social criteria, is inadequate. The concerns expressed in thecase studies are ample evidence that this is so, and it is to be hoped that theapproach they follow, which can readily be adapted to energy pricing studiesin general, will be of value to power and energy authorities in other coun-tries in addressing the complex and sensitive issues relating to electricitypricing policy.

The lists of persons to whom the authors are indebted for assistance in thecompletion of this book is long. Most important, we would like to thank allthe participants in the seminars- their names are listed in Appendix A.Among them we wish to give special mention to major contributors to thecase studies: Soejitno Sujanto, Djaya Santoso, Muhammed Jahangir,K.K.Y.W. Perera, Nelson Wijemanne, S. M. Christy, Pratin Pathanaporn,and Viset Choopiban. Other contributors who could not attend the seminars,but to whom we are equally indebted, are Malaine Manzo Valenzuela andIqbal Kahn, as well as Mark Gellerson, who helped to prepare one of the

PREFACE XV

case studies. The assistance of Rajesh Pradhan, Karl Jechoutek, Kam Kalaji,and Cecile Rivera in preiparing two of the appendixes is acknowledged withthanks.

We are also grateful for the encouragement and technical advice receivedfrom many colleagues at the World Bank, including Yves Rovani, RichardSheehan, James Fish, John Davis, Edwin Moore, Dennis Anderson, Anan-darup Ray, Jack Beach, Frank Lamson-Scribner, Rafael Moscote, BemardMontfort, Esref Erkmen, Karl Stichenwirth, John Sneddon, Cheruvari Chan-dran, Vatsal Thakor, John Vance, Colin Warren, Ibrahim Elwan, KarlSchmedtje, Joe Gilling, and Bahman Abadian. We wish to thank Judy Barryfor editorial assistance and Sibo Kong, Noriko Clark, Andie Dufigan, andConnie Villacorte for secretarial help.

Among those outside the Bank, Ralph Turvey, Fred McCoy, and ReneMales offered helpful comments while Jan Paul Acton and Allen Miedemaprovided useful information on recent tariff studies in the United States.

Virginia deHaven Hitchcock edited the manuscript for publication. BrianJ. Svikhart directed design and production. Chris Jerome read and correctedproofs. Raphael Blow prepared the figures. The maps were compiled byYung Koo and Josephine Cullen Dugan and drawn by Larry A. Bowring un-der the supervision of the World Bank's Cartography Division. Ralph Wardand James Silvan indexed the text. Joyce C. Eisen designed the cover.

The responsibility for all errors and omissions is, of course, ours.Finally, we owe much to our families-our respective wives Sria and

Beryl, and children, Anusha and Ranjiva, and Susan and Ian-for their pa-tience and understanding while this book was being written. The volume isdedicated to our children.

MOHAN MUNASINGHEJEREMY WARFORD

Definitions

A&G Administrative and general costsAIC Average incremental costARI Accounting rate of interestB BahtBP Border priceBTU British thermal unitCCF Consumption conversion factorCEB Ceylon Electricity Board (Sri Lanka)CES Constant elasticity of substitutionCF Conversion factorc.i.f. Cost, insurance, freightD DemandDP Domestic priceECF Electricity conversion factorEGAT Electricity Generating Authority of ThailandEHV Extra high voltageESWR Efficiency shladow wage ratef.o.b. Free on boardFTER Free trade exchange rateGT Gas turbineHSD High speed dieselHV High voltageIAEA International Atomic Energy AuthorityIEE Institution of Electrical Engineers (U.K.)IEEE Institute of Electrical and Electronic Engineers (U.S.)KESC Karachi Electric Supply Corporation (Pakistan)LDC Load duration curveLF Load factorLOLP Loss of load probabilityLRMC Long-run marginal costLV Low voltageMC Marginal costMCB Border-priced marginal costMEA Metropolitan Electricity Authority (Thailand)MECO Manila Electric Company (Philippines)MOC Marginal opportunity costMSB Marginal social benefitMSC Marginal social costMU Marginal utility

xvii

xviii DEFINITIONS

MV Medium voltageMW MegawattNB Net benefitNEA National Electrification Administration (Philippines)NPC National Power Corporation (Philippines)OC Outage costOCC Opportunity cost of capitalOER Official exchange rateO&M Operation and maintenance costsp PesoPEA Provincial Electricity Authority (Thailand)PF Power factorPLN Perusahaan Umum Listrik Negara (Indonesia)R ReliabilityRM Reserve marginRp RupiahRs RupeeSC Supply costSCF Standard conversion factorSER Shadow exchange rateSRMC Short-run marginal costSWR Shadow wage rateTB Total benefitTC Total costT&D Transmission and distributionTOU Time of useWAPDA Water and Power Development Authority (Pakistan)

Part One

Theory

Chapter 1

Objectives and Pricing Framework

ELECTRIC POWER IS A CRUCIAL FORM OF ENERGY in the world today. In 1980about 950 terawatt-hours of electricity were generated in the developingcountries. Production of electrical energy in the third world will continue togrow at an average rate of 8.5 percent annually, and will require investmentsof approximately $414 billion during 1980-89.' In comparison, about 2,350terawatt-hours of electricity were generated in the United States in 1980.During 1980-89 consumption in the United States will grow at an averagerate of a little more than 4 percent, requiring about $430 billion to meet theinvestment requirements .2

Background

A summary of selectedl statistics for the electric power sector in the devel-oping countries and other regions of the world during 1978 is given in Table1-1. The third world contains more than 2 billion inhabitants, or about halfthe world's population, having an average per capita income of approxi-mately $650-less than a third of the world average. Access to electricity inthe developing countries is poor because more than two-thirds of the popula-tion live in rural areas that are sparsely electrified. In 1978 the developedcountries produced more than seven times as much electrical energy as thedeveloping countries although their population was only about one-third aslarge. The per capita consumption of electricity in the third world, therefore,is about one-twentieth the corresponding value for the developed countriesand less than a fifth of the world average. Similarly, the installed generatingcapacity and the total commercial energy consumption in the developingcountries lags far behind that for the rest of the world. This underlines thewell-known correlation between per capita income and energy use.

1. Investment figures in this chapter are given in constant 1980 U.S. dollars. See AppendixB for details of electricity statistics in developing countries.

2. U.S. Department of Energy, "Report No. DOE/RG-0036" (Washington, D.C. June1980; processed); and "Thirtieth Annual Electrical Energy Forecast," Electrical World (Sep-tember 15, 1979), pp. 75-84. In this book "billion" is used to mean "thousand million."

3

4 THEORY

Table 1-1. Worldwide Electricity Statistics, 1978

Developed CentrallyDeveloping market planned

Item countries economies economies World

PopulationUrban (percentage of total) 30 75 35 40Rural (percentage of total) 70 25 65 60Total (billions) 2.08 0.78 1.36 4.24

Gross national product (GNP) per capita(dollars) 650 8,000 1,150 2,100

Access to electricity (percent), 29 >90 n.a. n.a.Electricity generation

Total (terawatt-hours) 696 5,070 1,851 7,617Thermal (terawatt-hours) 377 3,616 1,534 5,527Hydro (terawatt-hours) 307 982 269 1,558Nuclear (terawatt-hours) 12 472 48 532Per capita (kilowatt-hours) 331 6,509 1,365 1,803

Installed capacityTotal (gigawatts) 177 1,265 387 1,829Thermal (gigawatts) 105 900 308 1,313Hydro (gigawatts) 70 270 69 409Nuclear (gigawatts) 2 95 10 107Per capita (kilowatts) 0.085 1.624 0.285 0.433

Annual commercial energy usebTotal (million metric tons of oil

equivalent) 689 3,613 2,004 6.304Per capita (metric tons of oil

equivalent) 0.33 4.63 1.47 1.49Tons of oil equivalent per thousand

dollars of GNP 0.51 0.58 1.28 0.71Electricity generated/commercial energyb 0.253 0.351 0.231 0.302Electricity generated per dollar of GNP

(kilowatt-hours) 0.51 0.81 1.19 0.86Average annual growth of electricity

consumption, 1973-78 (percent) 8.12 3.49 6.44 4.55Average electricity price

(cents per kilowatt-hour), 3.4 n.a. n.a. n.a.

n.a. Not available.Note: See Appendix B for a list of countries in each region and more disaggregate data for thedeveloping countries. See list of definitions for unit equivalencies.I Access to electricity defined by fraction of total population living in areas where electricityservices are provided.I Commercial energy includes oil, coal, gas, hydroelectric, nuclear, and geothermal sources. Imillion metric tons of oil equivalent = 101 metric tons of oil equivalent = 1.47 million metrictons of coal equivalent = 41 x 10"2 BTU. I terawatt-hour of electricity a year is assumed to beequivalent to 0.25 million metric tons of oil equivalent of fossil fuel, based on the conversionefficiency of an average thermal power plant.c Average price = sales revenue/electrical energy consumed.Source: U.N. and World Bank data.

OBJECTIVES AND PRICING FRAMEWORK 5

In the developing countries electricity consumption grew at an average ofmore than 8 percent a year during 1973-78-more than twice the rate forthe developed countries. As development continues, the future demand forelectricity in the third world will tend to grow faster than the world average.In the past, the convenience and relatively low price of electricity in mostdeveloping countries helped to promote electricity use. As electricity andother energy prices rise during the next decade, however, the growth of de-mand is unlikely to accelerate further.

The third world's investment in the power sector and its fossil fuel re-quirements for the next decade are summarized in Table 1-2. The tableshows how capital intensive the power sector is. During the next decade, theinstalled capacity in the developing countries will more than double, requir-ing investments averaging more than $40 billion a year. The real costs of akilowatt will continue to rise for several reasons. These include the shift tomore costly coal and nuclear plants following the oil crisis, the reducedavailability of cheaply exploitable hydroelectric sources, and the inability torealize further significant economies of scale, particularly as systems expandinto regions of lower consumer density, such as small towns and rural areas.

Commercial energy requirements for producing electricity, including fos-sil fuels used in thermal generation, will more than double in the next tenyears, growing at an average rate of about 8.5 percent a year. The share ofoil-fired generation in total thermal generation is expected to decrease signif-icantly, however, from 57 percent in 1980 to 39 percent in 1990. Althoughnuclear and geothermal generation will grow dramatically, their contributionin 1990 will still be relatively small because of their small starting base in980.The large investments in, and rising costs of, power have highlighted the

need for increased economic efficiency in the electricity sector. Tradition-ally, the greatest emphasis has been placed on improving technical and fi-nancial efficiency through least-cost, long-range planning for system expan-sion, optimizing short- and medium-term system operation, and providingbetter management of utilities. These considerations on "the supply side" ofthe supply-demand equation have been tackled with a remarkable degree ofsuccess, usually by engineers using technically and financially oriented solu-tions. More recently, power economists have focused attention on the objec-tives of economic efficiency in the national context. These developmentshave had a growing and significant effect on "the demand side," chieflythrough the application of appropriate tariff policies based on the principlesof marginal cost pricing. On the supply side as well, the acceptance of eco-nomic arguments is reflected in the use of economic opportunity costs.These costs are represented by shadow prices that are the true costs of eco-nomic resources and not purely financial or accounting costs.

6 THEORY

Table 1-2. Power Sector Capacity, Investment, and Commercial EnergyRequirements in the Developing Countries, 1981 to 1990

Plant type

Item Thermal Hydro Nuclear Geothermal Total

Power sector requirementsInstalled capacity, 1980 (giga-

watts) 150 101 4 - 255Unit cost (dollars per kilowatt)a 1,160 1,730 1,920 2,100 -Capacity increments (gigawatts)

1981-85 62.4 47.4 6.8 1.0 117.61986-90 81.7 54.3 27.9 0.9 164.81981-90 144.1 101.7 34.7 1.9 282.1

Investment required (billionsof dollars)1981-85 72 82 13 1 1691986-90 95 94 54 2 2451981-90 167 176 67 4 414

Commercial energy required toproduce electricity (millionbarrels a day of oil equivalent)b

1980 2.54 2.10 0.08 0.01 4.73(56.7;1l.4;31.9)c

1985 3.90 3.13 0.27 0.05 7.35(47.2;17.9;34.9),

1990 5.34 4.11 1.20 0.08 10.73(38.6;21 .2;40.2)c

Growth rate 1981-90 (percent) 7.7 6.9 31.1 23.1 8.5(3.7;14.6;10.3)d

Note: See Appendix B for a list of countries amd more disaggregate data. All monetary valuesare given in 1980 constant U.S. dollars.- Not applicable.I Includes incremental cost of transmission and distribution facilities.bCommercial energy includes oil, coal, gas, hydroelectric, nuclear, and geothermal sources. Imillion barrels a day of oil equivalent = 50 million tons of oil equivalent a year. All nonther-mal electricity generated transformed into millions of barrels a day of oil equivalent using theconversion efficiency of an average thermal power plant: I terawatt-hour a year = 109 kilowatt-hours a year = 0.25 million metric tons of oil equivalent = 0.005 million barrels a day of oilequivalent.c Percentage shares of oil, gas, and coal-lignite are given in parentheses.I Growth rates of oil, gas, and coal-lignite are given in parentheses.Source: World Bank data.


Purpose of the Study

This book focuses on the importance of adopting correct power pricingpolicies to maximize the net economic benefits of electricity consumption tosociety. It reports on the progress of the pricing reform program in the elec-tric power sector that is underway in the developing world with the activeencouragement of the World Bank. A valuable contribution to this effortwas the book Electricity Economics by Turvey and Anderson, which helpedstimulate an awareness of the importance of reflecting long-run marginaleconomic costs in pricing power in developing countries.3 The further stim-ulus of rapidly increasing electricity costs has caused this approach to bebetter understood by power authorities in the third world than in many in-dustrialized countries.

More specifically, the Bank's involvement in electric power project andsector work in the developing countries and the continuing exchange of in-formation on pricing issues with utility companies have resulted in the syn-thesis and practical application of the pricing principles described in thisbook. Convincing national authorities that pricing based on marginal cost isnot an academic exercise also has been important. Pricing policy is a valu-able "soft" tool for managing demand and reducing electricity consump-tion. The effects of correct pricing policies are enhanced by coordinatingtheir use with the other soft techniques of demand management, such as taxand financial incentives and education and propaganda, as well as with thehard methods of demand management, including direct control of loads, cur-tailment, and so forth. The integrated use of soft and hard techniques of de-mand management is most important because the former are more effectivein the long run, whereas ihe latter have greater effect in the short run.

Because of the lack of data and other constraints, the search for exces-sively precise cost estimates and pricing policies is likely to be difficult andoften even counterproductive. Utilities have been encouraged to make "backof the envelope" cost estimates based on relatively simple considerations.These, however, may be a large improvement over traditional costingmethods, because they at least indicate trends in economic cost. It is alsonecessary to instill confidence in power sector institutions in the developingcountries to conduct such analyses and to persuade them to refrain from ex-cessive reliance on foreign experts. External consultants may lack the under-standing or "feel" for the developmental issues that are so critical in creat-ing truly effective power pricing policies. All too frequently, the reports are

3. Ralph Turvey and Dennis Anderson, Electricity Economics (Baltimore, Md.: JohnsHopkins University Press, 1977).

8 THEORY

not applicable and end up on dusty bookshelves-a costly experience for de-veloping countries.

The approach of "learning by doing" has been pursued by the powerpricing authorities of developing countries with considerable success. Thisprocess is considered absolutely essential, given the potentially importantrole that power pricing policy can play. The effects of the self-help approachare pervasive. Clearly, understanding domestic economic and social objec-tives and constraints is an indispensable part of the successful tariff analysis.A team of local engineers, economists, and financial analysts is more likelyto have this understanding than a foreign consultant. This is particularly truein the third world, in which the range of economic and social policy tools atthe disposal of governments is so limited and in which public revenues are ata premium. Also, in view of the rapid changes that may take place in acountry's official economic and social objectives, the value of the self-helpapproach is clear. The government machinery must be able to update and re-vise tariff analysis constantly to accommodate such changes. In brief, tariffrevision and policy should not be treated as a once-and-for-all, ad hoc effortto be carried out by external consultants, but rather as an important, contin-uous in-house activity. Therefore, the "learning by doing" or "institution-building" approach that the Bank has actively encouraged is of critical im-portance to all developing countries.

Structure of the Study

The first part of the book begins with a discussion of the many and oftenconflicting national and sectoral objectives of electricity pricing. Next, atwo-stage procedure for setting tariffs is outlined that meets these objectives.First the strict long-run marginal costs (LRMC) of electricity supply arecomputed to satisfy the criterion for economic efficiency. Then, the strictLRMC is adjusted to arrive at an appropriately realistic tariff structure thatmeets various other goals and constraints, including social-subsidy consider-ations for poor consumers, the financial viability of the electric power sec-tor, simplicity of metering and billing, and so on.

Part One continues with an overview of the economic principles underly-ing marginal cost pricing, followed by a discussion of how these basicmodels may be modified to satisfy more complex situations in the realworld. Next, problems involved in the second stage of making tariffs arediscussed, that is, adjusting the strict marginal cost price to reflect systemat-ically the various economic, social, and engineering constraints that mustactually be faced. Relatively greater emphasis is placed on this stage of tariffsetting. Thus a systematic procedure based on shadow prices is proposed,which makes economic second-best adjustments to compensate for distor-


tions in the prices of other goods and services in the economy. In particular,given the importance of integrating the pricing of alternative forms of en-ergy, such as oil, gas, coal, and traditional fuels, in a consistent manner,power prices need to be modified because of distortions in the prices ofother fuels.

Ideally, reform of electric power pricing policy should be considered asonly one aspect of a comprehensive analysis and revision of all energyprices.4 Indeed, all aspects of planning within the energy sector should becoordinated, as discussed in Chapter 3. In practice, however, many con-straints, such as the inefficient pricing of other energy sources, may have tobe accepted as given when electricity tariffs are set. In this context, themethodology discussed in this book is equally applicable to energy pricingin general. The first task of energy pricing should be to estimate an econom-ically efficient pricing st-ucture corresponding to the strict marginal (oppor-tunity) cost of various fuels, and then to adjust that structure as required toachieve other financial, economic, or social goals.

To broaden the Bank's experience in the practical application of the prin-ciples of marginal cost pricing in the electric power field, two power tariffseminars were conducted in Asia. The seminars were designed to increaseawareness and understanding of the roles and limitations of these techniquesamong utility companies in the developing countries. Part Two of the bookincludes five case studies prepared mainly in response to these seminars byparticipants representing several Asian power utilities, with some guidanceand editing by the authors. An introductory chapter reviews, compares, andanalyzes the principal issues and lessons to be learned from the tariffstudies. Specific contributors to Part Two include: Soejitno Sujanto andDjaya Santoso (Indonesia); Muhammed Jahangir and Iqbal Khan (Pakistan);Malaine Valenzuela and coworkers (Philippines); K. K. Y. W. Perera, Nel-son Wijemanne, and S. M. Christy (Sri Lanka), and the Electricity TariffConimittee (Thailand).

The seminars were held in Thailand in June 1978 and in Indonesia in Jan-uary 1979 and were attended by representatives from twelve Asian coun-tries.5 The countries represented were Burma, Fiji, Indonesia, Korea, Ma-laysia, Nepal, Pakistan, Papua New Guinea, Philippines, Singapore, Sri

4. For details, see Mohan Munasinghe, "An Integrated Framework for Energy Pricing inDeveloping Countries," Energy Journal, vol. I (July 1980), pp. 1-30; also available as Reprintno. 148 from the World Bank, Washington, D.C.

5. More recently, similar seminars have been successfully conducted in Colombia (Novem-ber 1979) and Brazil (July 1980) for twenty-six Latin American and Caribbean countries, and inKenya (June 1980) for twelve African countries. See Mohan Munasinghe and Colin J. Warren(eds.), Power Tariffs: Case Studies in Latin America and the Caribbean (Washington, D.C.:World Bank, 1981).

10 THEORY

Lanka, and Thailand.6 Some of the participants had several years' experi-ence working with the World Bank in this field; others had none. The semi-nars were successful, resulting in a high level of interaction among the par-ticipants. They helped both the authors and those participants that werefurther along in their thinking to resolve several conceptual and practicalproblems. In turn, the more experienced delegates were able to help otherparticipants realize that the seminar was critical to their own countries' ef-forts to ensure the rational use of increasingly scarce energy resources. Thefrank exchange of information on the common practical and sociopoliticaldifficulties faced by electric power sector authorities was as valuable to theparticipants as was the knowledge gained regarding the principles and meth-odology of the LRMC approach. These pricing studies have been used sub-sequently as the bases for revising both the level and structure of existingpower tariffs in many of the countries concerned. This is convincing evi-dence of the increasing importance of the marginal cost methodology.

The case studies illustrate the practical problems of applying marginalcost pricing techniques. As might be expected, they handle several concep-tual issues in different ways that may not fully satisfy the theoretical stan-dards of purists in the marginal cost field. Without exception, these studiesindicate an awareness of the fact that the real costs to the economy are themarginal costs. Even when tariff makers are constrained by other economicand social objectives in achieving a long-run marginal tariff structure that isbased on cost, such studies indicate to policymakers the economic cost ofmeeting these other objectives. Marginal cost is, therefore, the benchmarkby which the achievement of those other socioeconomic objectives can beconsciously judged. Whatever pricing policy eventually emerges, it seems tobe crucial to know at least the magnitude and structure of the LRMC of sup-ply. Such an inquiry may be conducted along the lines presented in thisbook.

Objectives of an Electric Power TariffThe modern approach to electric power pricing recognizes the existence of

several objectives or criteria, not all of which are mutually consistent. First,national economic resources must be allocated efficiently, not only amongdifferent sectors of the economy, but also within the electric power sector.This implies that prices that reflect cost must be used to indicate to the elec-tricity consumers the true economic cost of supplying their specific needs,so that supply and demand can be matched efficiently.

Second, certain principles relating to fairness and equity must be satisfied,

6. The full list of seminar participants is given in Appendix A.


including: (a) allocating costs among consumers according to the burdensthey impose on the system; (b) assuring a reasonable degree of price stabilityand avoiding large price fluctuations from year to year; and (c) providing aminimum level of service to persons who may not be able to afford the fullcost.

Third, the power prices should raise sufficient revenues to meet the finan-cial requirements of the sector, as described earlier. Fourth, the structure ofelectric power tariffs must be simple enough to facilitate the metering andbilling of consumers. Fifth, and finally, other economic and political re-quirements must also be considered. These might include, for example, sub-sidized electricity supply to certain sectors to enhance growth or to certaingeographic areas for regional development.

Since the above criteria often conflict with one another, it is necessary toaccept certain tradeoffs between them. The LRMC approach to setting pricesis both rigorous and flexible enough to provide a tariff structure that is re-sponsive to these basic objectives.

Tariffs Based on Long-Run Marginal Costs

A tariff based on LRMC is consistent with the first objective of efficientlyallocating resources. The traditional accounting approach is concerned withrecovering historical, or stnk, costs. In calculating the LRMC the importantconsideration is the amount of future resources used or saved by consumerdecisions. Since electricity prices are the amounts paid for increments ofconsumption, they should generally reflect the incremental cost incurred.Supply costs increase if existing consumers increase their demand, or if newconsumers are connected to the system. Therefore, prices that act as a signalto consumers should be related to the economic value of future resources re-quired to meet consumption changes. The accounting approach that uses his-torical assets and embedded costs implies that future economic resourceswill be as cheap or as expensive as in the past. This could lead to overin-vestment and waste, or underinvestment and the additional costs of unneces-sary scarcity.

To promote better utilization of capacity, and to avoid unnecessary invest-ments to meet peak demands, which tend to grow very rapidly, the LRMCapproach structures prices so that they vary according to the marginal costsof serving demands: by diifferent consumer categories, in different seasons,at different hours of the (Jay, by different voltage levels, in different geo-graphic areas, and so on.

In particular, with an arppropriate choice of the peak period, structuringthe tariffs based on LRMC by time of day generally leads to the conclusionthat peak consumers should pay both capacity and energy costs, whereas

12 THEORY

off-peak consumers should pay only the energy costs. Similarly, analysis ofLRMC by voltage level usually indicates that the lower the service voltage,the greater the cost that consumers impose on the system.

The structuring of tariffs based on LRMC also meets requirements (a) and(b) of the second, or fairness, objective mentioned above. The economic re-source costs of future consumption are allocated as much as possible amongthe customers according to the incremental costs they impose on the powersystem. In the traditional approach, fairness was often defined rather nar-rowly and led to the arbitrary allocation of accounting costs to various con-sumers. Because the LRMC method deals with future costs over a longperiod-for example, at least five to ten years-the resulting prices in con-stant terms tend to be quite stable over time. This smoothing out of costsduring a long period is especially important given the large size or "lumpi-ness" of power system investments.

Using economic opportunity costs (or shadow prices, especially for capi-tal, labor, and fuel) instead of purely financial costs and taking externalitiesinto consideration whenever possible also link the LRMC method to efficientresource allocation.

Developing Practical Tariff Structures

The first stage of the LRMC approach is the calculation of the pure orstrict LRMC that reflects the criterion of economic efficiency. If price wasset strictly equal to LRMC, consumers could indicate their willingness to payfor more consumption, thus signaling the justification of further investmentto expand capacity.

In the second stage of setting tariffs, ways are sought to adjust the strictLRMC to meet the other objectives, among which the financial requirementis most important. If prices were set equal to the strict LRMC, a financialsurplus would be likely. This is because marginal costs are higher than aver-age costs when the unit costs of supply are increasing. In principle, financialsurpluses of the utility may be taxed away by the state, but in practice theuse of power pricing as a tool for raising government revenues is usually po-litically unpopular and is rarely applied. Such surplus revenues also can beutilized in a way that is consistent with the other objectives. For example,the connection charges can be subsidized without violating the LRMC price,or low-income consumers could be provided with a subsidized block of elec-tricity to meet their basic requirement, thus satisfying sociopolitical objec-tives. Conversely, if marginal costs are below average costs-typically as aresult of economies of scale-then pricing at the strict LRMC will lead to afinancial deficit. This will have to be made up, for example, by higherlump-sum connection charges, by flat rate charges, or even by governmentsubsidies.


Another reason for deviating from the strict LRMC arises because ofsecond-best considerations, When prices elsewhere in the economy do notreflect marginal costs, especially for electric power substitutes and comple-ments, then departures fromn the strict marginal cost pricing rule for electric-ity services would be justified. Clearly the first-best solution would be to re-move the price distortions in the other parts of the economy. Thesecond-best adjustments to electricity prices arise only because the first-bestoption is not practically feasible.

For example, in rural areas inexpensive alternative energy may be avail-able in the form of subsidized kerosene or firewood. In this case, pricingelectricity below the LRMC may be justified to prevent excessive use of thealternative forms of energy. Similarly, if incentives are provided to importprivate generators and their fuel is also subsidized, then charging the fullmarginal cost to industrial consumers may encourage them to purchase theirown or captive power plant. This is economically less efficient from a na-tional perspective. Since the computation of the strict LRMC is based on thepower utilities' least-cost expansion program, LRMC may also need to bemodified by short-term considerations if previously unforeseen events makethe long-run power systemr plan suboptimal in the short run. Typical exam-ples of such situations include a sudden reduction in the growth of demandand a large excess of installed capacity, which may justify slightly reducedcapacity charges, or a rapid increase in fuel prices, which could warrant ashort-term fuel surcharge.

As discussed earlier, the LRMC approach permits a high degree of tariffstructuring. Practical data constraints and the need to simplify metering andbilling procedures, however, usually require that tariffs be differentiatedonly by: (a) principal customer categories-residential, industrial, commer-cial, special, rural, and so on; (b) voltage levels (high, medium, and low);(c) time of day (peak, off-peak); and (d) geographic region. Finally, variousother constraints also may be incorporated into tariffs based on the LRMC,such as the political requirement of having a uniform national tariff, subsi-dizing rural electrification, and so on. In each case, however, such devia-tions from the LRMC will impose an efficiency cost on the economy.

Summary

In the first stage of calculating the LRMC, the objective of economic effi-ciency in setting tariffs is satisfied, because the method of calculation isbased on future economic resource costs rather than on sunk costs, and alsoincorporates economic considerations, such as shadow prices and external-ities. The structuring of marginal costs permits the tariffs to be efficientlyand fairly allocated among consumers. In the second stage of developing a

14 THEORY

tariff based on LRMC, deviations from the strict LRMC are considered tomeet important financial, social, economic (second-best), and political crite-ria. This second step of adjusting the strict LRMC is generally as importantas the first calculation, especially in developing countries.

The LRMC approach provides an explicit framework for analyzing systemcosts and setting tariffs. If departures from the strict LRMC are required fornoneconomic reasons, then the economic efficiency cost of these deviationsmay be estimated roughly by comparing the effect of the modified tariff rel-ative to the (benchmark) strict LRMC. Since the cost structure may be stud-ied in considerable detail during the LRMC calculations, this analysis alsohelps to pinpoint weaknesses and inefficiencies in the various parts of thepower system-for example, overinvestment; unbalanced investment; or ex-cessive losses during generation, transmission, and distribution in differentgeographic areas; and so on. This aspect is particularly useful in improvingsystem expansion planning.

Finally, any tariff based on the LRMC is a compromise between many dif-ferent objectives. Therefore, no ideal tariff exists. By using the LRMC ap-proach, it is possible to revise and improve the tariff on a consistent andcontinual basis. Thus, the optimal price is reached gradually over severalyears, without subjecting long-standing consumers to unfair shocks becauseof large abrupt price changes.

Chapter2

Economics of Marginal Cost Pricing

MARGINAL COST PRICING THEORY dates to the pathbreaking efforts of Dupuitand, subsequently, Hotel'ling. Ruggles provided a comprehensive review ofwork on the subject up to the 1940s.' The development of the theory, espe-cially for application in the electric power sector, received a strong impetusfrom the work of Boiteux, Steiner, and others in the 1950s.2 Recent workhas led to more sophisticated investment models that enable analysts tostructure marginal costs rnore accurately; to detennine developments in peakload pricing; and to consider the effects of uncertainty, the costs of powershortages, and so on.3

Basic Marginal Cost Theory

The rationale for setting price equal to marginal cost may be clarified with

1. P. Dupuit, "De l'Utilite et de Sa Mesure," La Reforma Soziale (Turin, 1932); H. Hotel-ling, "The General Welfare in Relation to Problems of Railway and Utility Rates," Econo-metrica, vol. 6 (July 1938), pp. 242-69; N. Ruggles, "The Welfare Basis of the Marginal CostPricing Principle," Review of Economic Studies, vol. 17 (1949-50), pp. 29-46; and N. Rug-gles, "Recent Developments in the Theory of Marginal Cost Pricing," Review of EconomicStudies, vol. 17 (1949-50), pp. 107-26.

2. See M. Boiteux, ''La Tarification des Demandes en Pointe," Revue Generale del'Electricite, vol. 58 (1949); P. Steiner, "Peak Loads and Efficient Pricing," Quarterly Journalof Economics (November 1957); M. Boiteux and P. Stasi, "The Determination of Costs of Ex-pansion of an Interconnected System of Production and Distribution of Electricity," in Mar-ginal Cost Pricing in Practice, ed. James Nelson (Englewood Cliffs, N.J.: Prentice-Hall,1964); 0. E. Williamson, "Peak Load Pricing and Optimal Capacity under Indivisibility Con-straints," American Economic Review, vol. 56, no. 4 (September 1966), pp. 810-27; andRalph Turvey, Optimal Pricing and Investment in Electricity Supply (Cambridge, Mass.: MITPress, 1968).

3. See "Symposium on Peak Load Pricing," Bell Journal of Economics, vol. 7 (Spring1976), pp. 197-250; Ralph T'urvey and Dennis Anderson, Electricity Economics (Baltimore,Md.: Johns Hopkins University Press, 1977); Michael A. Crew and Paul R. Kleindorfer, PublicUtility Economics (New York' St. Martins Press, 1979); Canadian Electrical Association, Mar-ginal Costing and Pricing of Electrical Energy. Proceedings of the State of the Art Conference,Montreal, May 1978; and Mohan Munasinghe, The Economics of Power System Reliability andPlanning (Baltimore, Md.: Johns Hopkins University Press, 1979).

15

16 THEORY

the simple supply-demand diagram shown in Figure 2-1. Let EFGDO be thedemand curve, which determines the kilowatt-hours of electricity demandedin a given year at any given average price level. AGS is the supply curve,and is represented by the marginal cost (MC) of supplying additional units ofoutput.

At price p and demand Q, the total benefit of consumption is representedby the consumers' willingness to pay, that is, the area under the demandcurve OEFJ. The cost of supplying the output is the area under supply curveOAHJ. Therefore, the net benefit, or total benefit minus supply cost, is givenby the area AEFH. The maximum net benefit AEG is achieved when price isset equal to marginal cost at the optimal market clearing point G, that is,(pO, QO).

In mathematical terms, the net benefit (NB) is given by

NB = f p(q)dq - fJQ MC (q)dqwhere p (Q) and MC(Q) are the equations of the demand and supply curves,respectively. Maximizing NB yields d(NB)ldQ = p(Q) - MC(Q) 0 O, thepoint at which the demand and marginal cost curves intersect (po, QO).

The analysis so far has been static. Now consider the dynamic effect ofdemand growth from year zero to the first, which leads to an outward shiftin the demand curve from Do to D,. Assuming that the correct market clear-

Figure 2-1. Supply and Demand for Electricity Consumption

E S\F \ ' /~~~~~~~~~S (MC)

P~~~~~~~~~~~~~~~P

PiL , ----- l----

pO, ------ F------------i-

I ~~It IIIDD

Q QC Q' QtKilowatt-hours

ECONOMICS OF MARGINAL COST PRICING 17

ing price p, was prevailing in year zero, excess demand equal to GK will oc-cur in the first year. Ideally, the supply should be increased to Q, and thenew optimal market clearing price established at p,. The available informa-tion conceming the demand curve D, may be incomplete, however, makingit difficult to locate point L.

Fortunately, the technical-economic relations underlying the productionfunction usually enable the analyst to determine the marginal cost curvemore accurately. Therefore, as a first step, the supply may be increased toan intermediate level Q' at price p'. The existence of the excess demand MNindicates that both the supply and the marginal cost price should be furtherincreased. Conversely, if L is overshot and there is excess supply, then itmay be necessary to wait until demand growth catches up with the overca-pacity. In this iterative manner, it is possible to move along the marginalcost curve toward the optimal market clearing point. As the optimum is ap-proached, it is also shifting with demand growth. Therefore, this movingtarget may never be reached. The basic rule of setting price equal to themarginal cost and expanding supply until the market clears, however, is stillvalid.4

Capital Indivisibilil:ies and Peak Load Pricing

The analysis of the effect of capital indivisibilities, or "lumpiness" of in-vestments recognizes the fact that, owing to economies of scale, capacityadditions to power systems (especially generation) tend to be large and long-lived (Figure 2-2). Suppose that in year zero, the maximum supply capacityis Q, while the optimal price and output combination (pa, Q) prevails, cor-responding to the demand curve Do and the short-run marginal cost curveSRMC. The SRMC is based on fuel, operating, and maintenance costs, thatis, supply costs with fixed capacity.

As demand grows from Do to D, over time, the price must be increased top, to clear the market in the short run, because capacity is fixed and the sup-

4. As explained later, this simple rule has to be modified when there are constraints in theeconomy: in particular, the consequences of shadow pricing of inputs, second-best consider-ations, and subsidized social prices for poor consumers. Also there has been a recent resurgenceof interest in location-theoretical models of power supply for systems that have already ex-ploited most of the economies of scale. Typically the bulk transmission network is treated as acommon carrier, which purchases power from independent generating stations and then sellspower to separate distribution utilities. The possibilities for allocating costs according to thespatial location of generating and load centers and for the existence of different modes of mar-ket behavior, such as competition or collusion among generation companies with or withoutregulation, can give rise to a vwide range of pricing possibilities. For a more detailed discussion,see Richard E. Schuler and Benjamin F. Hobbs, "Spatial Competition: Applications in theGeneration of Electricity" (paper presented at the 1981 Annual Meeting of the Southem Re-gional Science Association, Washington, D.C., April 1981; processed).

18 THEORY

Figure 2-2. The Effect of Capital Indivisibilities on Price

P2 -- -- -SRMC

RP14*_Po 4 ------ __ __,

O Q, Q QKilowatt-hours

ply curve is extremely steep at Q. When the demand curve has shifted to D2and the price is P2, plant is added to increase the capacity to Q. As soon asthe capacity increment is completed and becomes a sunk cost, however,SRMC falls to its old trend line. Therefore, p3 is the optimal price corres-ponding to demand D3 and the SRMC curve. Generally, the large price fluc-tuations during this process will be unacceptable to consumers. This practi-cal problem may be avoided by adopting a long-run marginal cost (LRMC)approach and by recognizing the need for peak load pricing, as describedbelow.

The basic peak load pricing model shown in Figure 2-3 has two demandcurves. For example, D,k could represent the peak demand during the day-light and evening hours when electric loads are large, and Do, would indicatethe off-peak demand during the remaining hours when loads are light. Themarginal cost curve is simplified by assuming a single type of plant with theSRMC of fuel, operating, and maintenance costs given by the constant a,and the LRMC of adding to capacity given by the constant b. Adding to ca-pacity could involve, for example, investment costs suitably annuitized anddistributed over the lifetime output of the plant. The static diagram has beendrawn to indicate that the pressure on capacity arises because of the peak de-mand D0,, and that the off-peak demand D,D does not infringe on the capac-ity Q. The optimal pricing rule now has two parts corresponding to two dis-tinct pricing periods (differentiated by the time of day): peak period price(pk = a + b) and off-peak period price (p, = a).


Figure 2-3. Peak Load Pricing Model

a

D,,Q

Kilowatt-hours per hour

Note: Dpk = peak demand; D, = off-peal demand; a SRMC of fuel, operating, and mainte-nance costs; and b = LRMC of adding to capacity.

The logic of this simple result is that users during peak periods, who arethe cause of capacity additions, should bear full responsibility for the capac-ity costs, as well as fuel, operating, and maintenance costs. Off-peak con-sumers need not pay the capacity costs. As explained in Appendix C, theanalysis becomes more complicated when there is more than one type ofgenerating plant and there are more than two pricing periods.

Extensions of Simple Models

The models presented so far have been deliberately idealized and simpli-fied to clarify the basic principles involved. Extensions of these models in-corporate and analyze the economics of real-world power systems more real-istically. Three broad types of practical complications are discussed below.

First, the usual procedure adopted in marginal cost pricing studies may re-quire some iteration as shown in Figure 2-4. Typically, a deterministic long-range demand forecast is made assuming that prices will evolve in the fu-ture. Then, using power system models and data, several plans are proposedto meet this demand at some fixed target reliability level (see Chapter 3).The cheapest or least-cost system expansion plan is chosen from these alter-natives. Finally, the strict LRMC is computed on the basis of this least-cost

Figure 2-4. Use of Price Feedback in Estimating Tariffs Based on LRMCIterative feedback loop for price

[Systenm models|and data K.

Revisedprice m alternative Least-costforecast system system S lRMC Tariff dsed

/ plans and costs plan L0l

Original Load-demandpmodels, data,price and forecast

forecastFixed target Economic Financial viability,reliability efficiency social subsidy,level (R) other objective fairness, andlevel (R) ~~~~~~~~~~~other objectives


plan, and a tariff structure based on the adjusted LRMC is prepared. If thenewly estimated tariff that is to be imposed on consumers is significantlydifferent from the originally assumed evolution of prices, however, then thisfirst-round tariff must be fed back into the model to revise the demand fore-cast and repeat the LRMC' calculation.

In theory, this iterative procedure could be repeated until future demand,prices, and LRMC-based tariff estimates become mutually self-consistent. Inpractice, uncertainties in price elasticities of demand and other data may dic-tate a more pragmatic approach in which the LRMC results would be usedafter only one iteration to devise new power tariffs and to implement them.The demand is then observed over some time period, the LRMC is re-estimated, and tariffs are revised to move closer to the optimum, which mayitself have shifted, as described previously. An extreme form of price feed-back could result in a shift of the peak outside the original peak period, es-pecially if this period was too narrowly defined. That is, peak load pricingmay shift the demand peak from one pricing period to another. If sufficientdata on the price elasticity of demand were available, theory indicates thateach potential or secondary peak should be priced to keep it just below theavailable capacity level. Since the necessary information would rarely beavailable in practice, a combination of techniques-including use of a suffi-ciently wide peak period, redefining the peak period to include both the ac-tual and potential peaks, direct switching of certain consumer loads, and soon-may be used to avoid the shifting peak problem.

Second, the interrelated issues of supply and demand, uncertainty, reservemargins, and costs of shortages raise certain problems. As mentioned be-fore, the least-cost systerm expansion plan to meet the demand forecast isgenerally determined assuming some arbitrary target level of system reliabil-ity. Reliability measures include loss-of-load-probability (LOLP), reservemargin, and so on.5 Therefore, marginal costs depend on the target reliabil-ity level. Economic theory suggests that reliability should also be treated asa variable to be optimized and that both price and capacity-or, equiva-lently, reliability-levels should be optimized simultaneously. The optimalprice is the marginal cost price as described earlier. The optimal reliabilitylevel is achieved when the marginal cost of adding capacity to improve thereliability are equal to the expected value of the cost savings to consumersresulting from the electricity supply shortages averted by those capacity in-crements. These considerations lead to a more generalized approach to sys-tem expansion planning as shown below.6

5. For a more detailed review of measures of reliability and their relation to shortage costs,see Munasinghe, The Economics of Power System Reliability and Planning.

6. For details, see Mohan Munasinghe, "A New Approach to Power System Planning,"IEEE Transactions on Power Apparatus and Systems, vol. PAS-99 (May-June 1980), pp.1198-1209; also available as Reprint no. 147 from the World Bank, Washington, D.C.

22 THEORY

Consider a simple static expression for the net benefits (NB) of electricityconsumption, which is to be maximized:

NB (D,R) - TB (D) - SC (D,R) - OC (D,R)where TB = total benefits of consumption if there were no outages, SC =supply costs (system costs), OC = outage costs (costs to consumers of sup-ply shortages), D = demand, and R = reliability.

In the traditional approach to system planning, both D and R are exoge-nously fixed, and therefore NB is maximized when SC is minimized. This isconventional system expansion planning on a least-cost basis. If R is treatedas a variable, however, then

d(NB)ldR = -[d(SC + OC)/dR]+ [a(TB - SC - OC)IaD] (ODIlR) = 0

is the necessary first-order maximization condition. Next, assuming aDlaR= 0, the result is

aSCIaR = - dOCldR.Therefore, as described earlier, reliability should be increased by adding

to capacity until the above condition is satisfied. In Figure 2-5, as reliability

Figure 2-5. Relation betwveen Outage Costs, Supply Costs, and Total Costsat the Optimal Reliability Level

I '

~Jslope

C RI 100 percentReliability

Note: OC = outage costs, SC = supply costs, TC = total costs = OC + SC, and RI = opti-mal reliability level.


increases, outage costs fall, whereas supply costs rise more and more rap-idly. Reliability is optimized at RI when the slope of the SC curve is equal tothe negative slope of the OC curve. An altemative way of expressing thisresult is that since TB is independent of R, NB is maximized when total costsTC = (SC + OC) are minimized. The above criterion is one that effectivelysubsumes the traditional rule for least-cost system planning of minimizingonly the system costs.'

Third, some practical problems may be raised by the dichotomy of havingto choose between SRMC and LRMC. A simplified, intuitive explanationwill clarify this issue. SRMC may be defined in economic terms as the costof meeting additional electricity consumption with fixed capacity. LRMC isthe cost of meeting an increase in consumption, sustained indefinitely intothe future, when needed capacity adjustments are possible. If there is an in-cremental increase in consumption, in the short run both the system operat-ing costs and the outage costs (especially during the peak period) will alsorise at the margin. Similarly, in the long run, an increase in demand willresult in a corresponding increase in the operating costs as well as in the ca-pacity costs. Thus in both the short and long run an equivalent increase inoperating costs will occur. But the optimal reliability rule ensures that themarginal outage and capacity costs are also equal. Therefore, when the sys-tem is optimally planned and operated-that is, capacity and reliability areoptimal-SRMC and LRMC coincide.8 Therefore, the estimation and use ofthe strict LRMC is simplest when the system is near the ideal operatingpoint.

If the system plan is suboptimal, however, significant deviations betweenSRMC and LRMC will have to be resolved within the pricing policy frame-work. For example, after 1973 many utilities began to replace oil-firedplants with coal-fired units to save fuel costs. Such a situation could result insignificant excess capacity and low marginal capacity costs in the short tomedium run, thus justifying reduced demand charges below the LRMClevel. In this situation, however, as peak demand grows and the system ap-proaches its ideal operating point again, the capacity charges should rise

7. The emphasis on outage costs requires greater effort to measure these costs; see MohanMunasinghe and Mark Gellerson, "Economic Criteria for Optimizing Power System ReliabilityLevels," Bell Journal of Economics, vol. 10 (Spring 1979), pp. 353-65, also available as Re-print no. 112 from the World Bank, Washington, D.C.; and Mohan Munasinghe, "The Costsof Electric Power Shortages to Residential Consumers," Journal of Consumer Research, vol. 6(March 1980), pp. 361-69, also available as Repaint no. 128 from the World Bank, Washing-ton, D.C. An even more generalized system planning criterion in which the assumption aDlaR= 0 is relaxed, thus allowing D to vary with R, is presented in Mohan Munasinghe, "SystemPlanning to Achieve Optimal Reliability Levels," Proceedings of the Third International Con-ference on Analysis, Forecasting and Planning for Utilities, Paris, June 1980 (processed).

8. For a more rigorous proof of this result, see Crew and Kleindorfer, Public Utility Eco-nomics, chap. 7.

24 THEORY

smoothly toward LRMC. If demand charges are suppressed too far belowLRMC or for too long, then electricity demand may be overstimulated. Thiscould lead to costly shortages or uneconomic advancement of investments infuture capacity. Furthermore, when future prices have to be increased to theLRMC level, the transition may be undesirably abrupt, resulting in consumerdiscontent. Conversely, when there are significant shortages, the economi-cally efficient short-run solution would be to raise prices to ration the limitedsupplies according to the consumer's willingness to pay. Such a price in-crease would generally be impractical, however, because consumers wouldrarely accept higher prices when the quality of service is poor (see Chapter5).

Finally, if there are substantial outage costs outside the peak period, thenthe optimal marginal capacity costs may be allocated among the pricing pe-riods in proportion to the corresponding marginal outage costs. Another sug-gestion is to allocate capacity costs to different pricing periods in inverseproportion to LOLP, but this would be only a rough approximation, becauseaggregate reliability indexes such as LOLP generally are poor proxies forprorating marginal outage costs."

An alternate approach to this problem has been proposed recently anduses spot or instantaneous prices for electricity.'" Advances in solid stateswitching, metering, and communications technology have made it possibleto vary prices continuously instead of relying on a predetermined schedule.Very briefly, prices at any moment are set to reflect marginal supply costs.As demand rises toward the capacity limit, price is allowed to rise as high asnecessary to choke off demand before a shortage occurs. This type of pric-ing scheme is most appropriate for large electricity users, especially in in-dustrialized countries, where the increased costs of communications and me-tering hardware are more than compensated for by the more economic andefficient use of electricity (see Chapter 5).

9. See, for example, Joseph Vardi, Jacob Zahavi, and Benjamin Avi-ltzhak, "Variable LoadPricing in the Face of Loss of Load Probability," Bell Journal of Econiomics, vol. 8 (Spring1977), pp. 270-88.

10. One of the earliest articles is William Vickrey, "Responsive Pricing of Public UtilityServices," Bell Journal of Economics, vol. 2 (Spring 1971), pp. 337-46. For a recent reviewof the topic, see Roger E. Bohn, Michael C. Caramanis, and Fred C. Schweppe, "OptimalSpot Pricing of Electricity," Working Paper no. MIT-EL-81-008WP (Cambridge, Mass., MITEnergy Laboratory, March 1981; processed).

Chapter 3

Prerequisites for Marginal Costing

SEVERAL PRELIMINARY STEPS must be taken before the basic theory presentedearlier for estimating- long-run marginal costs (LRMC) can be successfullyapplied. The intimate theoretical link between the optimal investment andpricing rules was stressed in the previous chapter. If the load or demandforecast and the plan for least-cost system investment are not prepared accu-rately, the marginal costs that are derived from those earlier calculations arealso likely to be incorrect. Therefore, the rationale underlying the invest-ment decision and the elements of demand forecasting and system planning,which are essential prerequisites for a pricing exercise, and the principles ofshadow pricing need to be understood.

Long before the decision to invest in electric power is made, even broaderissues must be faced. They involve the total future energy needs, availabilityof supply, and the optimal mix of different sources to be developed. Ideally,the energy sector investrnent and pricing policies for the entire nation shouldbe analyzed and determined within an explicit integrated framework.' Inpractice, such decisions are often made by policymakers case by case.

Modem societies require increasing amounts of energy for domestic, in-dustrial, commercial, agricultural, and transport uses. Arrayed against theseenergy needs are the short-term, depletable fossil fuel supplies-petroleum,coal, and natural gas-as well as the longer-run, renewable energy sources.The latter include water, nuclear, solar, geothermal, wind, tidal, and bio-mass, along with traditional or noncommercial fuels such as wood and ani-mal waste.

At this stage, three basic energy policy decisions are required.2 First, theappropriate level of demand for energy that must be served to achieve social

1. See Mohan Munasinghe, "Integrated National Energy Planning (INEP) for the DevelopingCountries," Natural Resources Forum, vol. 4 (October 1980), pp. 359-73; also available asReprint no. 165 from the World Bank, Washington, D.C. Traditional or noncommercial fuelssuch as firewood are particularly important in developing countries, amounting to about 40 per-cent of total energy consumption in 1975. See Mohan Munasinghe and Colin J. Warren, "RuralElectrification, Energy Economics, and National Policy in the Developing Countries," in Fu-ture Energy Concepts, publication no. 171 (London: Institution of Electrical Engineers, 1979),pp. 44-47.

2. For a nontechnical discussion of these three aspects, that is, load forecast, investment

25

26 THEORY

goals, such as economic development, growth, and basic human needs,should be determined. Second, the optimal mix of energy sources must beestablished that will meet the desired demand, based on several national ob-jectives, such as minimum cost, independence from foreign sources, conser-vation of resources, environmental considerations, and price stability. Theanalysis is complicated by uncertainties regarding the future evolution of de-mand and supply, relative costs and prices, and incompatibility of the differ-ent energy sources with all the various energy uses. Third, closely associ-ated with and following the investment decision is the pricing policy, whichwill be based on criteria such as economic efficiency in resource allocation,economic second-best considerations, sector financial requirements, socialequity considerations, and other political constraints.3 Energy pricing deci-sions may also have feedback effects on investment decisions through de-mand (see Chapter 2).

The electric power sector is usually one of the most important elementswithin the broader energy framework. Once the important decisions regard-ing energy policy have been made at the national level, the electric powersector authorities must perform a similar but more detailed analysis. Morespecifically, the demand for electricity must be forecast, preferably disag-gregated by geographic region and customer category. Then alternativelong-range investment programs are compared that will meet this demandforecast, subject to various constraints, as described below. The cheapest orleast-cost program is usually selected as the optimal one.

The appropriateness of such a least-cost program for power expansionmust be further verified in the sense that, broadly defined, the social benefitsof this expansion should exceed the social costs by the maximum amount,that is, until the net benefits of consumption are maximized. A pricing pol-icy based on LRMC effectively permits the burden for the cost-benefit anal-ysis to be placed on the electricity consumer, because he signals the justifi-

plan, and output price, relating specifically to electric power, see Mohan Munasinghe, "Plan-ning for Electrical Power: Costs and Technologies." National Development (April 1980), pp.75-84; also available as Reprint no. 149 from the World Bank, Washington, D.C.

3. For details of energy pricing, see Mohan Munasinghe, "An Integrated Framework for En-ergy Pricing in Developing Countries," Energy Journal. vol. I (July 1980), pp. 1-30; alsoavailable as Reprint no. 148 from the World Bank, Washington, D.C. Interactions between dif-ferent energy sources must not be neglected; see Gunter Schramm and Mohan Munasinghe,"Interrelationships in Energy Planning: The Case of the Tobacco Industry in Thailand," En-ergy Systems and Policy vol. 5 (March 1981), pp. 117-39; also available as Reprint no. 187from the World Bank, Washington, D.C.; and Oli Havrylyshyn and Mohan Munasinghe, "In-teractions among Alternative Modes of Energy Production: Empirical Case Study for SriLanka," Economics Discussion Paper (Washington, D.C.: George Washington University,April 1980).

PREREQUISITES FOR MARGINAL COSTING 27

cation of further investment by his willingness to pay the marginal cost ofelectricity supply.

Load Forecasting

Many elements of load forecasting are relevant to the process of systemplanning. Further details may be found in the references cited in this chap-ter.4 The terms demand and load forecast are used interchangeably to indi-cate the magnitude as well as the structure of the requirements of both elec-trical power (kilowatts) and energy (kilowatt-hours), unless an appropriatedistinction is necessary. The structure of demand includes disaggregation bygeographic area, consumer category, and time period, as well as characteris-tics such as load and diversity factors and system losses.

Since demand characteristics vary by type of consumer, geographic area,and time period, a knowledge of loads at the disaggregate level is required.The properties of the aggregate demand at the system level may be quite dif-ferent from the characteristics of the individual loads. Disaggregate loads areimportant in the system planning process. In generation planning, the systemmay be modeled as one source feeding a single lumped load; in the design oftransmission networks, the characteristics of demand by region and by prin-cipal load center, such as a city, become important. Ultimately, for planningdistribution grids, a detailed knowledge of demand at each load center is re-quired, as discussed below. Furthermore, the sum of many disaggregate de-mand forecasts, estimated by using various different techniques, can oftenserve as a useful check on an independently made global forecast for thesame region.

Power, energy, and the loadfactorBefore discussing the other characteristics of demand, it would be helpful

to examine the basic relation between power and energy. The commonlyused unit of energy in heavy current electricity applications is the kilowatt-hour. The rate of flow of energy per unit of time is called power, which ismeasured in kilowatts. The distinction between power and energy is impor-tant because the same amount of energy may be delivered within a small in-terval of time at a relatively high rate of power flow, or over a longer periodat a lower power level.

4. See Federal Power Commission, The Methodology of Load Forecasting, 1970 NationalPower Survey (Washington, D.C.: Department of Energy, 1970); Robert L. Sullivan, PowerSystem Planning (New York: McGraw-Hill, 1977), chapter 2; and G. E. Huck, "Load ForecastBibliography: Phase 1," Proceedings of the IEEE PES Summer Meeting, Vancouver, July 1979,paper no. F7950-3.

Figure 3-1. Schematic of a Simple Electric Power System

G,

TF1

7',T 2v T5 = HVtanmssolns

TT2

TT1 , D d t TsL---_----J

T3

r- -- -_-_,

S1 , ~ ~ 52 = seonay ins

I

T~~~~

281 1 F2

M2 ~~DT,Note: G,, Ga generators;

TF,, TF2 = voltage transformers;T,, T,2, T., T6 = HV transmission lines;MS, TS2 = transmission substations;T. = BHV transmission;DS1, DS& = distribution substations;Fl, F2 = primary feeders (or circuits);DT1, DT2 = distribution transformers;S,, 52 = secondary lines;M,, m = customer service inlets and meters;

28


The load factor (LF), which is the ratio of average to maximum or peakkilowatts over a given interval of time, may be specified for a single cus-tomer, the whole systemn, on a daily or annual basis, and so on. The LF isimportant, because the size or capacity and, therefore, the cost of power sys-tem components are determined to a great extent by their ability to handlepeak power flows. Since practically all customers use maximum power onlyduring a short peak period during the day, the LF is also a measure of the in-tensity of capacity use. (See the discussion on the load duration curve be-low.) A load forecast may be made either in terms of peak power or of totalenergy consumed during a given period. The LF is used to convert from oneunit to the other. Kilowatt peaks for different types of customers do not oc-cur simultaneously. The diversity factor for a group of consumers measuresthe divergence over time of the individual peak loads and permits the com-bined peak load for the group to be computed starting from disaggregatepeak values.

It is convenient at this point to examine the load forecast requirementsthat will facilitate disaggregation of the LRMC estimates. As explained indetail in the next chapter, the LRMC of supply is estimated at various pointsin the system which usually are distinguished by the voltage level, for exam-ple, with respect to generation, transmission, and distribution. Therefore,the load-demand forecast must be sufficiently disaggregate to permit thistype of structuring.

Components of typical electric power systemsThe basic component and voltage levels in the simple power system are

shown in Figure 3-1. lThe output from two power generating plants G, andG, (hydroelectric or thermal) is increased to the high voltage (HV) level atsource by the respective transformers TF, and TF2 and is fed into the busbarsin transmission substation TS, through the HV transmission links T, and T2.At TS, the voltage is further increased to the extra high voltage (EHv) line T,to substation TS2. A voltage reduction occurs at TS2, after which the electricpower is fed, through HV tranmission lines T, and T5, into the distributionsubstations DS, and DS, located close to the load centers. Another voltagereduction occurs at DS, and DS2 , and then power flows out of the distribu-tion substation busbars, through primary feeders such as F,, to various distri-bution transformers (for example, DT,), where the voltage is decreased fur-ther. Finally, the power is delivered to a representative consumer throughthe secondary distribution line S, and service inlet and meter M,.

In transporting electric power the general principle is that voltage leveldepends on distance and power flow. Transmission lines are used to carrylarge amounts of power over long distances, whereas distribution lines in-volve smaller power flows over shorter distances. The technical distinction

30 THEORY

Figure 3-2. Power and Energy Flows, Consumption, and Lossesin a Typical Power System

System peak ,power and Generationenergy atgenerators Station use +

2 EHV and HVtransmission losses+ nontechnical losses

EHV and HV

System peak Power and energypower and (3) (4) demands ofenergy at HV HV- consumers

(5 { MV distribution losses1_ + nontechnical losses

System peak Power and energypower and (6) (7) demands ofenergy at MV MV consumers

LV distribution losses LV(8) and nontechnical losses

System peakpower and (9) Power and energy demandsenergy at LV of LV consumers

Note:- power and energy flows

lossesG generation

'3D transformation


between transmission and distribution facilities is usally made on the basisof their operating voltages. Although voltage standards vary greatly fromcountry to country, broadly accepted definitions for voltage levels are as fol-lows: EHV transmission, more than 220 kilovolts; HV transmission, 45 to 220kilovolts; primary distribution, 6 to 25 kilovolts; and secondary distribution,110 to 380 volts. In practice, considerable overlap is likely, and facilitiesoperating at voltages in the range of 25 to 45 kilovolts (often called sub-transmission) may be included within the distribution or transmission cate-gory, depending on their function.

An operating power system is much more complex than the one describedabove, and in general has many generating sources linked to many load cen-ters through an interconnected transmission network. Transmission intercon-nections may be used to tie the power systems of several different utilitiestogether to form an even larger power pool. The distribution grid at a singleload center would serve thousands of consumers. Furthermore, many othercomponents, including protective and relaying devices as well as load con-trol and dispatching equipment, would play important roles in a large inter-connected system.

Figure 3-2 shows the flow of power and energy from generators to con-sumers. The total amount of both kilowatts and kilowatt-hours generated atthe source will be greater than the corresponding values consumed becauseof losses in the system. Generation losses usually involve station use, suchas driving various auxiliary equipment. Transmission and distribution net-work losses occur in the lines, substations, and transformers. Nontechnicallosses, including theft and unmetered consumption, arise frequently in somecountries and must be allowed for at each voltage level, where necessary.To establish LRMC at the generators and at the high- medium- and low-voltage levels, the system peak power and energy forecast should be knownat points (1), (3), (6), and (9) in the figure. An estimate of the consum

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