Economic Assessment of 

RTO Policy

Prepared for:

Federal Energy Regulatory Commission

Prepared by:

ICF Consulting

February 26, 2002

i

TABLE OF CONTENTS

Page

EXECUTIVE SUMMARY.................................................................................................................V

1 INTRODUCTION............................................................................................................................1

1.1 STUDY OVERVIEW......................................................................................................................1

1.2 REGULATORY CONTEXT.............................................................................................................2

1.2.1 Basis for Current RTO Policy..............................................................................................2

1.2.2 Prospective Benefits from the Commission’s RTO Policy..................................................6

1.2.3 The RTO: Functions, Characteristics, and Form................................................................8

1.2.4 Developments Since Order No. 2000.................................................................................9

1.3 RELATED STUDIES.................................................................................................................. 13

1.3.1 FERC Order No. 888 Environmental Impact Statement (National, FERC/EIS-0096).....14

1.3.2 Supporting Analysis for the Comprehensive Electricity Competition Act (National, 

DOE/PO-0059)...........................................................................................................................15

1.3.3 FERC Order No. 2000 Environmental Assessment (National) ........................................17

1.3.4 Mirant Study and LECG Response (Northeast)...............................................................17

1.3.5 NYISO/LECG Response (Northeast)................................................................................18

1.3.6 PJM Study (Northeast)......................................................................................................19

1.3.7 RTO West Benefit/Cost Study (Preliminary Report, Northwest)......................................20

1.3.8 Conclusions.......................................................................................................................23

1.4 BASIS FOR ANALYTIC APPROACH........................................................................................... 23

2 ANALYTIC APPROACH............................................................................................................ 27

2.1 INTEGRATED PLANNING MODEL OVERVIEW........................................................................... 28

2.2 MODELING SCENARIOS:BASE CASE AND POLICY SCENARIOS............................................. 29

2.2.1 Base Case.........................................................................................................................29

2.2.2 Policy Scenarios................................................................................................................29

2.3 MODELING RTO SCENARIOS WITH IPM®............................................................................... 31

2.3.1 RTO Regional Configuration.............................................................................................31

2.3.2 Calibration .........................................................................................................................35

2.3.3 Base Case Specification...................................................................................................36

2.3.4 Policy Scenario Specification............................................................................................36

2.4 ANALYTIC ASSUMPTIONS ........................................................................................................ 38

2.4.1 Assumptions That Change Across Cases ........................................................................38

2.4.2 Invariant Assumptions.......................................................................................................42

2.5 TREATMENT OF NON-MODELED SYSTEM ELEMENTS ............................................................ 46

2.5.1 Treatment of Cost Categories Not Represented in Modeling ..........................................48

2.5.2 Short-Term Market Events................................................................................................49

2.5.3 Native Load and Contracts................................................................................................49

3 RESULTS..................................................................................................................................... 51

3.1 SUMMARY RESULTS: BASE CASE........................................................................................... 51
ii

3.1.1 Base Case Capacity and Generation Projections ............................................................51

3.1.2 Base Case Energy Prices and Production Costs .............................................................55

3.2 RTO POLICY CASE RESULTS................................................................................................. 58

3.2.1 RTO Policy Case: Changes in Inter-Regional Trade........................................................58

3.2.2 RTO Policy Case: Changes in Production Cost and Electricity Prices ............................65

3.3 TRANSMISSION ONLY CASE.................................................................................................... 69

3.4 DEMAND RESPONSE SCENARIO............................................................................................. 71

3.5 SENSITIVITY CASE I: LARGER RTOS...................................................................................... 73

3.6 SENSITIVITY CASE II: SMALLER RTOS................................................................................... 75

3.7 DISCUSSION AND INTEGRATION OF COSTS ............................................................................ 77

3.7.1 Costs of RTO Establishment.............................................................................................78

3.7.2 Short-term Market Imbalances and Market Power...........................................................80

3.7.3 Regional Variations in Economic Outcomes ....................................................................80
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TABLES

Page

Table ES-1: System-Level Production Costs for Regulatory Scenarios ............................................ vi

Table ES-2: Larger and Smaller RTO Sensitivity Cases....................................................................vii

Table 1.1: Level 2 TLRs and Above, Summer 1998-2000 ................................................................10

Table 1.2: PJM Study Results............................................................................................................20

Table 2.1: Base Case and Policy Scenario Specifications................................................................31

Table 2.2: RTO Regional Specification – Main RTO Policy Cases...................................................33

Table 2.3: RTO Regional Specification – Sensitivity Case I: Larger RTOs ......................................34

Table 2.4: RTO Regional Specification – Sensitivity Case I: Smaller RTOs ....................................35

Table 2.5: Load Growth Assumptions................................................................................................44

Table 2.6: Base Case Henry Hub Gas Price Trajectory....................................................................45

Table 2.7: Revenue from Sales to Ultimate Users by Utility Type, 1997 ..........................................47

Table 2.8: Investor-Owned Utility Costs, 1995 ..................................................................................47

Table 2.9: Example Capital Cost Output from IPM®..........................................................................48

Table 3.1: National Generating Capacity by Plant Type: Base Case and AEO 2002 .....................52

Table 3.2: National Generation Projections by Plant Type: Base Case and AEO 2002 ..................53

Table 3.3: Generating Capacity by Region: Base Case...................................................................54

Table 3.4: Generation by Region: Base Case..................................................................................54

Table 3.5: Base Case: System Level Annualized Production Costs.................................................55

Table 3.6: Base Case: Regional Firm Electricity Prices....................................................................56

Table 3.7: RTO Policy Case: System Level Annualized Production Costs ......................................65

Table 3.8: RTO Policy Case: Regional Firm Electricity Prices..........................................................66

Table 3.9: Transmission Only Case: System Level Annualized Production Costs...........................69

Table 3.10: Transmission Only Case: Regional Firm Electricity Prices............................................70

Table 3.11: Demand Response Case: System Level Annualized Production Costs........................71

Table 3.12: Demand Response Case: Regional Firm Electricity Prices...........................................72

Table 3.13: Larger RTOs: System Level Annualized Production Costs ...........................................73

Table 3.14: Larger RTOs: Regional Firm Electricity Prices...............................................................74

Table 3.15: Smaller RTOs: System Level Annualized Production Costs..........................................75

Table 3.16: Smaller RTOs Firm Electricity Prices .............................................................................76

Table 3.17: System Level Production Costs Across Cases..............................................................77

Table 3.18: Characteristics of Existing ISOs .....................................................................................79
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FIGURES

Page

Figure 2.1: Integrated Analytic Framework........................................................................................28

Figure 2.2: IPM® Regions...................................................................................................................32

Figure 2.3: RTO Regional Specification – Main RTO Policy Cases .................................................33

Figure 2.4: RTO Regional Specification – Sensitivity Case I: Larger RTOs.....................................34

Figure 2.5: RTO Regional Specification – Sensitivity Case II: Smaller RTOs..................................35

Figure 2.6: Production Cost Categories.............................................................................................48

Figure 3.1: Base Case 2010 Firm Power Prices ...............................................................................57

Figure 3.2: Northeast RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case

.....................................................................................................................................................60

Figure 3.3: Southeast RTO Energy Transfers in 2006: Change from Base Case to RTO Policy 

Case.............................................................................................................................................61

Figure 3.4: Midwest RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case

.....................................................................................................................................................61

Figure 3.4: Midwest RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case

.....................................................................................................................................................62

Figure 3.5: West RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case...63

Figure 3.6: ERCOT Energy Transfers in 2006: Change from Base Case to RTO Policy Case.......64

Figure 3.7: Illustrative Supply Curves ................................................................................................67

Figure 3.8: Percent Change in 2010 Firm Power Prices from the Base to RTO Policy Case..........68
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Executive Summary

This study was commissioned by the Federal Energy Regulatory Commission (FERC or 

the Commission) to examine potential economic costs and benefits of a move toward 

Regional Transmission Organizations (RTOs). RTOs are intended to improve the 

operation of the nation’s electric power system in a number of ways. The FERC issued 

Order No. 2000 to promote the formation of RTOs in all areas of the country. 

The Commission stated that properly functioning RTOs could provide several types of 

economic benefits:

• Improvements in transmission system operations with resulting enhancements to 

inter-regional trade, congestion management, reliability and coordination; and

• Improved performance of energy markets, including 

− Greater incentives for efficient generator performance; and

− Enhanced potential for demand response.

These changes to the regulation and operation of the electric power system would, 

according to the Commission, also lead to a reduced need for intrusive government 

regulation.

By identifying a set of potential changes to the operation of the electric power system, 

and resulting economic performance, this study seeks to be both comprehensive and 

rigorous, employing sufficient quantitative detail to accurately represent potential 

outcomes of RTO policy. Close collaboration with the Commission and cooperative 

efforts with other researchers and state regulators were an integral part of the scenario 

development process, resulting in an analysis that attempts to estimate a range of 

potential economic impacts using the best available information from a variety of 

sources. The potential benefits of RTOs are considered as are the tradeoffs involving 

RTO startup costs and the potential for regional cost shifting.

Under the set of assumptions analyzed regarding the effect of RTO formation on electric 

power markets, including the establishment of consistent and effective market rules, 

substantial net benefits should result from the Commission’s policy. Once policy 

changes are fully in place the results suggest that $1-10 billion per year in economic 

gains could result. These estimated benefits do not take into account secondary 

economic impacts (‘spillovers’) or employment gains. 

 Table ES-1 shows the total system production cost changes from the Base Case 

(status quo or no-action case), in millions of year 2000 dollars, as well as the twentyyear net present value for each scenario.
vi

Table ES-1: System-Level Production Costs for Regulatory Scenarios

(Million 2000$, NPV in Billion 2000$)

2004 2006 2010 2015 2020

NPV1

2002 -

2021

Base Case 89,493 94,161 109,489 129,374 149,758 1,076.8

RTO Policy Case

Savings from Base

% Savings From Base

88,414

1,080

1.2%

91,972

2,189

2.3%

104,254 

5,235

4.8%

123,057

6,318

4.9%

142,289

7,470

5.0%

1,035.9

40.9

3.8%

Transmission Only Case

Savings from Base

% Savings from Base

89,089 

405

0.5%

93,805 

356

0.4%

108,723 

767

0.7%

128,568 

806

0.6%

148,468 

1,291

0.9%

1,070.6

6.2

0.6%

Demand Response Case

Savings from Base

% Savings from Base

88,343 

1,150

1.3%

89,997 

4,164

4.4%

101,941 

7,548

6.9%

120,451 

8,923

6.9%

139,361 

10,398

6.9%

1,016.8

60.0

5.6%

The scenarios analyzed in this study were developed using assumptions that come from 

previous analyses of these topics and from estimates based on available data. While it 

is important to recognize the uncertainty of these estimates, these estimates are not 

necessarily optimistic or upper bound estimates. Several key assumptions are actually 

conservative in the policy scenarios, and further sensitivity analysis would be required to 

estimate a true upper bound on the potential economic benefits of RTO policy.

Within the range of costs and benefits estimated here, a key finding is that the net 

benefits of RTO policy will depend on the effective and timely implementation of 

competitive electric power markets, and on minimizing delays and excessive startup 

costs. While the size of RTOs does matter given the set of analytic assumptions used, 

the size and configuration of RTOs matters less than the dominant impact of enhanced 

incentives for efficient market outcomes. This assumes that consistent and effective 

market design is put in place throughout the country. 

Table ES-2 shows the results of two sensitivity cases developed to represent a smaller 

number of relatively large RTOs, as compared to a larger number of relatively small 

RTOs. The difference in production costs between these two cases is generally 

between $100-300 million per year, yielding an overall change in net present value of 

$1.2 billion over the study’s time frame. To the extent that a clear link can be 

established between RTO scope and competitive market effectiveness, the benefits of 

larger RTOs would be more significant. 

 

1 Net present value calculated using a 6.97% discount rate.
vii

Table ES-2: Larger and Smaller RTO Sensitivity Cases

(Million 2000$, NPV in Billion 2000$)

2004 2006 2010 2015 2020

NPV1

2002 -

2021

Larger RTOs

Savings from Base

% Savings from Base

88,301 

1,192

1.3%

91,893 

2,267

2.4%

104,185 

5,304

4.8%

123,000 

6,374

4.9%

142,190 

7,568

5.1%

1,035.4

41.4

3.8%

Smaller RTOs

Savings from Base

% Savings from Base

88,452 

1,041

1.2%

92,031 

2,130

2.3%

104,319 

5,171

4.7%

123,192 

6,182

4.8%

142,368 

7,390

4.9%

1,036.6

40.2

3.7%

Costs of RTO formation are also uncertain. A central low cost estimate of $1 billion and 

a central high cost estimate of $5.75 billion are developed in the study report. These 

costs can be allocated as one-time, single year costs or amortized over time, and netted 

out against estimated benefits for a net economic impact estimate. Although the exact 

magnitude of costs and benefits is uncertain, the range estimated here yields a positive 

net benefit from pursuing RTO policy even if benefits are relatively low and costs are 

relatively high.

While there is a consistent national net benefit from RTO policy, as measured by total 

production costs, a more complex result arises when energy price impacts are 

considered on a regional level. Most regions are expected to experience price 

decreases when inter-regional trade increases under RTO policy. However, some 

regions show transient price increases that last a few years, followed by decreasing 

prices over time, and a few regions appear likely to experience increased energy prices 

for a prolonged period. The region with the greatest price increase in any one year in 

these results is the ILMO (downstate Illinois and Missouri) region where prices in one

case rise 8% in 2006, while Montana and parts of the interior West show the most 

persistent, albeit small, price increases. In the Northeast there are similar small and 

transient price increases in portions of PJM.

An important limitation of this study involves short-term market imbalances and market 

power. The national scope and long time frame required for this analysis precludes a 

direct representation of inefficiencies that can result from poor market design, transient 

supply-demand imbalances, and systemic or episodic market power abuses. Some 

portion of the potential benefits of RTO policy could be lost if policy implementation fails 

to successfully address these issues.

In summary, this study cannot eliminate uncertainty regarding the ultimate outcomes of 

Commission policy on RTOs. It is intended to place such uncertainty into a quantitative 

context, to provide perspective, and to draw broad conclusions about the likely net 

economic impacts of changes in the national electric power system. On balance, the 

analysis conducted here suggests that a move toward RTOs, if it results in improved 

market operations, can deliver $1-10 billion dollars in long term annual savings. It is 

likely that larger RTOs would lead to slightly greater benefits, and that regional energy 

price impacts will vary, with most regions seeing price decreases.
viii

The increased inter-regional trade that leads to regional variations in price impacts also 

leads to regional variations in export revenues and producer earnings. Regions with 

higher prices due to increased exports also gain revenues from the exports. This 

increase in regional power revenue, in the immediate form of producer earnings, raises 

issues of equity and distribution that go beyond this report’s scope. Finally, it is also 

important to note that the changes in energy prices estimated here are wholesale 

energy prices; the ultimate consumer price impacts will be mediated by regulation, 

contract treatment, and other institutional mechanisms.
1

1 Introduction

The Federal Energy Regulatory Commission (FERC) commissioned a national 

cost/benefit study of regulatory policy concerning Regional Transmission Organizations 

(RTOs). This report is the main summary of the context, methods, and results of the 

cost/benefit analysis, carried out by ICF Consulting for the FERC.

1.1 Study Overview

The Commission’s RTO initiative is part of a broader move toward more competitive 

energy markets. Because electric power must be transported using a single integrated 

transmission grid, the operation of transmission systems plays a direct role in how 

electric power is produced and used. The design of the transmission system can set 

economic incentives and physical limits that influence the operation of power plants. In 

addition, the establishment of centralized, independent market operators is a key 

element in the creation of competitive supply markets. The tight linkage between realtime operating decisions and economic outcomes enhances the importance of FERC 

policy regarding the structure, ownership and control of the interstate transmission 

system. 

The US electric power sector is a critical element of the national economy. Regulatory 

policies affecting this sector can have large, long-term impacts that affect the entire 

country. This in turn requires regulatory analysis that is both national and long-term. 

The methods used in this study for the FERC reflect this, primarily through the use of 

dynamic computer simulations that forecast power system changes and economic 

outcomes under differing conditions. This methodology enables a detailed quantitative 

assessment of potential costs and benefits over long periods, taking into account 

interactions between power, fuel and environmental markets.

Previous analyses conducted by ICF at the FERC’s direction include the Environmental 

Impact Statement for Order No. 888 in 1996 and the Environmental Assessment for 

Order No. 2000 in 1999. These were also national, long run analyses that relied on 

computer simulation modeling as an analytic method. This economic analysis of RTO 

policy, while sharing the geographic scope and time frame of previous FERC studies, 

considers a different set of substantive issues. Economic cost/benefit analysis requires 

broader consideration of the purpose and possible outcomes of FERC policy beyond 

environmental impacts to include, for example, the costs of supplying power, the relative 

prices of that power, inter-regional trade patterns and other changes to the operation 

and economic performance of the power system.

In conducting this study, existing data and previous research were relied on as much as 

possible. One purpose of this report is to place the results of this study in the context of 

related work, and to allow for comparisons when possible. By focusing on methods and 

data sources, the key factors that drive the results of different analyses can be 
2

determined. This can aid in an overall understanding of how regulatory policy may 

affect economic outcomes in the electric power sector. 

Throughout this report, emphasis is placed on uncertainty and the role of multiple 

factors that, taken together, may result in differing degrees of change in economic 

outcomes. While this report cannot create certainty regarding regulatory impacts, it 

does attempt to explain the range of potential outcomes and quantify the importance of 

specific changes that may result from RTO policy.

The report is organized into three main sections. Section I describes the regulatory 

context, related work, and the basis for the analytic approach employed for this study. 

The second section details the analytic approach, including the role of simulation 

modeling, the specific model used, scenarios and assumptions. Section III presents 

results, both from the simulation model and integrated quantitative analysis that 

includes several important elements that were not directly represented in the model.

1.2 Regulatory Context

The regulatory policy being considered in this cost/benefit study is primarily embodied in 

the Commission’s Order No. 2000. However, there are a number of FERC orders and 

actions that are related to RTO policy, as well as ongoing fact-finding and research. 

Commission staff and other parties have continued to learn about and respond to 

changing conditions in the electric power sector. This section of the report presents the 

regulatory context and the specific potential benefits that led the FERC to issue Order 

No. 2000. Subsequent Commission findings are also summarized, including the order 

that called for the present study to be carried out for the Commission. This regulatory 

context is the starting point for the choice of analytic methods, as discussed in the next 

section.

1.2.1 Basis for Current RTO Policy2

The movement toward more competitive energy markets has been underway for several 

decades, marked by such major developments as the Natural Gas Act and the Public 

Utilities Regulatory Policy Act in 1978, and the Energy Policy Act in 1992. Successive 

Administrations and Congresses have considered the issues involved in energy market 

restructuring on an ongoing basis during this period. The role of the transmission 

system has long been recognized as being of critical importance for the performance of 

energy markets. This has highlighted the role of the FERC in its oversight of interstate 

wholesale power markets. 

FERC policy regarding the control and operation of the transmission grid has evolved 

over time, as shown most clearly in Order No. 888 in 1996 and Order No. 2000. In 

discussing the basis for the current policy on RTOs, the Commission provided economic 

rationales that describe a number of mechanisms connecting RTO policy to potential 

 

2

Excerpts from FERC Order No. 2000 Notice of Proposed Rulemaking (NOPR). Docket No. RM99-2-000. 

All parenthetical pages quotes refer to this edition.
3

changes in economic outcomes in the US electric power sector. The Commission’s 

regulatory discussion provides the starting point for this cost/benefit assessment.

This section of the report relies on the FERC Order No. 2000 language in order to 

clearly establish the economic issues involved in evaluating RTO policy. Later sections 

of the report discuss the analytic approaches adopted for consideration of the specific 

issues raised (and several additional topics that are also relevant for a full economic 

cost/benefit assessment). Relying on the Commission’s regulatory discussion in Order 

No. 2000 to frame the economic issues provides a consistent context and ensures that 

relevant economic issues are considered even when they are less well-suited for the 

types of quantitative assessment normally employed in analyses of this type. 

The basis for current RTO policy is described by the Commission in the following terms 

(in the context of then-existing policies under Order No. 888):

“In 1996 the Commission put in place the foundation necessary for competitive 

wholesale power markets in this country -- open access transmission. Since that time, 

the industry has undergone sweeping restructuring activity, including a movement by 

many states to develop retail competition, the growing divestiture of generation plants 

by traditional electric utilities, a significant increase in the number of mergers among 

traditional electric utilities and among electric utilities and gas pipeline companies, large 

increases in the number of power marketers and independent generation facility 

developers entering the marketplace, and the establishment of independent system 

operators (ISOs) as managers of large parts of the transmission system. Trade in bulk 

power markets has continued to increase significantly and the Nation's transmission grid 

is being used more heavily and in new ways.” (NOPR at 5) “Our objective is for all 

transmission owning entities in the Nation, including non-public utility entities, to place 

their transmission facilities under the control of appropriate regional transmission 

institutions in a timely manner.” (NOPR at 6)

“In April 1996, in Order Nos. 888 and 889, the Commission established the foundation 

necessary to develop competitive bulk power markets in the United States: nondiscriminatory open access transmission services by public utilities and stranded cost 

recovery rules that would provide a fair transition to competitive markets.” (NOPR at 14)

Prior restructuring efforts, according to the Commission, left important concerns 

unresolved and also led to the emergence of new issues. “In light of our experiences 

with ISOs and other utility restructuring activity in the aftermath of Order Nos. 888 and 

889, and after almost three years of experience with implementation of Order Nos. 888 

and 889, we believe that there remain important transmission-related impediments to a 

competitive wholesale electric market.” (NOPR at 36-37) Order No. 2000 discusses the 

current situation in which these problems are attributed to:

1. The decentralized industry decision-making structure and the inefficiencies that 

come with it;

2. Relatively high and volatile capacity flows across the system due to the leap in 

wholesale energy trading since Order No. 888; and
4

3. The persistence of the potential for market power abuses in the regional generation 

markets due to both concentration of incumbent utility’s generation assets and the 

potential for abuse the utility has, as manager of the transmission system, to favor its 

own units for dispatch over that of competitors.

The Commission discussed these problems in greater detail:

Reliability

“It is well accepted that the operation of interconnected transmission networks requires 

careful coordination and the exchange of information between many individual 

systems.” (NOPR at 43) “At present, the industry's ability to maintain reliable grid 

operation is hindered by the existence of many separate organizations that directly or 

indirectly affect the operation and expansion of the grid. There are more than 100 

owners of the Nation's grid who operate about 140 separate control areas. In addition, 

there are 10 regional reliability councils, 23 security coordinators, 5 regional 

transmission groups (RTGs) and 5 independent system operators. With so many 

entities, the lines of authority and communication are not always as clear as they should 

be. An additional complication is that many of these entities also own generation or 

have a decision making process that continues to be dominated by traditional vertically 

integrated utilities. Therefore, their independence and commercial neutrality as grid 

operators is subject to question.” (NOPR at 44)

Available Transmission Capability (ATC) and Total Transmission Capability

“ATC numbers are still calculated on an individual company basis in many areas of the 

country. Separate calculations of ATC by individual companies are fundamentally 

inconsistent with the physical reality of an interconnected transmission system.... 

Accurate ATC numbers would require reliable and timely information about load, 

generation, facility outages and transactions on neighboring sys tems. Individual 

transmission operators will generally not have this information. They also may apply 

differing assumptions and criteria to ATC calculations, which may produce wide 

variations in posted ATC values for the same transmission path.” (NOPR at 48) 

Congestion

“Congestion occurs when requests for transmission service exceed the capability of the 

grid. When transmission constraints limit the amount of power that can be transmitted, 

the loads on the system may not be able to be served by the least-cost mix of available 

generators... The cost of congestion is the additional energy cost associated with the 

new pattern of dispatch. Without mechanisms for determining the cost of congestion, it 

will be virtually impossible to make rational, cost effective decisions to expand the grid.” 

(NOPR at 50)
5

Planning and Expanding Transmission Facilities

“While uncertainty has always been a fact of life for any transmission planning exercise, 

the level of uncertainty has increased with the increasing number and distance of 

unbundled transactions and the wider variation in generation dispatch patterns... One 

troubling consequence of this uncertainty has been a noticeable decline in planned 

transmission investments. NERC recently reported that the level of planned 

transmission additions is significantly lower than five years ago despite an overall 

increase in load growth and unbundled transmission service.” (NOPR at 53)

Pancaked Rates 

“In most of the United States, a transmission customer pays separate, additive access 

charges every time its contract path crosses the boundary of a transmission owner. By 

raising the cost of transmission, pancaking reduces the size of geographic power 

markets. This, in turn, can result in concentrated electricity markets. Balkanization of 

electricity markets hurts electricity consumers, in general, by forcing them to pay higher 

prices than they would in a larger, more competitive, bulk power market.” (NOPR at 56)

Potential for Market Power Abuses

“Utilities that control monopoly transmission facilities and also have power marketing 

interests have poor incentives to provide equal quality transmission service to their 

power marketing competitors. The exercise of transmission market power allows 

transmission providers with power marketing interests to benefit in the short-run by 

making more power sales at higher prices, and benefit in the long-run by deterring entry 

by other market participants. As a result, prices to the Nation's electricity consumers 

will be higher than need be.

“Order 888 required functional unbundling of transmission services from generation 

services within the corporate structure of the utility. Functional unbundling did not 

change the incentives of vertically-integrated utilities to use their transmission assets to 

favor their own generation, but instead attempted to reduce the ability of utilities to act 

on those incentives. In Order No. 888, the Commission received and considered 

numerous comments that functional unbundling was unlikely to work, and that more 

drastic restructuring, such as corporate unbundling, was needed.” (NOPR at 59)

“Perhaps the most problematic aspect of relying on after-the-fact enforcement in the 

fast-paced business of power marketing, however, is that there may be no adequate 

remedy for lost short-term sale opportunities.” (NOPR at 63) 

Accurate Reporting of ATC

“Transmission providers with power marketing interests have incentives to understate 

ATC on those paths valuable to its marketing competitors, or to divert transmission

capacity so that it is available for use by its own marketing interests.” (NOPR at 67)
6

Standards of Conduct Violations 

“To ensure the functional separation of a transmission provider's transmission and 

merchant functions, the Commission adopted standards of conduct that prohibit the 

transmission provider's marketing interest employees from having any more access to 

transmission system information than is available on OASIS, and requires the 

transmission provider's transmission employees to provide impartial service to all 

transmission customers. If a transmission provider's marketing interests have favorable 

access to transmission system information or receive more favorable treatment of their 

transmission requests, this obviously creates a disadvantage for marketing competitors. 

“In spite of the standards of conduct, there continues to be a perception by many market 

participants that the transmission provider's marketing and transmission interests are 

not fully functionally separated. We are increasingly concerned about the extensive 

regulatory oversight and administrative burdens that have resulted from policing 

compliance with standards of conduct.” (NOPR at 79)

Conclusion

The Commission concluded, in summary, as follows:

“Order No. 888 has not been able to produce a fully efficient and competitive outcome 

because it does not address ATC calculations, congestion management, reliability, 

pancaking of transmission access charges, and grid planning and expansion. These 

are regional problems. Therefore, we are proposing a rule to encourage the 

development of independent regional transmission operators that can promote both 

electric system reliability and competitive generation markets.” (NOPR at 58)

The Commission’s regulatory discussion identified a series of factors that could give rise 

to inefficiencies in wholesale electric power markets. It also enumerated a set of 

potential economic benefits that could result from the RTO policy being advanced. 

However, there are also potential costs to such a policy, and the specific mechanisms 

that could tie RTO policy measures to economic impacts need to be carefully evaluated 

in order to assess the overall effects of the policy. The next section presents the set of 

benefits set forth by the Commission; the purpose of this analysis is to assess how 

these changes, along with other changes that might result from RTO policy, could result 

in both costs and benefits to the economy.

1.2.2 Prospective Benefits from the Commission’s RTO Policy

Appropriate regional transmission institutions could: (1) improve efficiencies in 

transmission grid management3; (2) improve grid reliability; (3) remove the remaining 

 

3Appropriate regional institutions could improve efficiencies in grid management through improved 

pricing, congestion management, more accurate estimates of Available Transmission Capability, 

improved parallel path flow management, more efficient planning, and increased coordination between 

regulatory agencies.
7

opportunities for discriminatory transmission practices; (4) improve market performance; 

and (5) facilitate lighter-handed regulation. 

RTOs Can Improve Efficiencies in the Management of the Transmission Grid

The Commission, in developing its policy with regard to RTOs, has stated that properly 

functioning RTOs would:

• “improve efficiency through regional transmission pricing. The Commission has 

long recognized that transmission pricing reform is most effectively accomplished 

on a regional basis.” (NOPR at 90)

• “improve the way congestion is managed over a large area, thus expanding the 

number of potential transactions over existing facilities while reducing the number 

of curtailments.” (NOPR at 91)

• “improve efficiency by providing more accurate estimates of ATC than those 

currently provided by individual systems. An RTO would produce better ATC 

estimates because it would have access to complete regional usage information, 

would have current information because the RTO will be the security coordinator 

as well as the OASIS site administrator, and would calculate ATC values on a 

consistent region-wide basis using a regional flow model.” (NOPR at 92)

• “more effectively manage parallel path flows. With an RTO in place, the 

geographic scope for scheduling and pricing transmission would be widened and 

parallel path flows would be internalized within the RTO.” (NOPR at 92)

• “promote more efficient planning for transmission or generation investments 

needed to increase transmission capacity. One advantage of an RTO that is 

helpful in planning is that it will be able to see the ‘big picture.’” (NOPR at 93)

• “increase coordination between separate state regulatory agencies by providing 

a single point of focus for transmission expansion review, possibly even 

encouraging multi-state agreements to review and approve new transmission 

facilities.” (NOPR at 94)

• Reduce transaction costs. “For example, the consolidation of transmission 

control operations would cut general and administrative costs over the long 

term.” (NOPR at 94)

• “facilitate establishing transmission rights and the ‘tradability’ of transmission 

rights.” (NOPR at 95)

• “facilitate the success of state retail access programs by providing greater 

confidence in the markets and a larger regional market with access to more 

potential suppliers.” (NOPR at 95)

RTOs Can Improve Grid Reliability

“A regional body that operates the regional grid and enforces reliability rules for the 

entire region could prove helpful to current efforts and should be considered. An RTO 

would enhance reliability by (1) operating the system for a large region, (2) ensuring 

coordination during system emergencies and restorations, (3) conducting 

comprehensive and objective reliability studies, (4) coordinating generation and 
8

transmission outage schedules, and (5) sharing of ancillary services responsibilities.” 

(NOPR at 96)

RTOs Can Remove Opportunities for Discriminatory Transmission Practices

“An RTO would have no financial interests in any power market participant, and no 

power market participant would be able to control an RTO. This separation will 

eliminate the economic incentive and ability for the transmission provider to act in a way 

that favors or disfavors any market participant in the provision of transmission service.” 

(NOPR at 96)

RTOs Can Result in Improved Market Performance

“By improving efficiencies in the management of the grid, improving grid reliability, and 

removing any remaining opportunities for discriminatory transmission practices, the 

widespread development of RTOs would also improve the performance of electricity 

markets in several ways and consequently lower prices to the Nation's electricity 

consumers.” (NOPR at 98) “To the extent that RTOs foster fully competitive wholesale 

markets, the incentives to operate generating plants efficiently are bolstered. Suppliers 

will continuously seek to avoid being made uncompetitive by rivals . . . The incentives 

for more efficient plant operation can also affect existing generation facilities . . .All 

plants are coming under pressure to improve their availabilities and operating 

efficiencies. Individual firms have made decisions to seek to become more competitive, 

or to prepare themselves for future competition.” (NOPR at 98-99)

RTOs Can Facilitate Lighter-Handed Governmental Regulation

“...To the extent an RTO is independent of power marketing interests, there would be 

no need for this Commission to monitor and attempt to enforce compliance with the 

standards of conduct designed to unbundle a utility's transmission and generation 

functions.” (NOPR at 102)

An independent RTO with an impartial dispute resolution mechanism would:

• resolve disputes without resort to the Commission complaint process.

• streamline filing and approval procedures.

• result in more streamlined transmission rate proceedings.

1.2.3 The RTO: Functions, Characteristics, and Form

Based on the considerations listed above, the Commission decided to proceed as 

stated:

“In light of important questions regarding the complexity of grid regionalization raised by 

state regulators and applicants in individual cases, we are proposing a flexible 

approach.” (NOPR at 8) “First, the Commission proposes minimum characteristics and 
9

functions that an RTO must satisfy.” (NOPR at 10) “A properly structured RTO will be 

an entity that is independent from all generation and power marketing interests, and has 

the exclusive responsibility for grid operations, short-term reliability, and transmission 

service within a region.” (NOPR at 116)

Minimum characteristics of RTOs:

• Independence from power market interests

• Scope and regional configuration

• Exclusive operational authority

• Maintain short-term reliability

Minimum functions of RTOs:

• Tariff administration and design

• Congestion management

• Parallel path flow

• Ancillary services

• Run a single OASIS node providing TTC and ATC information

• Market monitoring

• Planning and expansion

1.2.4 Developments Since Order No. 2000

Since the issuance of Order No. 2000, significant developments have taken place. The 

regulatory context of RTO policy has continued to evolve and to be informed by market 

events. The FERC has taken a number of actions that are relevant to the analysis 

undertaken here, as summarized in the following sub-sections.

Staff Investigation into Bulk Power Markets

The FERC issued a series of staff investigation reports after the issuance of Order No. 

2000. These staff investigation reports contained a wide range of observations and 

conclusions, and pointed out a variety of continuing inefficiencies and problems in bulk 

wholesale electric power markets. The Commission’s evolving policy regarding the 

transmission grid and RTO development can be seen as a response to these types of 

problems.

Each of the regional staff investigation reports is excerpted in this section, but the 

reports should be evaluated in their entirety for a full understanding of their contents.

Midwest Region

The Midwest staff investigation report discusses wholesale power prices from 1998-

2000. As the report explains:
10

"The summer of 2000 was relatively calm for Midwest wholesale prices. A number of 

factors contributed to this situation. As will be shown, the weather was cooler than 

normal, especially in the upper Midwest. Also, there were no widespread generation 

outages, as in the 1998 price spike when many nuclear plants were simultaneously 

down for maintenance. More generation facilities have been built in the Midwest, too. 

Finally, except for TLRs (Transmission Loading Relief episodes), there were no major 

transmission problems like the central Ohio voltage sag or the loop flow problems in 

1998 which threatened to isolate the Midwest from the rest of the grid."

"Table [1.1] shows the number of Level 2 TLRs and above, by region for each summer 

from 1998 to 2000. It tabulates the monthly and yearly totals for each region. The 

bottom row shows the total for each year and the grand total for all 3 years. There has 

been an enormous increase in TLRs between the summer of 1999 and the summer of 

2000. Specifically, TLRs have grown from 86 during the summer of 1999 to 492 for the 

summer of 2000, an increase of 472 percent. For this analysis, Staff only counted a 

TLR at its highest level. When a TLR escalated in Level while it was active, Staff only 

measured it as one occurrence."

Table 1.1: Level 2 TLRs and Above, Summer 1998-2000

Region 1998 1999 2000

Monthly 

Totals

Region

Total

ECAR

 June

 July

 August

ECAR Total

13

4

4

21

8

24

15

47

51

102

66

219

72

130

85

287

MAIN

 June

 July

 August

MAIN Total

40

25

21

86

10

3

12

25

31

92

75

198

81

120

108

309

MAPP

 June

 July

 August

MAPP Total

0

0

0

0

0

0

0

0

0

12

0

12

5

12

0

17

SPP

 June

 July

 August

SPP Total

0

0

0

0

4

6

4

14

27

20

11

58

31

26

15

72

All Regions 107 86 492 685

Source: FERC Congestion Management Team Reports compiled from NERC's website.
11

Western Region

The most recent staff report to be released is a follow-up to the Western region 

investigation. The report considers electric power prices at two Western market hubs 

(California-Oregon Border and Mid-Columbia) between February and September of 

2000, followed by prices for both natural gas and electric power in November and 

December of 2000.

"Although power market prices spiked at certain points over the summer, the recurrence 

of high prices over the longer term may have a greater impact on customer bills. Prices 

spiked less frequently as the summer progressed and California imposed price caps at 

lower levels, but average prices continued to climb.”

"In September and October, power prices appeared to be moderating from the 

sustained high levels of the summer. Prices continued to fluctuate considerably, but the 

trend was clearly downward from late August prices over $200 ($225 at Mid-Columbia 

on August 29) to prices under $100 in early November ($75 on November 4.) In midNovember, prices for natural gas and electricity started to rise again. The increases at 

first were small enough to be attributed solely to anticipation of the winter peak season, 

but then gas prices jumped over $10 per MMBtu and electricity prices rose to over 

$200. This significant trend was punctuated by dramatic increases in early December, 

but returned after the spikes subsided to close around $300 during the last week of 

December."

Northeast Region

In the Northeast region, the staff investigation examined three sub-regional markets 

(New England, New York, and Pennsylvania-New Jersey-Maryland or PJM). 

"With the moderate temperatures in summer 2000, and some market design changes 

undertaken to inhibit exercise of market power, energy prices have been lower in 

summer 2000 than summer 1999."

"The New York ISO has experienced major problems with its operating reserve markets. 

Prices remained reasonable from the start of the market until mid-January 2000, when 

prices for both 10-minute operating reserves climbed dramatically. The ISO suspended 

both markets in late March and applied a price cap.” 

“The monthly average price for 10-minute spinning reserve prices hit a peak of 

$73.27/MW in February 2000. Following the application of a price cap of $6.68/MW, 

prices declined substantially in April 2000, to a monthly average price of $3.51/MW. 

That price cap was later rejected by the Commission and removed. The monthly 

average price has ranged between $3.10/MW and $4.45/MW from April to September 

2000.”

“A similar pattern holds for 10-minute non-synchronous, or non-spinning, reserves. The 

average monthly price hit a peak of $65.58/MW in February 2000. Following application 
12

of a price cap of $2.52/MW in April, average prices declined substantially in this market 

as well, to $1.75/MW in April 2000. The monthly average price has ranged between 

$1.47/MW and $2.30/MW from April to September 2000.”

“Until summer 2000, the average regulation price was higher than the average energy 

price. This reflects market inefficiency. However, regulation prices have dropped over 

the course of summer 2000."

Southern Region

From the Southern regional report: "Peak prices were radically lower in the summer of 

2000 than they were in the past two summers . . . The peak price in the region in 1998 

was $2,386 per MWh. In 1999 it was $2,057 per MWh, but it was only $165 per MWh in 

2000.”

“The lower peak experienced this summer was due mainly to relatively lower 

temperatures for much of the summer in the Midwest. Lower temperatures in the 

VACAR sub-region relative to other regions in the Southeast increased the availability of 

generation to serve customers elsewhere in the Southeast. In addition, utilities appear 

to have been better prepared for peak events in the summer of 2000. According to 

utility interviews with the Commission staff, superior preparation took the form of 

increased hedging through the use of forward contracts, increased generation capacity 

on line and a reduced number of forced outages."

Staff Paper on Demand Responsiveness in Electricity Markets

Staff in the Office of Markets, Tariffs and Rates produced a paper on demand 

responsiveness in electricity markets that links market design and incentives for 

consumers to respond to electricity prices. This paper was revised on January 15, 

2001. 

The Executive Summary of the paper concludes:

“Past market designs and regulation have not promoted innovations in developing 

opportunities for demand side responses in electricity markets. The market rules in 

place today within ISO’s are poor substitutes for the benefits obtained from real demand 

response. The volatility in wholesale markets has demonstrated the importance of a 

demand response in times of scarcity. Demand responsiveness plays a vital role in 

increasing efficiency and reducing price volatility in the electricity markets. It allows 

customers to communicate the value of electricity to the market. Currently, advances in 

technology are leading to innovative pricing structures and generation alternatives to 

allow customers to better respond to prices. This can benefit all consumers by 

promoting efficiency and stability in electricity markets.”
13

Order of November 7, 2001 on State Coordination and Cost/Benefit Assessment

The Commission issued an order on November 7, 2001 concerning the process to be 

conducted on RTO filings and related matters resulting from Order No. 2000 

compliance.

This order states in part: “The FERC has before it numerous ongoing proceedings 

involving RTO proposals, and it has recently assessed the status of these proceedings 

and the ongoing changes in the electricity marketplace. Taking into account the various 

stages of RTO efforts in the country, and the industry and state comments we have 

received in recent weeks (discussed below), in this order we state some of our goals 

and provide general guidance on how we intend to proceed on RTO filings and other 

related efforts.”

“The Commission intends to complete the RTO effort using two parallel tracks. The first 

track will be to resolve issues relating to geographic scope and governance of qualifying 

RTOs across the nation; these will be addressed in pending RT dockets following 

consultation with state commissioners as discussed below.”

“The second track for resolving RTO issues will be in the transmission tariff and market 

design rulemaking for public utilities, including RTOs, in Docket No. RM01-12-000. This 

will help address business and process issues needed for organizations to accomplish 

the functions of Order No. 2000.”

“The FERC will take several immediate steps to move the RTO process along these 

tracks: (1) a broader definition of how certain RTO functions will be fulfilled; (2) better 

state/federal dialogue; (3) further cost/benefit studies; (4) identification of areas where 

standardization is called for; and (5) creation of a time line for RTO implementation.”

The portion of this order that calls for the present study reads as follows:

“C. Cost/Benefit Studies

“On a parallel track to the organizational efforts listed above, the Commission will 

perform additional cost-benefit analyses on RTOs to guide our further efforts. These 

analyses are intended to demonstrate whether and, if so, how RTOs will yield customer 

savings and to provide a quantitative basis for the appropriate number of RTOs.”

“The Commission has established a working group with state commission participation 

to work with FERC staff and the study consultant in framing these further analyses.”

1.3 Related Studies

A number of organizations have already conducted some type of quantitative impact 

analysis of RTO policy or related matters. For purposes of comparison, the following 
14

section provides brief synopses of several of these studies, the methodologies they 

used, and their principal findings. 

1.3.1 FERC Order No. 888 Environmental Impact Statement (National, FERC/EIS0096)

In April of 1996, the FERC released the Order No. 888 Notice of Proposed 

Rulemaking’s Environmental Impact Statement (EIS). The EIS was geared primarily 

toward calculating the possible effects of Order No. 888’s open access transmission 

policy on national air emissions from the electric power system including NOX, SO2, and 

CO2. The EIS also produce a bounded quantitative estimate of potential system 

savings of approximately $3.8 to $5.4 billion per year resulting from changes, including 

lower transmission access charges and transmission capacity reserve margins, that 

could be produced by the open access policy.

The FERC retained ICF Consulting to conduct the electric system simulation work for 

the EIS using the Coal and Electric Utility Model (CEUM). CEUM is a computer-based 

linear programming model with detailed representation of all electric generating facilities 

in the US. The model is used to determine the least cost means of meeting electric 

generation energy and capacity requirements while complying with specified air 

pollutant regulations. CEUM is forward-looking and optimizes the system over an 

extended time frame.

FERC defined several scenarios that were analyzed using CEUM to produce estimates 

of total emissions and economic gains from the Order No. 888 policies. The economic 

gains presented in the EIS were based on the following improvements (over a businessas-usual case) that the conditions from Order No. 888 would create:

• Better use of existing infrastructure;

• New market mechanisms;

• Faster technological innovation; and

• Less rate distortion and greater customer choice.

To quantify the potential magnitude of these economic gains, FERC identified the 

following specific improvements that were analyzed within the CEUM modeling 

framework:

• Lowered inter-regional transmission tariffs

• Decreased reserve transmission capacity 

• Improvement in power plant availability and performance

The EIS concluded that air emissions under several iterations of an open access 

scenario would not be significantly affected on a national basis. Notably, in all 

scenarios run, the relative price of gas and coal tended to be a more powerful driver of 

emissions levels than transmission access policy.
15

The EIS did not address several issues that were potentially important from a legislative 

perspective. Due to CEUM’s forward-looking nature, all operational dispatch and 

capacity upgrade decisions that affected the results reported in the EIS are made on a 

marginal-cost basis. Some cost issues involving the stock of existing or sunk capital, 

such as so-called “stranded costs” are not captured in CEUM calculations of potential 

costs or benefits. The EIS also did not attempt to treat state jurisdiction or power plant 

siting issues as they were outside of the scope of the FERC’s authority.

The Order No. 888 EIS represents an early attempt to bound the potential savings from 

reduced barriers to transmission access on a national scale. While its scope was 

limited to specific system elements such as transmission charges and capacity reserve 

margins, the EIS provided quantitative estimates of the potential cost of existing 

transmission system inefficiencies at the time of its publication.

1.3.2 Supporting Analysis for the Comprehensive Electricity Competition Act 

(National, DOE/PO-0059)

In early 1999, The DOE published the supporting analysis for the Clinton 

Administration’s proposed Comprehensive Electricity Competition Act (CECA). The 

report describes and quantifies the economic and environmental benefits of competition 

in retail electricity markets. The analysis produced a quantifiable cost savings estimate 

of switching to a competitive system of approximately $32 billion in the year 2010, as 

well as reductions in CO2 emissions, relative to a base case. 

According to the CECA analysis, competition provides strong economic incentives to 

raise productivity, encourages sellers to pursue efficient pricing practices, spurs 

development of innovative products and services that add value and better meet 

customer needs, and in the long run leads to increased productivity, new services, and 

better use of resources that will benefit the overall economy and electricity consumers.

The CECA analysis also described competition as having the following environmental 

benefits: Incentives to use fuel more efficiently (cutting emissions, costs, and fuel use) 

and retail-level customer access to energy efficiency services and green power, thereby 

decreasing air emissions from fossil-fueled power plants.4

The analysis uses the Policy Office Electricity Modeling System (POEMS) to simulate 

the US power market under Cost-of-Service Regulation and Competitive scenarios with 

a focus on economic and environmental impacts of a national transition to competition. 

The POEMS system is computer simulation model of the national electric power 

system, configured at the control area level and representing both short run operations 

and long run investment in a least-cost optimization framework.

 

4 The CECA also contains special provisions for energy efficiency and renewable energy development. 

Although greater market competition alone is not expected to lead inevitably to increased renewable 

energy capacity or utilization of energy efficiency resources, it will allow consumers access to alternative 

means of meeting their energy needs. To help maximize the reliance on alternative resources, the CECA 

proposes a renewable portfolio standard (RPS).
16

Although it did not isolate any specific state efforts to transition to a competitive market 

model, the analysis did incorporate some of the common elements in state deregulation 

processes in an attempt to realistically assess the probable course of deregulation on a 

wider scale. The focus of the analysis is a quantitative assessment of the impacts of 

national retail competition relative to a continuation of cost-of-service regulation that 

includes wholesale competition.

The report found the following results in comparing the two scenarios (Cost-of-Service 

Regulation vs. Competition Scenarios5):

Economic:

• Delivered cost of electricity to all consumers $32 billion lower in 2010 than in the 

Cost-of-Service Scenario, including estimates of stranded costs, recovery 

impacts and higher capital build costs in competitive scenario; 

• Average national price of electricity estimated to be 14 percent lower than Costof-Service;

• Regions with highest prices under cost-of-service regulation tend to gain largest 

reductions in price under competition;

• Cost reductions for investor-owned and public utilities: O&M, administrative and 

general costs, more efficient use of transmission and distribution, and capital cost 

savings (estimated to exceed $20 billion a year).

Environmental:

• Generation of electricity from Renewable Portfolio Standard-eligible renewable 

energy resources is projected to triple by 2010 as a result of a cost cap provision 

in the RPS proposal;

• Emissions of CO2 are reduced by between 40 and 60 million metric tons carbon 

equivalent in 2010 due to the effects of competition itself, and enhanced by an 

RPS provision, a public benefits fund, and a consumer information provision;

• NOX and SO2 emissions are subject to caps under the CAA, so their emissions 

are projected to be similar under competition and cost-of-service.

The CECA is not a full cost-benefit analysis, and is intended to analyze a transition to 

full retail competition (as opposed to the Commission’s jurisdictional interest in 

wholesale competition). It does, however, provide a quantifiable estimate of total retail 

savings under a deregulated market system. Moreover, the CECA report incorporates 

an assessment of stranded cost recovery impact on the total system costs if the US 

were to transition to a competitive market, a relatively rare element of most goingforward competitive policy impact assessments.

 

5 The year 2010 was chosen as a comparison year to show the effects of competition in a medium-term 

view.
17

1.3.3 FERC Order No. 2000 Environmental Assessment (National)

In 1999 the FERC contracted with ICF Consulting to prepare an Environmental 

Assessment (EA) to analyze the impacts of implementing the Commission’s proposed 

rule on RTOs, Order No. 2000. Although the EA was not meant to provide economic 

cost-benefit analysis, its methodology was similar to the study conducted for this report. 

The EA indicated changes in air pollutant emissions and generation, key market drivers 

of national energy markets, under the proposed rule compared to baseline trends 

without the rule. 

Building on its earlier work on the EIS, ICF used the successor model to CEUM, the 

Integrated Planning Model (IPM®) to perform the work required by the EA. To simulate 

the effects of the proposed rule, ICF calibrated the model by incrementally adjusting 

transmission tariffs among NERC regions for simulations of 1998, until model 

generation results (by fuel mix and total MWh) reflected the actual 1998 generation mix 

in those regions to within 5%. As in the earlier Order 888 EIS, FERC identified a 

number of scenarios to be analyzed including:

• A lowered transmission tariff scenario to represent the removal of non-physical 

transmission constraints under the proposed rule

• A high-transmission capacity scenario

• A high generation efficiency scenario

• A high new market entrant scenario

• A “No-Action Alternative” case representing the status quo

The results indicated that the proposed rule would result in little generation change on a 

net national basis, but that there may be shifts in regional generation. The Midwest, for 

example, was expected to produce incrementally more power and the East Coast to 

produce incrementally less power. In addition, the EA indicated that the proposed rule 

would incrementally shift the baseline fuel mix projections toward coal and away from 

fuel oil (and to some extent natural gas). Air pollutant emissions, corresponding 

generally with generation and fuel mix, would also shift regionally but would not rise or 

fall significantly nationwide and would remain within regulated levels where such 

restrictions apply.

1.3.4 Mirant Study and LECG Response (Northeast)

Mirant commissioned Energy and Environment Analysis, Inc. (EEA) to perform an 

assessment (the Mirant Study) of potential efficiency gains from the integration of the 

three primary Northeast ISOs--PJM, New York, and New England--into a single RTO. 

EEA conducted an analysis of publicly available market price and energy flow data to 

provide evidence of transmission system inefficiencies in the Northeast. The study 

estimated impacts for a one-year snapshot based on year 2000 information. EEA 

determined a total annual efficiency savings of $440 million was available if the 

Northeast adopted an RTO system. EEA used the following methodology.
18

To test the current efficiency of the interregional transmission system, EEA compared 

year 2000 hourly wholesale energy prices from real-time and day-ahead markets across 

the three regions alongside actual energy flows between the adjacent regions. EEA 

posited that in a liquid energy market, these prices should be kept from converging only 

by physical transmission constraints between higher and lower priced areas. EEA 

compared the transmission constraints to the operational and market boundaries of the 

ISOs and concluded that no primary transmission constraints subdivide the Northeast 

region along currently drawn limits and that the existing ISO boundaries are based on 

political rather than physical constraints. 

EEA surmised that the fundamental differentiation among regions in the Northeast 

energy markets is an East-West split based on fuel type. The majority of installed 

capacity in the West is coal- or nuclear-fueled, while more units in the East burn oil or 

gas. According to the Mirant study, this difference should impact energy prices, 

especially during peak gas demand periods in midwinter and midsummer in New 

England. But it should not be able to sustain the price differential between two adjacent 

ISOs where transmission capacity is available to move the low-price energy to the highprice region.

By examining instances where both available transmission capability (ATC) and a price 

differential existed between any two regions, EEA calculated a total annual efficiency 

loss of $440 million to the Northeast. EEA asserted that where there is ATC between a 

high-price and a low-price region, it is reasonable to assume that the $440 million 

efficiency loss is the result of operational failings in the greater northeast energy market. 

EEA attributed the operational failings to differences among the three ISO systems: 

“Differences in a variety of market-related rules, such as varying 

transmission rights, products and transmission scheduling systems, and 

different energy market structures (e.g., the lack of a “Day-ahead” energy 

market in New England) contribute to inefficiency”. (FERC Affidavit, 

Vidas&Henning/EEA p3)

According to EEA, these differences among the ISOs produce irreconcilable seams 

issues between adjacent transmission regions under the existing transmission market 

structure. Furthermore, although the Northeast could take steps to mitigate these 

seams problems, it would only realize the total efficiency gains by eradicating the seams 

altogether by adopting a single RTO system.

1.3.5 NYISO/LECG Response (Northeast)

New York ISO hired LECG, LLC to conduct a review and analysis of the Mirant Study. 

LECG replicated EEA’s methodology and conducted several sensitivity analyses using 

the data for the same time period and for an extended time period. While LECG did not 

take issue with the Mirant Study’s findings that differing market rules and design among 

the Northeast regions were to blame for the operational inefficiencies, it did question the 

magnitude of those inefficiencies and sought to show that EEA’s methodology was 

flawed and led to erroneous final figures. According to LECG’s report, the Mirant Study
19

• Compares real-time flows with day-ahead prices;

• Ignores real transmission constraints;

• Bases part of its conclusions on prices from NEPOOL, which does not use 

locational marginal pricing like NYISO and PJM do;

• Relies on overly flat supply curve estimates; and

• Focuses on a startup period for PJM’s day-ahead market and ISO NY as an 

operational entity.

According to LECG, correction of these elements in EEA’s methodology would 

drastically reduce the price efficiency savings that would result from combining the 

Northeast ISOs. LECG also claimed that the energy cost savings in New York would be 

minimal, and might even increase by as much as $90 million per year.

1.3.6 PJM Study (Northeast)

More recently, PJM conducted its own analysis (the PJM Study) of the costs and 

benefits of establishing an RTO in the Northeast. PJM used the GE Multi-Area 

Production Simulation (MAPS) to simulate the operation of Northeast energy grid for the 

year 2001 under several scenarios: a base case, a high demand scenario, and a low 

demand scenario. For each scenario, PJM ran the model under an ISO system 

assuming independent ISOs in each region, and under an RTO system, assuming RTO 

control of the entire Northeast. The run results, though varying significantly across 

scenarios, each confirmed an overall system savings to consumers, although those 

savings accrued most heavily to the New York region. In addition, most consumer 

savings carried a corresponding drop in operating profit to the generators in the regions 

where the savings occurred. For example, the base case scenario reported annual 

system savings to consumers of $299 million, even though costs to consumers actually 

rose in PJM and New England by roughly $70 million each. The results are discussed 

in greater detail below.

PJM used the following assumptions: 

• NERC load forecast for 2001; 

• A cost-based generation offer curve utilizing data from Resource Data 

International; 

• Economic transfers among regions based on historic averages from the past 7 

years; 

• Firm generation capacity additions announced for 2001; 

• No upgrades to the transmission system; and

• Phase angle regulators (PARs) not fully coordinated across ISOs.

 

For both the base case and RTO case, PJM modeled the hourly dispatch for 8760 

hours under three scenarios in a Locational Marginal Pricing (LMP) market. LMP 

markets determine transmission costs on a nodal supply-to-load basis. Depending on 

demand, supply, and constraints between nodes, each node was assigned an hourly 
20

market clearing price for energy by the model. In the ISO case, each ISO represented a 

power pool with a series of dedicated nodal market points. The power pools could trade 

energy at contact points with adjacent pools, but were run as individual markets. In the 

RTO case, the region was run as a single power pool with node-to-node costs 

calculated across the Northeast.

PJM reported results in three categories: generation production cost, load payments 

(based on spot purchases), and generation revenue (based on spot purchases). The 

results from the Base Case scenario are provided in Table 1.

Table 1.2: PJM Study Results

(Million 2001$)

Parameter

Northeast 

RTO Total

PJM

Total

New York

Total

New England

Total

Load 

Payments

-299 71 -432 62

Generation 

Production 

Cost

-222 252 -640 166

Generator 

Revenues

-259 511 -1,094 324

Source: PJM, PJM Cost/Benefit Analysis for Northeast RTO, DRAFT, 1/04/2002, p. 7.

Although generator production costs rose in PJM and New England, in both cases 

generator revenues rose by a greater margin. The reverse was true of New York, 

where the consumers realize a savings of $432 million, but the net revenue to 

generators decreases by $434 million. The sensitivity scenarios returned similar 

patterns of gains and losses, although the welfare distributions tended to be magnified 

in the high demand case and diminished in the low demand case.

In addition to the net system costs, PJM also provided an estimate of $71 million in 

startup costs for the proposed RTO, most of which would be attributed to extending 

PJM’s existing system architecture to New York and New England. PJM assumed the 

existence of administrative savings from switching to an RTO system, but did not 

provide a dollar estimate in its preliminary findings. At the time of this publication, the 

PJM Study results are tentative.

1.3.7 RTO West Benefit/Cost Study (Preliminary Report, Northwest)

In February of 2002, Tabors Caramanis & Associates (TCA) released the Preliminary 

Status Report (PSR) of their cost-benefit analysis for RTO West. TCA integrated a 

simulation of the WSCC NERC region electric system with a series of specialized extramodeling analyses to create a report that addresses multiple aspects of the proposed 

transition to an RTO in the northwest region of the US.6 Although they are still 

 

6 The following utility service areas are to be consolidated under the RTO West proposal: Avista Corp., 

Idaho Power Company, Montana Power Company, PacifiCorp, Portland General Electric, Puget Sound 
21

preliminary at the time of this writing, the results of the modeling process show that a 

net annual benefit to the RTO West territory of $358 million is available if it were 

operated as an RTO. According to the PSR, the greater WSCC region also stands to 

gain $400 million each year in efficiency savings from the formation of RTO West.

Like the PJM Study described above, the RTO West study uses the GE MAPS model7

to simulate the possible impacts on generation costs and levels, energy flows across 

regions, and final energy prices for a single year -- 2004. TCA simulates operations in 

the WSCC area using a sub-regional breakdown of RTO west, CAISO, and the 

WestConnect ISO under two cases, a “With RTO” case and a “Without RTO” case. In 

the future, TCA plans to expand its analysis to test multiple sensitivities, such as 

alternative energy demand scenarios.

As per the request of the RTO West, TCA assumed that an RTO would provide the 

following benefits to its service area:

• Elimination of pancaked transmission capacity and loss charges;

• Better sharing of operating reserves;

• Better coordination of scheduled O&M;

• Internalized loop flows;

• More competitive generation markets;

• Lower transaction costs;

• Improved ATC;

• Maintenance of a single OASIS site;

• Better regional reliability; and

• Better transmission planning and expansion coordination.

TCA captured the proposed benefits in the modeling process via the following 

adjustments to the “Without RTO” case:

• Transmission rates between the three WSCC regions - raised for transfers 

between RTO West and the adjacent regions, leveled to and from WestConnect, 

and kept unchanged for CaISO;

• Plant O&M scheduling - optimized among all units at the regional rather than 

sub-regional level;

• Reserve margins reduced;

• Internal RTO tariffs and pancaked rates - removed, as was contract path 

scheduling for transmission flows; and

• Pancaked loss charges - reduced to zero within the RTO West territory.

 

Energy, Sierra Pacific Resources (Sierra Pacific Power and Nevada Power), Bonneville Power 

Administration, and BC Hydro. 

7 Some of the features of the GE MAPS model noted in the PSR are: unit-by -unit marginal cost bidding in 

a real-time market; a region-by-region market clearing price (locational marginal pricing [LMP] aggregated 

up to zonal prices); and a cost of congestion calculated as the transmission shadow-price multiplied by 

the MWh energy flow.
22

The results of the simulation show annual region-wide savings of having RTO West 

operate the transmission system of roughly $358 million. TCA uses three metrics to 

estimate the net benefit: production costs, producer revenues, and energy costs paid by 

load. In the With RTO Case, RTO West operations provide energy cost savings to load 

of nearly $1.6 billion8 and a corresponding drop in producer revenues of roughly $1.2 

billion. Production costs for the region rise by about $37 million. To arrive at a net 

benefit estimate, TCA subtracts the revenue loss to producers ($1.2 billion) from the 

load energy cost savings ($1.6 billion) and then adds the additional production costs 

($37 million) to arrive at a final benefit of $358 million. A sensitivity case assuming 

lower inter-RTO charges results in benefits over $400 million.

The PSR shows net welfare gains for all sub-regions within the proposed RTO area. 

Whether these gains accrue more heavily to load or to supply varies from region to 

region. The natural tendency is for consumers in high-cost regions to benefit from 

access to wider supply and for producers in low-cost regions to benefit from access to 

higher-price markets. Average energy prices9in all sub-regions within RTO West drop, 

with the exception of Montana, where prices rise nearly 3%.

The PSR shows no overall trend for transmission capacity congestion. Some lines are 

fully utilized more often while others tended to experience less congestion. According 

to the TCA, however, the major inefficiency of the non-RTO transmission system comes 

from the practice of contract path scheduling; a mechanism that poorly reflects actual 

energy paths, especially loop flows. In short, poor management of existing transmission 

capacity, as opposed to capacity shortage, in the RTO West area is the principle culprit 

in current system efficiency losses.

In a separate section of the PSR, TCA provides estimates of RTO startup and O&M 

costs independent of the simulation effort. Start-up investments are offered from 

studies on and previous experience with regional organizations (ISOs). TCA also 

provides “ball park” approximations for annual O&M costs for RTO West in the range of 

$126 to $146 million per year based on the same regional information. It did not, 

however, offer a cost for the same total transmission area under the Without RTO Case. 

The total cost of running the transmission system is expected to be lower in an RTO, 

however, due to the elimination of redundant functions among transmission regions and 

the consolidation of tasks and information in a single operating center.

In addition to the analysis above, the PSR makes qualitative investigations into other 

RTO topics such as increased information exchange among market participants, better 

system coordination, market consolidation, and organizational relationships. TCA 

discusses the potential impacts of the integrated market processes under an RTO 

system; they may make the system more efficient but also may add to the complexity. 

Furthermore, TCA notes that many of the proposed benefits of RTO West may be 

 

8 Including $246 million in spinning reserve payments and $2.3 million in uplift charges, both of which are 

paid by load.

9 Simple average, not load-weighted in PSR.
23

achieved due to the natural progression of the energy system, absent an official RTO 

policy.

1.3.8 Conclusions

An increasing amount of research and information is becoming available about the likely 

or potential impacts of RTO development on regional and national electric power 

markets. While the studies summarized above rely on disparate methodologies, data 

sets, and scopes, it is important to make use of all relevant information in drawing 

conclusions about the potential costs and benefits of RTO policy.

Because the FERC has regulatory responsibilities across the entire country, the most 

comparable analyses are the limited set of national analyses previously carried out by 

the DOE and the FERC. The longer time frames and dynamic analysis in these 

previous studies are also more comparable to the present study. While the recent 

studies focusing on the Northeast region and the West were limited in terms of 

geographic scope and time frame, they provide an interesting basis for comparing 

results. When similar conclusions can be drawn from several parallel and robust 

analytic methods, it suggests greater confidence in such conclusions.

In developing the analytic approach for the present economic cost/benefit study, both 

the regulatory context and related work provide useful starting points. The next section 

describes the set of analytic requirements that this study is intended to meet, based on 

the forgoing contextual and background material.

1.4 Basis for Analytic Approach

In conducting this study, an analytic approach was developed to meet the requirements 

imposed by both the nature of the issues and the resources available. The foregoing 

sections discuss the context of the study, the issues to be addressed, and the analytic 

approaches that have been used in related studies. These issues, and the available 

methods for addressing them, resulted in a challenging set of requirements for this 

economic cost/benefit analysis.

Requirements for the Present Study

Three-Month Schedule: A major challenge for this study was a 90-day schedule. This 

limited both analytic methods and data development. Analytic methods had to be well 

tested and immediately available, while data and assumptions had to be taken from 

existing sources and/or developed over a short time period.

National Scope: The national scope of the Commission’s jurisdiction meant that the 

study had to address economic issues across the entire contiguous US. Interactions 

among the electric power systems in various regions, and consequent market and 

economic impacts, required the study to use a single national framework for making 

quantitative assessments.
24

Regional Representation: Within the overall national scope of the study, regional levels 

of detail had to be represented. This applies to both physical elements of the power 

system and to the associated economic characteristics of these system elements. Thus 

a great deal of detailed data had to be incorporated into one national analytic 

framework.

Long-Term Time Frame: The electric power system is characterized by capital intensity 

and takes time to react to new incentives. In addition, national policy can have longlasting impacts on the economy, and regulatory cost/benefit assessment should be able 

to assess such potential impacts over a period of years or decades. At some point 

impact assessment becomes too speculative, and the discounted present value of 

impacts becomes less important over time. But the present study had to take into 

account a reasonably long time horizon, not simply a one-year ‘snapshot’.

Dynamic Assessment: Once impacts are being assessed over time, the dynamics of 

economic decisions and interactions become important. In particular, capital investment 

decisions are partly determined by expected future conditions. Consequently, this study 

had to use an analytic approach based on a dynamic framework to estimate how the 

power system might be operated in any given time period in which operating decisions 

take expectations of future system conditions into account. 

Integration of Generation and Transmission: Another important characteristic of the 

electric power system is the tight linkage between the transmission grid and power plant 

operating decisions. As a network industry, electric power flows and feasible 

transactions are limited by transmission capacity under real-time operating conditions. 

Many of the key policy issues involved in the Commission’s RTO policy also concern 

aspects of the transmission system. This requires an analytic framework that 

represents the transmission grid and its interactions with power generation.

Differentiation of Load Segments: Varying levels of demand (load) create quite different 

sets of system conditions in this industry. This is because of the changes in marginal 

costs of generation as more expensive power plants respond to higher demand, and the 

fact that different transmission links become full or congested as load increases. This 

means that the analytic framework must take varying load levels (load segments) into 

account.

Interregional Energy Flows and Capacity Markets: Interchanges between regions 

provide the basis for effective energy markets, allowing for price equilibration when 

transmission capacity is available and establishing price signals for operating and 

investment decisions. The framework used for this analysis thus had to be able to 

assess such interchanges on an economic basis, and to take them into account over 

time for dynamic analysis. 

Accounting for Transmission System Investment: Investment in transmission system 

upgrades, including new lines and enhancement of existing line transfer capabilities, is 
25

especially relevant to assessment of RTO policy. Some form of accounting for such 

investments is another analytic requirement of the present study.

Using the issues identified by the Commission and building on previous work done by 

FERC and others, a foundation for this cost/benefit study has been established that 

ensures sufficient scope and analytic rigor. Where certain issues cannot be 

incorporated into a dynamic, long-run quantitative framework, they have been identified 

and efforts made to assess their impact using other methods. Similarly, where issues 

raise questions that go beyond the available resources or scope of this analysis, they 

have also been identified and suggestions made for further research. 

The next section of this report lays out the analytic approach developed for national 

economic cost/benefit assessment of RTO policy. It also describes the development of 

a number of alternative scenarios intended to represent uncertainty and to identify 

critical factors that determine the outcome of the analysis, and the detailed assumptions 

that were employed in the analysis. Results are presented and discussed in the 

concluding section.
26
27

2 Analytic Approach

The preceding section describes a number of requirements for an analytic framework 

designed to conduct an economic cost/benefit assessment of RTO policy. By 

identifying a set of potential changes to the operation of the electric power system, and 

resulting economic performance, this basis for developing an analytic approach seeks 

to be both comprehensive and rigorous, employing sufficient quantitative detail to 

accurately represent potential outcomes of RTO policy. Close collaboration with the 

Commission and cooperative efforts with other researchers and state regulators were 

an integral part of the scenario development process, resulting in an analysis that 

attempts to estimate a range of potential economic impacts using the best available 

information from a variety of sources.

In most sectors of the economy, such assessments are conducted using techniques of 

industrial economics and institutional analysis. However, the characteristics of the 

electric power sector make it particularly well suited for computer simulation modeling. 

Such models have been used for planning and analytic purposes for decades, owing to 

the interconnected nature of the transmission grid, the prevalence of centralized 

dispatch for generation, relatively small number of decision agents, and high quality of 

data.

Taking advantage of the benefits of computer simulation modeling allows for nationalscale analysis using extremely detailed models that are well tested. Most other 

economic sectors are represented poorly in national computer simulation models, 

typically at a high level of aggregation into simple production functions. The ability to 

utilize detailed optimization models gives an analytic advantage to studies in the electric 

power sector.

In this study, FERC produced estimates of economic impacts associated with the 

proposed policy primarily using ICF’s IPM® computer simulation framework. The IPM®

modeling framework is based on detailed, generation unit-level, publicly reviewed 

assumptions with regard to the costs and performance of electric power supply options, 

with full integration of fuel and environmental markets. IPM® has been used to support 

public agencies including the FERC in the preparation of formal rulemakings, and has 

undergone extensive public review and comment on technical aspects of the modeling 

framework. 

While the IPM® framework is a central element of this cost/benefit analysis, there are 

critical topics that cannot be directly addressed using this particular computer simulation 

model. By placing the IPM® analysis into a broader overall framework, this study 

provides a quantitative context for consideration of the economic issues involved in 

RTO policy. When possible, issues falling outside the scope of the study or beyond the 

immediate analytical assessment are placed in perspective and suggestions made 

regarding the role of further analysis.
28

This section first discusses the IPM® framework. Next, it describes the scenarios used 

to evaluate the RTO policy. Finally, it discusses how IPM was used to model the 

scenarios and details key assumptions of the analysis.

2.1 Integrated Planning Model Overview

ICF’s national Integrated Planning Model (IPM®) combines wholesale electric markets, 

air pollution regulations, and fuel markets into one integrated framework. IPM® is a 

computer-based linear programming model with detailed representation of every electric 

boiler and generator in the US. The model is used to determine the least cost means of 

meeting electric generation energy and capacity requirements, subject to transmission, 

fuel and air pollution limitations.

The following figure illustrates the integrated analytic approach that informs this part of 

the analysis. As discussed in later parts of this section, assumptions concerning the 

regulatory scenario to be simulated, cost and performance of new generation 

technologies, electric market conditions, transmission limits, and fuel supply and 

transportation costs are combined into model scenarios and input into the IPM®

framework.

Figure 2.1: Integrated Analytic Framework

All IPM® regions have a representation of the electric transmission system that connects 

neighboring regions. The inter-regional transmission connections allow for the transfer 

of both capacity and energy and allow for broad price equilibration when transmission 

Existing and New 

Generation 

Technologies

RTO Regulatory 

Scenarios

•Electric Demand

•Gas Supply

•Coal Supply

Environmental 

Compliance 

Technologies

and Costs

•Capacity Additions

•Fuel Consumption

•Electric Prices

•Capital, O&M, and Fuel 

Costs

•Emissions

IPM

Existing and New 

Generation 

Technologies

RTO Regulatory 

Scenarios

•Electric Demand

•Gas Supply

•Coal Supply

Environmental 

Compliance 

Technologies

and Costs

•Capacity Additions

•Fuel Consumption

•Electric Prices

•Capital, O&M, and Fuel 

Costs

•Emissions

•Capacity Additions

•Fuel Consumption

•Electric Prices

•Capital, O&M, and Fuel 

Costs

•Emissions

IPM
29

capability is available. These transmission links are aggregated from line-specific data 

and form a transportation-type network, which is not intended to assess engineering or 

reliability limits on a short-term basis but rather to represent a reasonable estimate of 

long-term transfer limits. IPM® divides the US markets into model regions based on 

persistent transmission bottlenecks (i.e. sub-regions in which spot prices are expected 

to diverge significantly). For this study, a total of 32 US regions were modeled in order 

to best capture the effects of RTOs on the national grid.

2.2 Modeling Scenarios: Base Case and Policy Scenarios

For this study, IPM® is used to analyze three main Policy Scenarios and two Sensitivity 

Cases developed by FERC to quantify the benefits described in FERC Order No. 2000. 

These cases are evaluated relative to a Base Case that assumes that regulatory and 

market conditions reflecting Order No. 888 as a no-RTO status quo govern the 

wholesale power market over the entire time horizon of the study. The policy scenarios 

differ from the Base Case in that they reflect an RTO structure as envisioned in Order 

No. 2000. The Sensitivity Cases isolate specific aspects of the scenarios, such as the 

RTO regional specification, to examine particular policy issues and indicate how key 

assumptions drive modeling results.

2.2.1 Base Case

The purpose of a Base Case is to establish points of comparison for policy analysis and 

to show how underlying trends in power markets play out in the IPM® framework. The 

Base Case represents current estimates of underlying market conditions and regulatory 

policy under Order No. 888, including market inefficiencies that exist within and across 

regions. Base Case assumptions are provided later in this chapter.

2.2.2 Policy Scenarios

The policy scenarios are defined to explore the five categories of benefits listed in 

Section III.B of Section 1 in Order No. 2000:

• RTOs would improve efficiencies in the management of the transmission grid;

• RTOs would improve grid reliability;

• RTOs would remove opportunities for discriminatory transmission practices;

• RTOs would result in improved market performance; and

• RTOs would facilitate lighter-handed governmental regulation.

Estimates of these benefits, to the extent that they affect elements of the electric system 

that are represented by model parameters, are made through comparison of the Base 

Case and policy scenario projections. 

The RTO initiative is expected to increase power trading through better management of 

transmission infrastructure. The elimination of pancaked rates, better congestion 

management, internalization of loop flow effects, elimination of transmission related 
30

market power, and availability of more reliable ATC values all impact the power markets 

in the direction of removing transmission related barriers to competitive wholesale 

power markets.

The formation of RTOs is also expected to increase market liquidity. Markets function 

better when increased liquidity allows for more participants through price revelation, 

information transfer, and choices for both buyers and sellers. Greater liquidity can be 

achieved by lowering barriers to trade. There is thus a logical connection between a 

better functioning transmission grid, which serves as the transportation system for the 

power market, and improved market function in general.

For example, in an illiquid market, it is more risky for market participants to rely on 

short-term spot markets for final energy delivery, and it is more advantageous for 

owners of generation to hold back supply, partly in order to ensure they can meet their 

own delivery obligations. This can lead to increased reliance on higher-priced forward 

markets (relative to an optimal mix of spot and forward markets) and increased real-time 

reserve requirements.

Improvements in the functioning of power markets due to better utilization of the 

transmission infrastructure are also expected to impact some of the engineering and 

economic fundamentals of these markets. Increased opportunities for selling power in a 

larger area will heighten competition for customers, and thus would increase incentives 

for power plants to function more efficiently. As in previous FERC analysis, the 

enhanced incentives for power plant operation are assumed to result in improvement in 

their availabilities, a lowering of their heat rates, and a lowering of their O&M costs. 

Increased availabilities coupled with greater opportunities of importing power from 

neighboring regions in time of need could result in a lowering of reserve margins. In 

addition, lower wheeling charges and greater opportunities for building new 

transmission lines may also occur.

The policy scenarios analyzed here represent these benefits through a variety of 

assumptions about unit and system operation. The following table outlines the Base 

Case, Policy Scenarios, and Sensitivity Cases proposed for this analysis.
31

Table 2.1: Base Case and Policy Scenario Specifications

Scenario

Parameter Base Case Transmission 

Only RTO Policy Demand Response

Sensitivity 

I: Larger 

RTOs

Sensitivity 

II: Smaller 

RTOs

RTO 

Configuration

No RTOs; 

32 region 

structure

4 RTOs and ERCOT 2 RTOs and 

ERCOT

9 RTOs and 

ERCOT

Reduced 

Inter-Regional 

Barriers to 

Trade

Base Case 

assumption

No transmission charges within RTOs; charges converge to $2 per MWh 

between RTOs beginning in 2004

Transmission 

Capability 

Expansion

Base Case 

assumption Increased by 5% from 2004 onward

Capacity 

Sharing

75% of 

energy 

transfer 

capability

100% of electricity transfer capability

Reserve 

Margins

Decline over 

time to 

system -wide 

average of 

15% by 

2020

Decline over time to system -wide average of 13% by 2020

Efficiency 

Improvements Base Case assumption Fossil-fired Units: Heat rate improves by 6% by 2010 and availability increases by 2.5%

Demand 

Response Not analyzed

3.5% 

reduction in 

peak 

beginning in 

2006

Not analyzed

The Sensitivity Cases isolate a key factor in the evaluation of the RTO policy: regional 

RTO configuration. The two Sensitivity Cases vary from the RTO Policy Case only in 

the regional specification of the RTOs. Sensitivity Case I broadens the scope of the 

RTOs to the widest degree possible given current physical transmission constraints, 

while Sensitivity Case II disaggregates the 4 RTOs in the RTO Policy Case into smaller 

organizations, leaving existing ISOs largely untouched. The regional configurations for 

the RTO Policy Case and the Sensitivity Cases are described in Section 2.3.1.

2.3 Modeling RTO Scenarios with IPM®

This section provides an overview of how IPM® was used to model the scenarios 

described above. 

2.3.1 RTO Regional Configuration

For this analysis, the 32 model regions shown in Figure 2.2 below are intended to 

capture commercially significant historical transmission bottlenecks within the US and 

can be considered to be potential building blocks of a power system blanketed end-toend with RTOs.
32

Figure 2.2: IPM® Regions

For the RTO Policy, Transmission Only and Demand Response Cases, four RTOs were 

specified, along with ERCOT, as the basis for this cost-benefit analysis. The subregions within the RTOs have separate load profiles and generating capacity, as in the 

Base Case, and are linked by transmission facilities with limited transfer capability, also 

as in the Base Case. Within the policy scenarios, however, the cost of sending power 

from one sub-region to another and other market and unit operational details will 

change relative to the Base Case, as described below. The RTO regional configuration 

used in the Transmission Only, RTO Policy, and Demand Response Cases is shown in 

the following table and figure.

PACNW

NOCAL

SOCALNV

AZNM

NWPPE

MONTANA

RMA

MAPP

SPPN

SPPW

ERCOT

ENTERGY

ILMO

WUMS

MECS

SOECAR

TVA

COMED

SOCO

LILCO

FRCC

SCEG

DUKE CAPO

VIEP

PJMS

PJMW

PJME

UPSNY

DSNY

NYC

NEPOOL

PACNW

NOCAL

SOCALNV

AZNM

NWPPE

MONTANA

RMA

MAPP

SPPN

SPPW

ERCOT

ENTERGY

ILMO

WUMS

MECS

SOECAR

TVA

COMED

SOCO

LILCO

FRCC

SCEG

DUKE CAPO

VIEP

PJMS

PJMW

PJME

UPSNY

DSNY

NYC

NEPOOL
33

Table 2.2: RTO Regional Specification – Main RTO Policy Cases

RTO IPM® Sub-regions (Map Abbreviations)

West Northern and Southern California (NoCAL and SoCAL), Pacific Northwest 

(PACNW), Montana, NWPP-East (NWPP-E), Rocky Mountain Area 

(RMA), Arizona and New Mexico (AZNM)

Midwest SPP (SPP-N and –W), ECAR (So. ECAR and MECS), MAIN (ILMO, 

COMED, and WUMS), MAPP

ERCOT ERCOT

Southeast SERC (Southern, SCEG, CP&L, Duke, TVA, Entergy), Florida

Northeast NEPOOL, PJM, New York, VIEP

Figure 2.3: RTO Regional Specification – Main RTO Policy Cases

PACNW MONTANA

NWPPE

MAPP

RMA

AZNM

SPPN

SPPW

ERCOT

ENTERGY

ILMO

COMED

WUMS

SOECAR

MECS

FRCC

SOCO

NOCAL

SOCALNV

TVA

SCEG

DUKE

CAPO

VIEP

PJMW

PJMS

PJME

NYC

LILCO

UPSNY

DSNY

NEPOOL
34

Sensitivity Case I, Larger RTOs, aggregates the RTOs shown above into only 2 large 

RTOs and ERCOT.

Table 2.3: RTO Regional Specification – Sensitivity Case I: Larger RTOs

RTO IPM® Sub-regions (Map Abbreviations)

West Northern and Southern California (NoCAL and SoCAL), Pacific Northwest 

(PACNW), Montana, NWPP-East (NWPP-E), Rocky Mountain Area 

(RMA), Arizona and New Mexico (AZNM)

East SPP (SPP-N and –W), ECAR (So. ECAR and MECS), MAIN (ILMO, 

COMED, and WUMS), MAPP, SERC (Southern, SCEG, CP&L, Duke, 

TVA, Entergy), Florida, NEPOOL, PJM, New York, VIEP

ERCOT ERCOT

Figure 2.4: RTO Regional Specification – Sensitivity Case I: Larger RTOs

PACNW MONTANA

NWPPE

MAPP

RMA

AZNM

SPPN

SPPW

ERCOT

ENTERGY

ILMO

COMED

WUMS

SOECAR

MECS

FRCC

SOCO

NOCAL

SOCALNV

TVA

SCEG

DUKE

CAPO

VIEP

PJMW

PJMS

PJME

NYC

LILCO

UPSNY

DSNY

NEPOOL
35

Sensitivity Case II, Smaller RTOs, instead disaggregates the RTO Policy Case RTOs 

into organizations that preserve, roughly, existing ISOs, and expand the Midwest to 

include Entergy.

Table 2.4: RTO Regional Specification – Sensitivity Case I: Smaller RTOs

RTO IPM® Sub-regions (Map Abbreviations)

California Northern and Southern California (NoCAL and SoCAL)

Pacific Northwest Pacific Northwest (PACNW), Montana, NWPP-East (NWPP-E)

Rockies Rocky Mountain Area (RMA), Arizona and New Mexico (AZNM)

Midwest SPP (SPP-N and –W), ECAR (So. ECAR and MECS), MAIN (ILMO, 

COMED, and WUMS), MAPP, Entergy

Southeast SERC (Southern, SCEG, CP&L, Duke, TVA)

FRCC Florida

NEPOOL NEPOOL

PJM and VIEP PJM, VIEP

New York New York

ERCOT ERCOT

Figure 2.5: RTO Regional Specification – Sensitivity Case II: Smaller RTOs

2.3.2 Calibration 

Current market impediments, such as congestion, strategic behavior and market power, 

and pancaking of rates, lead to out-of-merit dispatch resulting in increased costs. IPM®

represents these inefficiencies within the current markets in the Base Case by 

calibrating the model to year 2000 generation by region. Transmission charges were 

therefore adjusted to represent the inefficiencies that the RTO policy purports to 

eliminate. These adjustments are called ‘transmission hurdle rates’ in this report to 

distinguish them from direct costs, such as tariffs.

PACNW MONTANA

NWPPE

MAPP

RMA

AZNM

SPPN

SPPW

ERCOT

ENTERGY

ILMO

COMED

WUMS

SOECAR

MECS

FRCC

SOCO

NOCAL

SOCALNV

TVA

SCEG

DUKE

CAPO

VIEP

PJMW

PJMS

PJME

NYC

LILCO

UPSNY

DSNY

NEPOOL
36

Transmission hurdle rate assumptions (in dollars per megawatt-hour -- $/MWh) for this 

study were developed using IPM® in an iterative process. Hurdle rates were increased 

or decreased between ICF sub-regions a number of times in order to duplicate both the 

generation distribution and generation mix reported in actual year 2000 data for the 

entire US as provided in EIA Forms 714 and 900. Calibration was performed using 

historical data from 2000, including regional demand and hourly load, regional delivered 

fuel prices, hydro and nuclear generation, transmission capability, and foreign imports. 

The final hurdle rates in IPM® yield results matching regional generation levels within 

5% and capture interregional transmission volumes.

Hurdle rates are used in this exercise to represent both actual transmission usage fees 

and market inefficiencies. The inefficiencies represented here include market power, 

open access limitations, non-economic contracts or other barriers that may impede the 

economic flow of power from one region to another. Existing ISOs (California, PJM, 

New York, and New England) are assumed to have no internal hurdle rates.

2.3.3 Base Case Specification

The hurdle rates resulting from the calibration exercise served as the basis for the Base 

Case projection. The Base Case assumes no further FERC policy regarding regional 

transmission structures, i.e. the Order No. 888 status quo. As a result, the hurdle rates 

are assumed to decline gradually at 2.5% per year until leveling off in 2010 and 

remaining constant thereafter to represent modest improvements in the management of 

the grid. Other Base Case assumptions will be provided in the assumptions section.

2.3.4 Policy Scenario Specification

Analyzing the policy scenarios and Sensitivity Cases requires that several adjustments 

be made to the Base Case assumptions. The key adjustments are described below for 

each Scenario. Many of these assumptions are adapted from previous FERC analyses, 

as reflected in the EIS for Order No. 888 and the EA for Order No. 2000.

The Transmission Only Case combines several potential benefits of RTOs into one 

scenario using the following model parameters:

• Reduced Inter-Regional Barriers to Trade: Hurdle rates within the four RTOs 

decline to zero for 2004 and onward. Rates between RTOs converge from the 

hurdle rates used in the Base Case to $2 per MWh by 2004 and remain at that 

level throughout the study horizon.

• Transmission Transfer Capability Expansion: RTOs may lead to better incentives 

for transmission investment and improved regional planning. In IPM®, this 

expansion is represented by increasing the effective transfer capability of 

transmission links among sub-regions within an RTO at no incremental cost by 

5% beginning in 2004. Capabilities between RTOs are not changed from Base 

Case levels.
37

• Capacity Sharing: Regions can share generating capacity across transmission 

links in the IPM® simulation framework, in order to meet reserve margin 

requirements, but there are losses (effective capacity derating) when this occurs 

in the Base Case. Capacity sharing in the RTO Policy Scenario is allowed to 

equal total energy transfer capability beginning in 2004.

• Reserve Margins: Larger RTO regions will be able to pool their reserve resource 

more effectively, leading to reduced reserve margin requirements, particularly 

because larger regions lead to smaller contingency impacts from the loss of 

individual system elements (the larger the region, the smaller each element’s 

share of capacity). As a result, reserve margin requirements in the Policy 

Scenarios decline by 2020 to a system average of 13% from the Base Case 

average level of 15%.

The RTO Policy Case maintains these transmission-related changes. In addition, 

changes are included to represent potential improvements in other aspects of the power 

markets:

• Efficiency Improvements: Previous work on competitive power markets done by 

FERC and others has often assumed that competitive pressure will result in 

generators moving toward the ‘best practice frontier’ in order to maintain 

competitive position. For this scenario, specific generator parameters, including 

unit availability and heat rates, are adjusted to reflect this effect.

The Demand Response Case includes the changes above and adds:

• Demand Response: Improvements in the ability of consumers to react to price 

changes can lead to dramatic improvements in market performance. In IPM®, 

this response is represented by reducing regional peak generation requirements 

by 3.5% beginning in 2004. This methodology is discussed in greater detail in 

the Assumptions section.

In discussing the results of these policy scenarios, greater attention is given to the RTO 

Policy Case, because this case is considered to be the most likely outcome of RTO 

policy by the Commission. The other policy scenarios are intended to capture 

uncertainty in the potential economic outcomes of RTO policy. Even in the Demand 

Response Case, however, assumptions are intended to be reasonable rather than 

optimistic, meaning that the Demand Response Case is not intended as an upper 

bound. Such an upper bound on estimated benefits would require a policy scenario that 

changes several assumptions and would produce substantially greater economic 

benefits than the cases modeled here.
38

2.4 Analytic Assumptions

In order to represent the key interrelationships among the power, fuel and emissions 

markets, IPM® draws upon a detailed database of all of the generating units connected 

to the US power grid. The database that supports IPM® contains information regarding 

unit heat rates, capacities, emission rates and operational constraints. This database, 

combined with IPM®’s capabilities to capture interactions in the converging power, fuel 

and emissions markets, provides a strong analytical tool that offers a unique level of 

detail in a national simulation model. This section describes the key assumptions that 

underlie the Base Case and policy scenarios.

For the purpose of this analysis, assumptions can be divided into two types: (1) 

assumptions that are altered among cases, and (2) assumptions that remain the same 

across the Base Case and policy scenarios. The previous section touched on the first 

category of assumptions. This section provides detailed discussion of those 

assumptions and their role in IPM®. Section 2.4.2 then discusses those assumptions 

that remained the same in all cases.

2.4.1 Assumptions That Change Across Cases

All of the policy scenarios modeled for this cost/benefit assessment include changes to 

the following IPM® assumptions:

1. Transmission charges and transfer capabilities

2. Reserve margins.

The RTO Policy Case added changes to the following classes of assumptions:

3. Unit cost and performance

a. Availability

b. Heat rates

The Demand Response Case adds one more category of assumption change:

4. Price response and distributed generation

Transmission Charges and Capacities

Central to the definition of the RTOs within IPM® are the transmission hurdle rate and 

transfer capability assumptions that define the links between the sub-regions. These 

characterizations are used in IPM® to represent the implementation of an RTO 

structure, and to simulate potential changes to grid operations and resulting economic 

shifts that could be realized under specific RTO policies. 

For this study ICF has aggregated individual transmission lines into transmission paths 

that link the 32 model regions. This approach is consistent with the way NERC 
39

transmission studies group lines. IPM® models each interregional link as one line with a 

maximum flow capability, energy and capability loss, and hurdle rate. The hurdle rates 

are modeled in IPM® as transmission usage charges, or a dollar per MWh charge for 

each MWh sent through a particular path. 

The hurdle rates are used to constrain inter-regional flows in order to reflect actual 

system usage, so these model charges also include implicit barriers to trade as seen in 

historic power flow data. For example, if the model simulated year 2000 market 

conditions but the result over-estimated the amount of power actually transmitted 

between two regions, the hurdle rate was adjusted upward to limit this flow of power to 

observed levels. This process was iterated until the hurdle rates limited all the regional 

power flows to within 5% of actual year 2000 generation patterns.

The actual tariffs, including OASIS posted and other publicly disclosed tariffs, are in 

principal included in the transmission hurdle rates used in this approach. But because 

there is limited information on the actual transmission rates paid for each transaction in 

the year 2000, it is not possible to directly compare the modeled hurdle rates to actual 

transmission charges for that year. Data on public tariffs is maintained and used for 

comparison purposes in other modeling applications, and can be used as the only 

representation of transmission charges. But this would not be an accurate 

representation of the actual rates paid (many or most of which are not disclosed), nor 

would it lead to an accurate model simulation for the year 2000.

Transmission path capability was developed by ICF using public sources. The primary 

sources were the 2000 NERC Summer Assessment and the 2000/2001 Winter 

Assessment. These studies are published by NERC annually and include estimates of 

transfer capability between NERC defined sub-regions. The IPM® regions shown in 

Figure 2.2 above are based on NERC regional definitions. Transfer capability modeled 

is the average of the NERC Summer and Winter Assessments between NERC regions. 

Where available, additional transmission studies have been used to augment the NERC 

data. This is the case specifically the in the Northeast where NE-ISO and NYPOOL 

studies were consulted to determine both intra- and inter-ISO transmission capability. 

Additional sources include the VACAR ECAR MAAC Study Group (VEM) and MAAC 

ECAR NPCC Study Group (MEN) studies and, in some cases, regional coordinating 

councils. In a few instances internal ICF assumptions were used for particular links; 

these are generally derived from load flow modeling and project-specific information.

This method of aggregating transmission links and using static transfer capabilities is an 

important aspect of the analytic framework used in this study. More detailed 

engineering models that can estimate actual power flows across all system elements 

are often used for reliability assessments and other short-run modeling applications. 

The results of such models are not directly comparable when system conditions 

change, and system conditions are constantly changing. As a result, any fixed estimate 

of transmission transfer capability is necessarily subject to important limitations. The 

established practice of using such transfer capability estimates in long-run optimization 

models, while a simplification, is required in order to allow other aspects of the system 
40

to be fully represented. This is why sensitivity analysis of important assumptions is 

often conducted, to assess the impact of uncertainty on analytic results.

The hurdle rates resulting form the calibration exercise were used as a starting point for 

the Base Case and policy scenarios to insure that all cases captured those barriers to 

trade. In the Base Case, the rates were assumed to decline at 2.5% per year until 

leveling off in 2010 to reflect moderate improvements to the management of the 

transmission grid without requirements beyond existing policies. 

Adjustments were made to Base Case assumptions in the policy scenarios to simulate 

changes resulting from the proposed rule itself and from improvements in the 

transmission system brought about by better management of the grid. Hurdle rates 

within RTOs declined to zero for 2004 and onward. Rates between RTOs converged 

from the hurdle rates used in the Base Case to $2 per MWh by 2004 and remained at 

that level throughout the time horizon of the study. The policy scenarios also assumed 

expansion of transmission capability beyond Base Case levels. The effective transfer 

capability of transmission links among sub-regions within an RTO increased by 5% 

beginning in 2004. Capabilities between RTOs were not changed from Base Case 

levels.

Reserve Margins

IPM® models reserve margin requirements in order to capture ongoing reliability 

requirements. These reserve margins require the model to build economic capacity 

additions to meet peak demand plus a specified percentage in each model region. 

Historically, reserve margins have been declining as more inter-regional power transfers 

and increasing real-time response options have reduced the need for dedicated reserve 

capacity. Each model region has a specific trajectory of projected reserve margin 

requirements. Current reserve margin requirements are based on a number of sources, 

primarily NERC projections and regional reliability council estimates.

Reserve margins in the Base Case reach a system average of 15% by 2020. Except in 

the Northeast and Florida, reserve margins remain at a constant 15% over time. In the 

Northeast (PJM, New York and NEPOOL), reserve margins begin closer to 20% in 2003 

before converging with the rest of the system at 15% by 2020. Florida maintains a 20% 

mandatory reserve margin through 2010, due to existing state reliability requirements, 

and then declines slightly in the long-term.

In the policy scenarios, regional reserve margins are adjusted downward to achieve a 

system average of 13% by 2020. This assumption is intended to capture the pooling of 

generation resources likely to occur within a large RTO region. With a larger base of 

assets available to meet generation needs, the loss of individual system elements will 

have a smaller impact on the region’s ability to meet demand, thereby requiring a 

smaller reserve margin.
41

Unit Cost and Performance

The RTO Policy Case is based on the premise that open access transmission and clear 

market rules will increase incentives for generators to improve efficiency and unit 

performance. As markets widen and competition increases, less efficient, higher cost 

generators will face competitive pressure to improve, or be forced from the market. 

Several potential effects of such incentives are modeled, consistent with the methods 

employed in other national studies. Further analysis on unit performance and incentives 

could refine the assumptions used here. 

The two main areas of improvement expected are in unit availability and efficiency. 

Increased competition is likely to encourage generators to reduce maintenance outage 

time, and at the same time improve maintenance procedures to decrease forced 

outages. For the purpose of this analysis, this improvement is assumed to be 2.5% on 

an annual basis for fossil units between 2004 and 2010. Efficiency gains were also 

modeled by decreasing the full load heat rate of fossil-fired units by 1% per year 

between 2004 and 2010. Both of these assumptions are held constant after 2010.

These assumptions were based directly on previous analyses of national electric sector 

restructuring policy conducted by DOE and the FERC. New research on the actual 

performance of generating plants in competitive markets was not available for this 

study; improvements in the knowledge base on this critical topic would be one important 

area for further research. The intent of this study is to indicate the importance of 

generator efficiency to the overall economic impacts of RTO policy using existing 

analysis that has been subject to public review and scrutiny, rather than establishing a 

specific estimate of improvements based on statistical analysis or other comparative 

methods.

An additional area of potential generator improvement, fixed operating and maintenance 

(fixed O&M), has been estimated in previous studies of competition in the electric power 

sector. This type of cost does not directly affect operating decisions in the model used 

here, since changes in production level at a unit do not change such fixed costs. 

However, an estimate of potential fixed O&M improvements was carried out using 

assumptions similar to those used in other studies. Because this was not part of the 

modeling it is discussed along with other non-modeled system elements in Section 3.

Demand Response

The demand estimates in the Base Case and policy scenarios already incorporate a 

limited degree of demand response. NERC estimates for load, the basis for the load 

assumptions in this analysis as described later in this section, include load 

management, or direct load control and interruptible demand. An analysis of the data 

suggests that these account for about 4% of peak demand nationally.

What is not included in these estimates, however, is price responsive load, or the load 

that is responsive to high peak prices. It is assumed that customers will lower their 
42

demand in the face of higher prices (i.e., demand elasticity). Customers can be 

exposed to higher peak prices through either time of use rates or real-time pricing 

programs. It is likely that these programs will be more prevalent in future years. The 

additional demand response included in the Demand Response Case reflects 

implementation of these pricing programs.

The introduction of time-varying demand (either time of use rates or real-time pricing) 

will introduce variable prices to customers at different points during the year and day. In 

particular, if customers are exposed during peak periods to prices that reflect on-peak 

wholesale prices, based on standard economic theory, it is expected that they will 

reduce or shift their load to lower price periods. 

The staff paper on demand responsiveness prepared by Commission staff, as 

mentioned in Section 1, discusses the link between market design, infrastructure 

technology, and demand response. The paper also elaborates on the benefits that 

demand response can provide to consumers through lessened volatility and mitigation 

of potential market power abuse. This is consistent with other work in this area as well 

as the approach employed for this study.

In order to estimate this aspect of demand response, simple measures of elasticity were 

applied to a set of regional prices disaggregated by load segment. For the final demand 

response assumption used here, a short run price elasticity of –0.1 was applied to half 

the customer base in each region, yielding a conservative estimate of 3.5% as a peak 

reduction under assumed more transparent pricing conditions. This estimate was 

applied to all regions in the relevant scenarios. Because of the complexity, uncertainty 

and importance of demand response in electric power markets, this assumption was 

used as a sensitivity case and is meant to be illustrative, although it is reasonable and 

consistent with recent analytic work in this area.

2.4.2 Invariant Assumptions

Several types of assumptions remain the same across the Base Case and policy 

scenarios. This section provides an overview of those assumptions.

Regional Structure

The national IPM® framework captures key interrelationships among wholesale power, 

fuel and environmental markets. To capture regional variations in wholesale power 

prices, IPM® divides the US electric sys tem into model regions with a representation of 

the electric transmission system connecting neighboring regions. The regional 

representation within IPM® is flexible and can be structured to offer a level of resolution 

that captures transmission bottlenecks located throughout the US electric power grid. 

For this analysis, the US is divided into 32 regions, each having a representation of the 

transmission interconnections that link one region with the next.
43

While the transmission charges among regions change from the Base Case to the 

policy scenarios to reflect the formation of the RTOs, the sub-regions maintain their 

Base Case demand growth and load shapes, new technology cost and performance 

assumptions, fuel market characterizations, and environmental regulatory requirements.

Load Growth and Load Shape

Forecast electricity demand growth represents a key assumption in this analysis. Given 

regional variations in demand growth, an individual demand growth forecast for each of 

the IPM® modeling regions is provided. The demand forecast for each model region is 

assumed to climb at about the rate of growth in GDP through 2005. Beyond 2005, 

growth in electric demand declines with the introduction of real time pricing for retail 

customers. 

The table below details starting points and average growth rates for net internal demand 

and net energy for load for the 32 model regions included in this study. Net energy for 

load is the total electrical energy requirements of an electric system as provided by the 

“NERC Electricity Supply and Demand (ES&D)” for year 2000 and forecast. Net internal 

demand is modeled as internal demand less direct control load management and 

interruptible demand, again provided by NERC ES&D for year 2000 and forecast. 
44

Table 2.5: Load Growth Assumptions

Region

2000 Net 

Energy for 

Load (GWh)

Average 

Annual 

Growth to 

2020

2000 Net 

Internal 

Demand (MW)

Average 

Annual 

Growth to 

2020

Arizona-New Mexico 87,895 3.8% 16,805 3.7%

CP&L 58,321 3.0% 10,424 3.1%

COMED 90,271 2.1% 19,295 2.2%

Downstate NY 34,632 1.4% 6,439 1.8%

Duke 101,435 3.0% 18,132 3.1%

Entergy 159,146 2.0% 29,262 2.1%

ERCOT 286,318 2.2% 54,451 2.7%

Florida 196,562 3.5% 34,476 3.9%

ILMO 91,737 2.1% 16,583 2.2%

LILCO 18,610 1.4% 4,200 1.9%

MAPP 165,028 2.4% 30,450 2.3%

MECS 94,986 2.3% 16,700 2.6%

Montana 12,462 1.8% 2,072 1.9%

NEPOOL 124,888 1.7% 21,919 2.1%

Northern California 113,379 2.2% 21,332 2.4%

NWPP-East 36,731 1.8% 5,284 1.9%

New York City 47,819 1.4% 8,891 1.9%

Pacific Northwest 

(PACNW) 191,898 1.8% 27,617 1.9%

PJM-E 133,522 1.8% 24,414 2.4%

PJM-S 62,955 2.7% 11,511 2.4%

PJM-W 65,845 1.7% 12,040 2.4%

Rockies (RMA) 51,481 2.2% 8,470 2.2%

SCEG 52,071 3.0% 9,309 3.1%

Southern California 170,070 2.2% 31,998 2.4%

Southern 210,023 3.8% 41,621 3.3%

Southern ECAR 450,973 2.3% 72,172 2.6%

SPP-North 58,241 2.8% 12,683 2.7%

SPP-West 111,213 2.8% 22,611 2.7%

TVA 160,549 1.7% 27,128 2.0%

Upstate NY 55,578 1.4% 8,608 1.7%

VIEP 83,512 3.0% 14,926 3.1%

WUMS 60,916 2.1% 10,268 2.2%

System 3,639,067 2.4% 652,091 2.6%

Fuel Market Assumptions

Effectively integrating the fuel markets, IPM® also simulates coal production, 

transportation, and consumption. For this purpose, the model has supply curves for 40 

coal producing regions and contains over 10 coal types distinguished by rank and sulfur 

content. Each power plant is assigned to one of over 40 coal demand regions 

characterized by location and mode of delivery including rail, barge, and truck. 

Transportation costs are specified for each supply and demand region link.

Natural gas prices are determined within the model using a similar supply curve and 

transportation network representation. The natural gas price forecast and the related 
45

curves are derived in part from results from ICF’s North American Natural Gas Analysis 

System (NANGAS). The NANGAS model allows assessment of gas resources and 

markets from reservoir to burner-tip, working from a database of more than 17,000 US 

and Canadian reservoirs. The Base Case gas price trajectory is provided in the table 

below.

Table 2.6: Base Case Henry Hub Gas Price Trajectory

Year 2000$ per Million Btu Nominal $ per Million Btu

2003 3.20 3.45

2004 3.12 3.44

2005 2.78 3.14

2010 2.85 3.65

2015 2.74 3.96

2020 2.63 4.31

Environmental Regulation and Compliance

The Base Case and policy scenarios assume existing, final regulations for SO2 and NOX

including implementation of future requirements in existing final regulations:

• Phase II of the Title IV Clean Air Act (CAA) SO2 emissions trading program 

adjusted for the recent settlement of legal actions.

• NOX SIP Call program that caps summer NOX emissions in 19 states spanning 

the Northeast, Midwest and Southeast. The NOX SIP Call Policy takes effect in 

May 2003 in SIP Call states currently participating in the Ozone Transport 

Region (OTR) trading program. The remaining SIP Call states enact the policy in 

May 2004. 

No potential or speculative future air emissions regulatory changes are assumed in the 

Base Case or policy scenarios.

The integration of emissions markets in IPM® is achieved with a detailed representation 

of air regulations that are met through compliance decisions that reduce overall 

emissions for a given pollutant. IPM® endogenously determines the optimal compliance 

for meeting environmental air regulations for every plant in the US. The compliance 

options considered in IPM® encompass the full range of choices available: 

• Pollution control technologies such as flue gas desulfurization (scrubber), 

selective catalytic reduction (SCR), selective non-catalytic reduction (SNCR), and 

gas-reburning,

• Allowance purchases,

• Repowering,

• Retirement,

• Dispatch adjustments, and

• Fuel switching.
46

Capacity Retirements

Within the IPM® modeling framework, fossil power plant retirements can be forced at a 

specific age and/or retirements can be determined endogenously based upon the 

relative economics of a unit. Because plant age has not been a reliable indicator of 

plant retirements in the past, fossil plant retirements are determined endogenously 

within the model. Economic retirements occur whenever the going forward fixed costs 

of a unit cannot be recovered from wholesale power price sales.

Many nuclear units located throughout the US are approaching the end of their existing 

operating licenses issued by the Nuclear Regulatory Commission (NRC). For the 

purpose of this analysis, nuclear units are assumed to not be decommissioned at the 

end of their 40-year operating license. Rather, it is assumed that owners of nuclear 

assets will move forward with relicensing efforts through the NRC. 

Other Invariant Assumptions

Other classes of assumptions used to model the electric power sector in IPM® also 

remained unchanged across the Base Case and policy scenarios. These assumptions 

include:

• Financial assumptions

• Cost and performance of capacity additions

2.5 Treatment of Non-Modeled System Elements

In considering the role of simulation modeling in an analysis of this type, it is useful to 

consider the structure of general costs and revenues in the electric industry, and to 

identify what portion of the electric system is typically modeled using IPM®. Because 

the modeling framework only estimates costs that are relevant for system operation and 

investment decisions (as detailed below), a number of financial flows in the industry are 

not directly represented. Some of these costs are relevant to RTO policy assessment 

while others are not. This section lays out the conceptual framework for considering 

these issues, and the treatment of non-modeled, relevant system costs.

In 1997, the size of the electric industry amounted to about $215 billion. This includes 

revenues earned by investor- as well as publicly-owned utilities. By 2000, the industry 

grew by approximately 6 percent to $228 billion.10 Table 2.7 shows the distribution of 

industry revenues between different types of utilities.

 

10 Electric Power Annual 2000 Volume I, US Energy Information Administration, Table A-21 “Retail Sales 

of Electricity, Revenue, and Average Revenue per Kilowatt-hour by US Electric Utilities to Ultimate 

Consumers by Census Division, and State, 2000 and 1999.”
47

Table 2.7: Revenue from Sales to Ultimate Users by Utility Type, 1997 

(Million 1997$)

Utility Type Total Revenue

Investor-Owned 168,701

Municipal 27,744

Cooperative 17,583

Federal 1,035

Total 215,063

 Source: Supporting Analysis for the CECA, DOE/PO-0059,

 May 1999, Table 2. 

Complete data regarding the costs incurred by all types of utilities is not available. 

However, investor-owned utilities comprise the largest part of the electric industry. 

Thus, to give a sense of costs incurred by the industry, Table 2.8 lists the primary costs 

incurred by investor-owned utilities in 1995. Public entities, independent power 

producers and others would not be expected to have a similar cost breakdown; some 

public entities operate mainly transmission and distribution systems, while many 

independent power producers own generation resources exclusively.

The three cost categories directly represented in the IPM® simulation framework include 

future capital expenditures on new power plants and pollution controls, operation and 

maintenance costs, and the cost of fuel inputs. Figure 1 shows that these three 

categories comprise 83% of the production costs incurred by investor-owned utilities. 

Due to the forward-looking nature of the model, however, this leaves approximately 

17% of production costs unaccounted for. Although it captures the bulk of the industry 

with production costs, IPM® does not directly calculate any of the costs related to the 

transmission and distribution of power. 

Table 2.8: Investor-Owned Utility Costs, 1995

 (Million 1995$)

Cost Category Amount

PRODUCTION 107,191

Purchased Power 12,131

Fuel 28,991

Non-fuel O&M 17,184

Capital Related 42,637

A&G Allocation 6,245

TRANSMISSION 11,620

DISTRIBUTION 43,470
48

Figure 2.6: Production Cost Categories

Source, Table 2 and Figure 1: Supporting Analysis for the CECA, DOE/PO-0059, May 1999, Table 4.

Table 2.9 shows the system capital costs from a typical IPM® run. Over time, the capital 

costs estimated by IPM® approach the level of investor-owned capital costs as listed in 

Table 2 above. However, IPM® does not take into account any sunk capital costs that 

may have been expended prior to the first IPM® run-year. This is because such sunk 

costs are not relevant for system operation and dispatch (this follows from the 

microeconomic theory of the firm, as production decisions are based on marginal costs, 

not average costs that can include sunk capital). Capital costs shown in Table 3 are 

strictly costs incurred to build new power plants or install pollution controls, and are thus 

marginal in the sense that they can be affected by production decisions. In the long 

term, current sunk capital is fully depreciated and all system capital is represented in the 

model.

Table 2.9: Example Capital Cost Output from IPM®

(Million $)

2005 2008 2012 2017 2022 2027

4,126 7,668 13,245 22,101 30,479 40,006

2.5.1 Treatment of Cost Categories Not Represented in Modeling

Sunk capital costs are not affected by RTO policy. The regulatory treatment of these 

sunk costs, some of which can become so-called ‘stranded costs’, is an important policy 

issue, but not directly relevant to this economic analysis. So this major category of

industry revenue is not directly considered in this analysis.

Other major cost categories do raise analytic issues in the context of RTO policy. 

Transmission and distribution, taken together, are important elements of the electric 

power system that may be affected on a going forward basis by the Commission’s 

actions with regard to RTOs. In particular, transmission system operating costs and 

potential expansion are directly affected by the ownership structure and associated 

incentives created by RTOs. 

Nonfuel O&M

16%

Fuel

27%

Purchased 

Power

11%

A&G 

Allocation

6%

Capital 

related

40%
49

Similarly, administrative and general (A&G) costs may be affected by RTO policy. 

Consolidation of system operators has both costs and potential savings, depending on 

the implementation of RTO policy, and these potential costs and benefits need to be 

estimated and taken into account. This is the major area where direct costs of RTO 

establishment are estimated. 

In order to estimate startup costs for RTOs, this study relies for the most part on existing 

studies of the costs of system operations, which typically use static comparative 

analysis, to estimate a range of possible economic outcomes for this cost category. 

Specifically, a number of cost indicators are developed that relate existing system costs 

to the size of the system in terms of capacity, energy, number of customers, etc. These 

cost indicators are then used to extrapolate a range of potential RTO startup costs for a 

nationwide RTO-based system.

 2.5.2 Short-Term Market Events

The IPM® simulation framework is designed for relatively long run analysis. Because of 

the large set of variables required for detailed national simulation, including integrated 

treatment of fuel and environmental market drivers, simplification of temporal detail is 

traded off against other relevant system attributes. As a result, the IPM® framework 

treats power markets as spot pools that clear on a marginal cost basis within a set of 

defined demand segments. 

This treatment of the time dimension is not intended to represent very short-term market 

events such as temporary price spikes. If longer-term underlying market conditions are 

out of equilibrium (such as during a chronic capacity shortage or glut), these market 

conditions can be simulated. However, severe price volatility as a result of poor 

transmission management will generally be a transient effect that will not be forecast 

using a model like IPM®.

Although there is no direct accounting for such short-term effects in the analytic 

framework used here, the economic issues associated with such effects are discussed 

in Section 3 in order to place them into perspective and suggest possible analytic 

approaches for related work.

2.5.3 Native Load and Contracts

The current wholesale power market is made up of a diverse set of transactions. Shortterm spot purchases, bilateral contracts of varying terms and durations, and native load 

generation commitments all coexist. Furthermore, there is great regional variation in the 

makeup of wholesale market transactions. 

In the long run these various transactions will tend to lead to similar market results (all 

of these transaction types, including native load commitments, can be viewed as 

contracts with values based on opportunity costs, which in turn are established by a 

real-time marginal transaction). However, the long run in this context can be as long as 

is required for the longest duration contracts to be renewed and possibly longer if 
50

multiple contract renewals are needed to allow for information revelation and adjustment 

of prices.

The IPM®framework is normally run as a market with full spot or pool price treatment, 

dispatching all supply resources in a common clearing mechanism. This approach 

treats all transactions as spot or the equivalent of spot transactions. To the degree that 

various transaction types approach the marginal cost solution (keeping in mind that a 

good deal of the short run volatility is already eliminated in this approach), such a 

method gives reliable estimates for actual market conditions. 
51

3 Results

Based on the analytic approach described in the preceding section, computer simulation 

modeling and other related analyses were carried out. The results of the analysis are 

presented in this section, beginning with Base Case results. The main policy scenarios 

and the various Sensitivity Cases are also presented in this section. Integration of 

computer model results with other quantitative analysis is presented, followed by overall 

conclusions from this economic cost/benefit assessment.

3.1 Summary Results: Base Case

This section provides national and regional level summary results for the Base Case, 

including capacity and generation projections. Where applicable, the summary data 

provided includes a comparison to the Energy Information Administration’s Annual 

Energy Outlook 2002 (AEO 2002) base case forecast. This comparison is provided 

because the AEO forecasts are often useful as a starting point for assessing other longrun forecasts of the energy sector. 

3.1.1 Base Case Capacity and Generation Projections

This section presents trends in generating capacity, including economic additions, 

retirements and modifications, as well as generation levels by plant type for the Base 

Case. Tables 3.1 and 3.2 contain IPM®and AEO 2002 projections for 2005, 2010, 2015 

and 2020. Tables 3.3 and 3.4 contain regional IPM®projections from the Base Case for 

the same years. Because the Base Case does not include 2005 as a run year, 2005 

IPM®projections reflect an average of 2004 and 2006. The reported years were 

selected because they provide a reasonable representation of the study period and 

allow for a comparative assessment of the IPM®and AEO 2002 national forecasts.

The Base Case reflects the future of the electric industry without any change from 

current policies regarding RTOs and other relevant regulatory policies in the electric 

power sector (the current ‘status quo’ or no-action case). The major findings in this 

case as they relate to installed capacity and dispatch trends are summarized below.

Base Case: National Results

Table 3.1 lists national generating capacity forecasts from the Base Case and from AEO 

2002. Base Case total generating capacity increases by 352 GW (38 percent) from 

2005 to 2020, whereas AEO 2002 projections show an increase of 253 GW (31 percent) 

over the same period. Both the total amount of capacity and growth in capacity is 

greater in the Base Case relative to the AEO 2002 projection, reflecting higher electric 

demand growth rates over the study period. The Base Case includes an assumed 

annual average demand growth rate of 2.3 percent, while the AEO 2002 reference case 

assumes average annual demand will grow at 1.8 percent.
52

Regardless of the absolute amount of capacity forecasted, both projections indicate that 

new capacity additions will rely heavily upon gas-fired combined cycles and combustion 

turbines (included in the oil/gas classification) to meet growing demand for electric 

power. Nearly 100 percent of the new capacity in the Base Case comes from either 

new combined cycles or combustion turbines. In the AEO 2002 forecast, 90% of new 

capacity additions are either combined cycles or combustion turbines, with the 

remainder largely coming from new coal and renewable plants late in the forecast 

period. The Base Case forecast reflects the expectation that costs to build and operate 

new gas-fired facilities are likely to be lower relative to new coal-fired plants through 

2020.

Table 3.1: National Generating Capacity by Plant Type: Base Case and AEO 2002

(GW)

200512010 2015 2020

Plant Type Base 

Case

AEO 

20022

Base 

Case

AEO 

2002

Base 

Case

AEO 

2002

Base 

Case

AEO 

2002

Coal 308 305 308 306 308 313 308 329

Oil/Gas 417 292 514 385 632 446 770 505

Nuclear 96 98 96 94 96 89 96 88

Renewable/Other3117 115 117 122 117 130 117 140

Total 938 809 1,034 907 1,153 979 1,291 1,062

1

2005 projections for the Base Case are represented as the average of 2004 and 2006.

2

Source: EIA, Annual Energy Outlook 2002, DOE/EIA-0383(2002) (Washington DC, December 2001).

3

Includes conventional hydroelectric, geothermal, wood, wood waste, municipal solid waste, landfill gas, 

other biomass, solar, wind, distributed generation and pumped storage.

Table 3.2 presents national generation forecasts by plant type from the Base Case and 

from AEO 2002. Consistent with new capacity additions, the most significant growth in 

generation occurs at natural gas-fired plants, which increase generation by 269 percent 

from 2005 to 2020 in the Base Case and by 225 percent in the AEO 2002 forecast. As 

with the addition of new capacity, the larger growth in electric generation in the Base 

Case relative to the AEO 2002 forecast reflects higher demand growth rates. 

Increased gas-fired generation is accompanied by higher levels of coal generation, 

albeit to a much lesser extent. From 2005 to 2020, Base Case coal-fired generation 

increases by 4.2 percent, while the AEO 2002 projection shows coal generation 

increasing by 16.2 percent over the same period. Much of the boost in coal generation 

that occurs in the AEO 2002 forecast occurs late in the analysis, with the addition of 

new coal-fired generation as described above. The Base Case projection also shows 

growing coal-fired generation, in this case reflecting increased utilization at existing 

units rather than coal-fired capacity additions. In the Base Case, average capacity 

factors for coal units increase from just over 80 percent in 2005 to nearly 84 percent in 

2020.

As with coal-fired generation, average capacity factors for oil/gas plants also increase 

over the study period, rising from 26 percent in 2005 to over 37 percent in 2020 under 

the Base Case. However, this is largely a reflection of a growing proportion of 

combined cycle units within the oil/gas classification, which includes combined cycles, 
53

oil-gas steam and simple cycle combustion turbines. The average Base Case capacity 

factor for each of these plant types is 50 percent, 11 percent and 8 percent respectively. 

The higher capacity factor for combined cycle units is an indicator of their intermediateto-baseload position in the dispatch order.

Table 3.2: National Generation Projections by Plant Type: Base Case and AEO 

2002

 (TWh)

200512010 2015 2020

Plant Type Base 

Case

AEO 

20022

Base 

Case

AEO 

2002

Base 

Case

AEO 

2002

Base 

Case

AEO 

2002

Coal 2,173 2,086 2,227 2,215 2,240 2,292 2,259 2,423

Oil/Gas 977 646 1,440 921 1,985 1,235 2,581 1,452

Nuclear Power 671 759 682 737 682 707 693 702

Renewable/Other3400 374 399 390 397 400 396 406

Total 4,221 3,865 4,749 4,263 5,303 4,634 5,929 4,983

1

2005 projections for the Base Case are represented as the average of 2004 and 2006.

2

Source: EIA, Annual Energy Outlook 2002, DOE/EIA-0383(2002) (Washington DC, December 2001).

3

Includes conventional hydroelectric, geothermal, wood, wood waste, municipal solid waste, landfill gas, 

other biomass, solar, wind, distributed generation and pumped storage.

Even with the increased utilization of existing coal units, natural gas becomes the 

dominant fuel source by the end of the study time horizon. Under the Base Case, 

growing demand pushes gas-fired generation above coal-fired generation for the first 

time in 2020. Over the Base Case study period the coal-fired share of total generation 

falls from just over 51 percent in 2005 to 38 percent in 2020. By 2020, gas-fired 

generation is less than 48 percent of national electric generation. The AEO 2002 

forecast indicates a less significant role for gas-fired generation relative to the Base 

Case, reflecting lower demand levels and the infiltration of new coal fired capacity late in 

the study period.

Base Case: Regional Results

Table 3.3 displays regional electric generating capacity from the Base Case over the 

study time horizon. National capacity additions increase at an average annual rate of 

just over 2.5 percent from 2005 through 2020; however, capacity growth rates vary 

considerably by region. For example, the average annual growth in new capacity is 

approximately 1.4 percent for NPCC and exceeds 4.1 percent for FRCC. Regional 

variation in capacity growth reflects regional variability in demand growth and 

transmission constraints assumed in the Base Case, which assumes no reorganization 

of regional transmission authorities.
54

Table 3.3: Generating Capacity by Region: Base Case

 (GW)

NERC Region 200512010 2015 2020

ECAR 126 140 155 172

ERCOT 80 80 93 108

FRCC 54 65 74 88

MAAC 71 77 84 92

MAIN 65 67 74 82

MAPP 41 47 52 57

NPCC 74 79 83 90

SERC 217 242 274 311

SPP 47 55 62 69

WSCC 165 181 201 223

Total 938 1,034 1,153 1,291

1

2005 projections for the Base Case are represented as the average of 2004 and 2006.

IPM® regional electric generation levels are shown in Table 3.4 for the Base Case. As 

with capacity growth, generation levels exhibit considerable variation among regions. 

Depending upon the specific region, growing generation levels vary in relation to growth 

in sales, and do not necessarily reflect a direct relationship to changes in demand. The 

growth in sales incorporates interregional electricity transmission charges and 

transmission limitations among neighboring regions. As long as transmission capability 

is available, regions with lower-cost power export energy to higher-cost regions, while 

considering any transmission charges (whether actual tariffs or hurdle rates 

incorporating implicit barriers to trade)under the current transmission structure. 

Some regions exhibit higher growth in generation than in capacity, signifying higher 

utilization of existing plants. Other regions (ECAR, MAAC and SPP) add new capacity 

at a higher rate than increases in generation, signifying the need to meet regional 

reliability requirements. A large portion of increased generation originates from the 

addition of new gas-fired combined cycle capacity, even in regions that rely on 

increased utilization of existing fossil units to meet growing demand. The addition of 

new simple cycle combustion turbine units serve peak load in all regions.

Table 3.4: Generation by Region: Base Case

 (TWh)

NERC Region 200512010 2015 2020

ECAR 652 702 771 868

ERCOT 305 343 388 439

FRCC 239 286 334 391

MAAC 297 322 349 369

MAIN 286 326 348 370

MAPP 192 217 240 278

NPCC 295 328 353 382

SERC 994 1,143 1,308 1,476

SPP 210 238 266 295

WSCC 753 843 946 1,061

Total 4221 4,749 5,303 5,929

1

2005 projections for the Base Case are represented as the average of 2004 and 2006.
55

3.1.2 Base Case Energy Prices and Production Costs

Base Case production costs are shown below. These production costs are those that 

are relevant for operating and investment decisions, so sunk capital and transmission 

and distribution costs are not reflected in the IPM®production cost calculation. One 

consequence of this method of estimating production costs is that in all IPM®simulation 

runs, capital costs increase over time as generating units are added to meet growing 

demand. The Base Case production costs shown below follow this pattern.

Table 3.5: Base Case: System Level Annualized Production Costs 

(Million 2000$)

2004 2006 2010 2015 2020

Fixed Costs 27,081 27,438 28,309 29,827 31,788

Variable Costs 5,369 5,714 6,204 6,831 7,554

Fuel Costs 53,574 54,067 61,878 70,800 78,551

Capital Costs 3,470 6,943 13,098 21,917 31,865

Total System Costs 89,493 94,161 109,489 129,374 149,758

While production costs are reported at the system-wide level for consistency purposes, 

more regional detail is presented for energy prices. These prices are annual average 

firm electricity prices. They aggregate a set of segmental marginal energy prices, and a 

set of capacity prices that reflect the marginal cost of meeting peak demand. Thus 

these prices represent the per-MWh cost of purchasing firm (non-interruptible) 

electricity. In general these firm electricity prices are dominated by the energy price as 

opposed to the capacity price. The prices in Table 3.6 are aggregated by the RTO 

specification used in the policy scenarios for comparison purposes.
56

Table 3.6: Base Case: Regional Firm Electricity Prices 

(2000$/MWh)

RTO Sub-Region 2004 2006 2010 2015 2020

West AZ-NM 39.3 36.0 35.0 32.2 28.5

West RMA 39.2 37.0 35.4 32.9 29.0

West Montana 34.2 31.6 31.4 31.5 28.3

West NWPP-East 33.7 31.4 30.2 30.3 27.2

West Pacific Northwest 38.8 35.9 34.5 32.9 29.1

West Northern CA 43.4 40.0 36.4 34.5 30.5

West Southern CA - NV 43.2 39.7 36.1 34.3 30.3

West Average 40.6 37.4 35.2 33.3 29.5

ERCOT 26.1 24.7 32.7 31.5 29.2

Midwest COMED 30.0 29.5 32.6 32.5 31.4

Midwest ILMO 27.9 27.2 30.4 32.2 30.9

Midwest MAPP 33.8 32.3 32.5 32.4 29.3

Midwest MECS 33.1 32.9 36.0 35.0 32.6

Midwest So. ECAR 32.3 31.8 33.6 33.5 32.2

Midwest SPP-North 30.4 30.7 32.5 31.4 29.2

Midwest SPP-West 38.2 35.4 34.1 32.3 29.3

Midwest WUMS 34.0 32.2 32.3 31.9 30.3

Midwest Average 32.6 31.7 33.2 33.0 31.1

Southeast Entergy 26.5 24.5 27.0 31.2 29.3

Southeast CP&L 36.3 34.3 34.2 32.8 32.5

Southeast DUKE 34.8 34.2 34.1 32.7 32.5

Southeast SCEG 37.4 35.6 34.9 33.3 33.0

Southeast Southern 35.0 34.2 34.4 32.7 32.5

Southeast TVA 32.3 31.6 33.7 32.5 30.2

Southeast FRCC 41.1 38.3 37.1 35.2 33.2

Southeast Average 34.6 33.2 33.8 33.1 31.9

Northeast Downstate NY 40.8 38.9 37.6 36.2 35.7

Northeast LILCO 49.1 41.6 40.1 38.7 38.5

Northeast New York City 43.5 41.9 40.6 39.1 38.9

Northeast Upstate NY 33.1 32.9 34.3 33.4 32.9

Northeast NEPOOL 30.2 36.9 38.0 36.5 35.4

Northeast PJM-East 37.3 35.9 35.9 34.8 34.3

Northeast PJM-South 35.1 34.6 35.1 34.5 34.3

Northeast PJM-West 32.7 32.0 33.2 32.6 32.0

Northeast VIEP 35.6 35.0 34.7 33.1 32.9

Northeast Average 35.7 36.0 36.2 35.0 34.5
57

Figure 3.1: Base Case 2010 Firm Power Prices

 (2000$/MWh)
58

Regional variations in firm electricity prices are greatest in the initial run year, reflecting 

differences in installed generating base and firmly planned plant builds. Regional price 

variations diminish over time as the long run marginal cost of electricity is driven by 

natural gas plants at the margin in all regions. Some of these plants are combinedcycle and some are simple cycle turbines. The mix of combined cycle to simple cycle 

depends on each region’s need for energy as opposed to reserve margin or backup 

capability. The relative economics of the two types of natural gas-fired power plants 

turn mainly on the expected capacity factor, since the higher capital cost of a combined 

cycle plant can be offset by its higher operating efficiency if it operates in enough hours 

in the year.

3.2 RTO Policy Case Results

As discussed in Section 2, the RTO Policy Case is designed to represent the primary 

scenario representing potential impacts of RTO policy. It incorporates both 

transmission grid improvements and a set of market improvements that could result 

from heightened performance incentives caused by increased wholesale competition.

The major impact of RTO policy as implemented in the IPM®framework is to allow 

increased inter-regional trading of energy and capacity. As a result, the regional 

distribution of generation and capacity builds changes. Regions with high barriers to 

trade generally require larger amounts of reserve margin capacity, for example. If the 

transmission grid allows greater trade, the need for some capacity may be deferred or 

eliminated, leading to cost savings.

3.2.1 RTO Policy Case: Changes in Inter-Regional Trade

Because of the importance of the inter-regional trade flows in explaining the results of 

this analysis, a set of maps is presented below that document the exports and imports 

between all IPM®regions. The maps are presented by major US region for clarity. 

Each mapped region has an arrow pointing to any interconnected region, with the flows 

in each direction shown numerically. The two numbers are the Base Case and RTO 

Policy Case flows, respectively.

Lowering of hurdle rates leads to major shifts in power flows in both the Eastern and 

Western Interconnections. One of the ways this study differs from most others recently 

addressing RTO issues is geographic scope; studies of the Northeast that do not 

consider changes to Southeastern power markets, for example, may miss important 

dynamics that can drive the ultimate outcome of regulatory changes. The results of the 

RTO Policy Case demonstrate this, as the opening of higher-price regions in the 

Southeast, particularly Florida but also Entergy, attracts exports from neighboring 

regions. This leads to a cascading effect in which the Midwest reduces flows to the 

Northeast and sends them to the Southeast instead. As a result, Northeast regions 

such as PJM must meet more of their own energy and reserve margin requirements. 
59

In the maps presented here, this overall effect is most evident in the Southeast regional 

map showing the large increase of power transfers into Florida and to a lesser extent 

Entergy. Note that some of the power sent into Entergy is actually wheeled through as 

increased transfers into Southern, part of the dominant influence of the Florida export 

market in a more liberalized transmission grid.

As a result of this increase in transfers toward Florida, both SoECAR and CP&L reduce 

their Base Case power transfers into the Northeast and re-route power to the 

Southeast. It is noteworthy that such shifts occur as far away as ILMO and MAPP. By 

opening up the closed Southeastern markets, the entire power flow pattern of the 

Eastern Interconnection can be shifted to a considerable degree, with consequences for 

both production costs and energy prices.

A similar pattern emerges in the West, with California as the dominant export market. 

Transfers from the interior Western regions flow through to California, with some 

transfers flowing through the PACNW region on their way to the final demand region. 

Both Northern and Southern California increase their energy imports relative to the 

Base Case, with Southern California wheeling through some energy to Northern 

California.

These shifts in power flows are not large relative to the overall size of the US electric 

power sector. But because inter-regional trade flows are often at the margin, they can 

determine prices and investment patterns in some regions, especially smaller regions. 

This dynamic explains the economic results, which are presented following the 

transmission flow maps.

These maps of inter-regional transmission flows show each link between regions as an 

arrow with two ends. One end indicates the flow in one direction and the other end 

indicates the opposite flow. The number shown by each arrow reflects the change in 

transmission flows from the Base Case to the RTO Policy Case in TWh. For example, 

in the first map of Northeastern regions, the arrow pointing to PJMW and coming from 

So.ECAR indicates that transmission flows drop in the RTO Policy Case by 7.0 TWh 

relative to the Base Case level. In other words, Southern ECAR is transmitting less 

power to PJM West in the RTO Policy Case. Flows from PJMW to PJME, on the other 

hand, increase in the RTO Policy Case by 1.5 TWH relative to the Base Case level.
60

Figure 3.2: Northeast RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case

 (TWh)

PJMS

PJME LILCO

NYC

NEPOOL

UPSNY

DNSNY

PJMW

VIEP

To 

So.ECAR

To CP&L

- 0.7

2.0

2.5

0.0

0.0

0.0

0.0

1.9

0.0

0.2

2.3

0.0

0.9

1.5

- 3.9

0.0

- 0.5

- 7.0

0.4

1.0

3.6

2.9

0.0

1.7

- 4.2

0.0

PJMS

PJME LILCO

NYC

NEPOOL

UPSNY

DNSNY

PJMW

VIEP

To 

So.ECAR

To CP&L

- 0.7

2.0

2.5

0.0

0.0

0.0

0.0

1.9

0.0

0.2

2.3

0.0

0.9

1.5

- 3.9

0.0

- 0.5

- 7.0

0.4

1.0

3.6

2.9

0.0

1.7

- 4.2

0.0
61

Figure 3.3: Southeast RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case

(TWh)

SCEG

Entergy

Southern

TVA

Florida

CP&L Duke

To VIEP

To ILMO

To SPPN

To SPPW

- 0.6

- 4.2

- 1.7

6.4 5.2

To SoECAR

- 0.3

0.0

To MAPP

0.5

- 0.7

3.7

0.2

- 0.2

0.0

6.7

- 0.4

0.2

0.0

- 0.6

0.0

31.0

- 1.8

- 0.3

0.4

1.3

0.0

19.1

- 1.9

0.0

1.9

2.9

0.0

5.2

1.9

5.7

7.1

7.4

SCEG

Entergy

Southern

TVA

Florida

CP&L Duke

To VIEP

To ILMO

To SPPN

To SPPW

- 0.6

- 4.2

- 1.7

6.4 5.2

To SoECAR

- 0.3

0.0

To MAPP

0.5

- 0.7

3.7

0.2

- 0.2

0.0

6.7

- 0.4

0.2

0.0

- 0.6

0.0

31.0

- 1.8

- 0.3

0.4

1.3

0.0

19.1

- 1.9

0.0

1.9

2.9

0.0

5.2

1.9

5.7

7.1

7.4
62

Figure 3.4: Midwest RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case

(TWh)

To VIEP

1.7

MAPP

SPP-N

ILMO

So. 

ECAR

MECS WUMS

COMED

SPP-W

To 

Entergy

- 0.5

0.1

0.0

1.1

5.9

0.5

0.1 0.8

To TVA

6.7

2.6

5.2

1.2

To RMA

To 

Montana

0.2

0.1

0.2 0.4

0.8

5.4

To 

PJMW

To 

DUKE

- 4.9

7.1

- 1.1

1.7

- 7.0

7.4

4.2

1.9

1.7

- 0.4

3.6

To 

AZNM

- 0.7

0.0 To 

ERCOT

- 0.1

0.6

5.7

0.2

0.0

0.2

- 0.7

- 0.2

0.5 0.0 - 1.9

- 0.3

0.1

- 0.2

0.0

0.0

To VIEP

1.7

MAPP

SPP-N

ILMO

So. 

ECAR

MECS WUMS

COMED

SPP-W

To 

Entergy

- 0.5

0.1

0.0

1.1

5.9

0.5

0.1 0.8

To TVA

6.7

2.6

5.2

1.2

To RMA

To 

Montana

0.2

0.1

0.2 0.4

0.8

5.4

To 

PJMW

To 

DUKE

- 4.9

7.1

- 1.1

1.7

- 7.0

7.4

4.2

1.9

1.7

- 0.4

3.6

To 

AZNM

- 0.7

0.0 To 

ERCOT

- 0.1

0.6

5.7

0.2

0.0

0.2

- 0.7

- 0.2

0.5 0.0 - 1.9

- 0.3

0.1

- 0.2

0.0

0.0

MAPP

SPP-N

ILMO

So. 

ECAR

MECS WUMS

COMED

SPP-W

To 

Entergy

- 0.5

0.1

0.0

1.1

5.9

0.5

0.1 0.8

To TVA

6.7

2.6

5.2

1.2

To RMA

To 

Montana

0.2

0.1

0.2 0.4

0.8

5.4

To 

PJMW

To 

DUKE

- 4.9

7.1

- 1.1

1.7

- 7.0

7.4

4.2

1.9

1.7

- 0.4

3.6

To 

AZNM

- 0.7

0.0 To 

ERCOT

- 0.1

0.6

5.7

0.2

0.0

0.2

- 0.7

- 0.2

0.5 0.0 - 1.9

- 0.3

0.1

- 0.2

0.0

0.0
63

Figure 3.5: West RTO Energy Transfers in 2006: Change from Base Case to RTO Policy Case

(TWh)

PACNW

Montana

SOCAL

AZNM

RMA

To SPP-W

0.1

0.0

0.0/0.0

4.3

To MAPP

0.0

0.2

0.0

1.7

0.0

0.1

- 1.5

1.1

- 0.2 0.0

- 1.1

1.2

1.0

0.0

1.6

0.0

10.3

0.5

0.0 0.2

0.0

- 1.5

0.0

- 2.6

NOCAL

- 0.7

0.1

0.2

NWPP-East 0.1

PACNW

Montana

SOCAL

AZNM

RMA

To SPP-W

0.1

0.0

0.0/0.0

4.3

To MAPP

0.0

0.2

0.0

1.7

0.0

0.1

- 1.5

1.1

- 0.2 0.0

- 1.1

1.2

1.0

0.0

1.6

0.0

10.3

0.5

0.0 0.2

0.0

- 1.5

0.0

- 2.6

NOCAL

- 0.7

0.1

0.2

NWPP-East 0.1
64

Figure 3.6: ERCOT Energy Transfers in 2006: Change from Base Case to RTO Policy Case

(TWh)

ERCOT

- 0.2

To SPP-W

- 0.1

ERCOT

- 0.2

To SPP-W

- 0.1
65

3.2.2 RTO Policy Case: Changes in Production Cost and Electricity Prices

The following table shows the production costs for the RTO Policy Case. The effects of 

the policy are gradual, leading to an increase in production cost savings over time. By 

2010, changes in assumptions and the effects on the electric power system are fully in 

place. The overall effect is to decrease production costs significantly, with annual 

savings reaching over $5 billion per year in 2010 in the RTO Policy Case. These 

savings are in range of 1-5% of the total production costs estimated in the model, 

although the total sectoral revenue is larger (as discussed in Section 2), so these 

savings are smaller fraction of the total revenue in the electric power industry.

Table 3.7: RTO Policy Case: System Level Annualized Production Costs 

(Million 2000$)

2004 2006 2010 2015 2020

Fixed Costs 27,042 27,384 28,126 29,564 31,311

Variable Costs 5,389 5,739 6,211 6,839 7,569

Fuel Costs 52,678 52,147 57,628 65,872 73,187

Capital Costs 3,304 6,702 12,289 20,782 30,222

Total System Costs

Savings from Base

% Savings from Base

88,414 

1,080

1.2%

91,972 

2,189

2.3%

104,254 

5,235

4.8%

123,057 

6,318

4.9%

142,289 

7,470

5.0%

On a regional basis, firm electricity prices (as defined in Section 3.1.2) undergo a 

complex set of changes. Changes are defined relative to Base Case prices in any given 

year. While the majority of regions experience price declines in the 3-5% range, some 

regions have more substantial decreases of over 8% by 2010. The region with the 

greatest price increase in any one year in these results is the ILMO (downstate Illinois 

and Missouri) region where prices in one case rise 8% in 2006, while Montana and 

parts of the interior West show the most persistent, albeit small, price increases. 
66

Table 3.8: RTO Policy Case: Regional Firm Electricity Prices

 (2000$/MWh)

RTO Sub-Region 2004 2006 2010 2015 2020

West AZ-NM 38.2 35.9 33.6 31.0 27.4

West RMA 37.1 36.8 34.3 31.6 28.1

West Montana 35.6 33.1 32.1 31.4 28.1

West NWPP-East 33.8 31.7 30.3 29.9 26.8

West Pacific Northwest 38.5 35.9 32.5 31.5 27.9

West Northern CA 42.0 39.4 35.0 33.2 29.4

West Southern CA - NV 41.4 38.9 34.8 32.9 29.1

West Average 39.5 37.1 33.8 32.1 28.4

ERCOT 25.9 23.6 31.1 30.1 28.1

Midwest COMED 30.6 29.6 31.8 31.6 30.1

Midwest ILMO 29.5 29.6 30.4 31.1 29.6

Midwest MAPP 32.1 31.4 31.5 31.2 28.3

Midwest MECS 31.1 30.0 32.7 32.7 31.3

Midwest So. ECAR 32.4 31.3 32.3 32.2 30.8

Midwest SPP-North 30.5 31.0 31.4 30.8 28.4

Midwest SPP-West 38.0 34.8 32.8 31.1 28.2

Midwest WUMS 33.7 32.0 31.2 30.7 29.2

Midwest Average 32.4 31.3 32.0 31.7 29.8

Southeast Entergy 24.7 22.9 24.8 29.3 27.8

Southeast CP&L 34.3 33.1 32.7 31.3 31.1

Southeast DUKE 34.4 33.2 32.7 31.4 31.2

Southeast SCEG 35.0 33.7 33.5 32.0 31.7

Southeast Southern 34.4 33.3 33.0 31.5 31.1

Southeast TVA 32.5 31.5 32.7 31.1 29.1

Southeast FRCC 39.2 37.0 35.5 33.8 31.8

Southeast Average 33.5 32.1 32.2 31.6 30.6

Northeast Downstate NY 39.5 37.7 36.1 34.7 34.1

Northeast LILCO 48.8 41.0 38.6 37.2 36.9

Northeast New York City 43.5 41.0 39.0 37.5 37.2

Northeast Upstate NY 33.0 32.2 32.6 31.9 31.5

Northeast NEPOOL 30.8 36.0 36.4 35.0 33.9

Northeast PJM-East 37.3 35.4 34.6 33.5 33.0

Northeast PJM-South 35.7 34.2 34.0 33.1 32.9

Northeast PJM-West 33.2 31.9 32.1 31.3 30.8

Northeast VIEP 37.0 34.6 33.3 31.9 31.5

Northeast Average 36.0 35.4 34.8 33.6 33.0

The implications of these price effects are discussed after the full set of scenario results 

is presented. Here the focus is on the reason for the price changes. The model is 

based on a database of actual generating plants, augmented by new units that are 

selected by the model as needed for reasons of economic efficiency and system 

reliability. The specific sets of generating units within each model region are dispatched 

according to economic costs (‘merit order dispatch’), leading to sets of regional supply 

curves for energy as illustrated below (using just two model regions as an example).
67

Figure 3.7: Illustrative Supply Curves

The figure shown above illustrates how small shifts in transmission transfer capability 

and hurdle rates can yield significant price increases in some regions, but only modest 

price decreases in neighboring regions. Note that when transmission transfer capability 

between Region A and Region B is expanded only slightly we can see dramatic 

increases in marginal energy costs in Region A and slight decreases in Region B. This 

effect can be related to either increased transmission transfer capability, or lowered 

hurdle rates between regions. Of course this effect can also work the other way around, 

with an exporting region’s prices increasing only slightly (or not at all, if exports shift the 

regional supply curve along a flat segment) and the importing region’s prices declining 

more. It is the complex set of interactions among the regional supply curves that 

determines the overall economic impact of changes in inter-regional trade.

Below the changes in regional energy prices between the Base Case and the RTO 

Policy Case are mapped for the year 2010, when the changes in assumptions 

representing RTO policy impacts are fully in place.

MW

$/MWh

Base Case

Supply Curve Peak

RTO Policy Case

Supply Curve Peak

Region B

Region A
68

Figure 3.8: Percent Change in 2010 Firm Power Prices from the Base to RTO Policy Case
69

3.3 Transmission Only Case

In addition to the RTO Policy Case, which is intended to represent a best estimate of 

potential economic benefits of RTO policy, a number of other scenarios were developed 

as described in Section 2. The results of each scenario are presented in turn, beginning 

with the Transmission Only Case. 

The Transmission Only Case resulted in the following estimates for system-wide 

production costs:

Table 3.9: Transmission Only Case: System Level Annualized Production Costs

 (Million 2000$)

2004 2006 2010 2015 2020

Fixed Costs 27,067 27,425 28,230 29,707 31,553

Variable Costs 5,348 5,699 6,189 6,830 7,560

Fuel Costs 53,254 53,798 61,572 70,651 78,471

Capital Costs 3,420 6,884 12,732 21,381 30,884

Total System Costs

Savings from Base

% Savings from Base

 89,089 

405 

0.5%

 93,805 

356 

0.4%

 108,723 

767 

0.7%

 128,568 

806 

0.6%

 148,468 

1,291

0.9%

The Transmission Only Case is intended to represent a “limited benefits” scenario in the 

Commission staff’s view of the potential economic impacts of RTO policy, considering 

only direct benefits to increased reserve pooling and transmission coordination. The 

benefits in this case (as detailed in Table 3.9) are significant even though assumptions 

are conservative. 

In terms of more detailed regional results, the Transmission Only Case resulted in the 

following firm electricity prices (on an annual average basis, accounting for both energy 

and capacity value):
70

Table 3.10: Transmission Only Case: Regional Firm Electricity Prices 

(2000$/MWh)

RTO Sub-Region 2004 2006 2010 2015 2020

West AZ-NM 38.6 36.4 35.0 32.3 28.5

West RMA 38.5 37.6 35.6 32.8 29.0

West Montana 35.8 33.7 33.4 32.7 29.2

West NWPP-East 34.4 32.9 32.5 31.2 27.8

West Pacific Northwest 38.9 36.5 33.9 32.9 29.0

West Northern CA 42.4 40.0 36.4 34.5 30.6

West Southern CA - NV 42.0 39.6 36.1 34.3 30.3

West Average 40.0 37.8 35.2 33.4 29.5

ERCOT 26.0 24.6 32.6 31.5 29.2

Midwest COMED 31.6 30.9 33.4 33.1 31.6

Midwest ILMO 30.4 30.7 32.1 32.5 31.0

Midwest MAPP 32.7 32.5 33.2 32.5 29.4

Midwest MECS 32.1 31.4 34.8 34.4 32.7

Midwest So. ECAR 33.3 32.8 34.2 33.7 32.2

Midwest SPP-North 31.3 32.1 33.2 32.2 29.5

Midwest SPP-West 38.3 35.4 34.1 32.3 29.3

Midwest WUMS 34.6 32.7 32.8 32.2 30.4

Midwest Average 33.2 32.5 33.7 33.1 31.1

Southeast Entergy 25.5 24.4 26.4 30.9 29.3

Southeast CP&L 35.1 34.3 34.1 32.7 32.5

Southeast DUKE 35.1 34.4 34.2 32.8 32.6

Southeast SCEG 35.9 35.0 34.7 33.2 32.9

Southeast Southern 35.2 34.6 34.5 32.8 32.5

Southeast TVA 33.3 32.7 34.1 32.5 30.3

Southeast FRCC 39.5 37.7 37.0 35.3 33.2

Southeast Average 34.2 33.3 33.7 33.0 31.9

Northeast Downstate NY 39.9 38.5 37.7 36.2 35.6

Northeast LILCO 48.6 41.6 40.1 38.7 38.5

Northeast New York City 43.5 41.7 40.5 39.1 38.9

Northeast Upstate NY 33.7 33.1 34.4 33.4 32.9

Northeast NEPOOL 31.1 37.0 38.1 36.5 35.5

Northeast PJM-East 37.7 36.3 36.2 34.9 34.4

Northeast PJM-South 36.6 35.3 35.5 34.5 34.2

Northeast PJM-West 33.9 33.0 33.8 32.9 32.1

Northeast VIEP 37.6 35.2 34.8 33.2 32.9

Northeast Average 36.5 36.3 36.4 35.1 34.5

The dynamics of the Transmission Only Case are similar in most respects to the RTO 

Policy Case. Because the changes in inter-regional flows are caused by the changes in 

transmission hurdle rates, and these changes are maintained in the Transmission Only 

Case, the overall pattern of flows shifts towards the Southeast in the Eastern 

Interconnect and towards California in the Western Interconnect. Relative changes in 
71

generation, production costs, and electricity prices follow suit. In this case, however, 

there are no efficiency gains on the part of generators, so the changes to inter-regional 

flow patterns are the only driver of economic gains throughout the forecast horizon. 

One significant difference between the Transmission Only Case and the RTO Policy 

Case is the presence of more regional price increases in the Transmission Only Case. 

The underlying economics of power supply in the various regions determine how prices 

will change when inter-regional trade patterns shift. Some regions can export power 

without price increases (since they have available generating capacity that is no more 

costly than the Base Case generation mix), while other regions may have prices rise 

with only small changes in exports. Even though these price increases are small in 

percentage terms, with none over 10% in any region or year, the implication is that 

improvements in market functioning are critical for securing clear consumer benefits. 

Such market improvements, as modeled in the RTO Policy Case, allow for increased 

exports and price declines in most parts of the country.

Even in the absence of competitive incentives for energy market improvements, 

improvements in the management of the transmission grid offer significant potential 

economic gains on a national production cost basis. Sensitivity cases designed to show 

the effect of RTO scope and configuration are presented later in this section. 

Transmission-related changes do affect the economic results estimated here, and are 

significant, even though generator efficiencies lead to much greater changes in 

economic outcomes.

3.4 Demand Response Scenario

The Demand Response Scenario presented next adds a limited amount of priceresponsive demand (intended to represent a conservative estimate of real-time pricing 

impacts and distributed generation, taken together as a simplifying assumption) to the 

same underlying assumptions as in the RTO Policy Case. The Demand Response 

Scenario leads to the following changes in estimated production costs:

Table 3.11: Demand Response Case: System Level Annualized Production Costs

 (Million 2000$)

2004 2006 2010 2015 2020

Fixed Costs 26,943 26,883 27,584 28,969 30,644

Variable Costs 5,382 5,750 6,225 6,854 7,585

Fuel Costs 52,642 52,348 57,763 65,998 73,357

Capital Costs 3,377 5,016 10,370 18,631 27,775

Total System Costs

Savings from Base

% Savings from Base

88,343 

1,150

1.3%

89,997 

4,164

4.4%

101,941 

7,548

6.9%

120,451 

8,923

6.9%

139,361 

10,398

6.9%

The Demand Response Case is not designed as an upper bound, in the Commission 

staff’s view, to the possible savings under a successful RTO policy implementation. All 

of the assumptions used in this scenario are based on earlier related analysis, or other 

existing information, as discussed in Section 2. Hence these are changes that could 

reasonably be expected to occur in a more competitive electricity market. Additional 
72

changes to assumptions could be made in order to estimate a reasonable upper bound 

on potential RTO benefits. The Demand Response Case is instead intended to isolate 

the important role of price information and consumer choice in determining economic 

outcomes in the electric power markets.

The detailed regional results for firm electricity prices are as follows:

Table 3.12: Demand Response Case: Regional Firm Electricity Prices 

(2000$/MWh)

RTO Sub-Region 2004 2006 2010 2015 2020

West AZ-NM 38.3 35.9 33.7 31.0 27.4

West RMA 37.8 36.5 34.4 31.6 28.1

West Montana 35.5 33.1 31.4 31.4 28.2

West NWPP-East 33.8 31.8 30.3 29.5 26.7

West Pacific Northwest 38.5 36.0 32.5 31.5 27.9

West Northern CA 42.1 39.3 35.0 33.1 29.5

West Southern CA - NV 41.5 39.0 34.7 32.9 29.1

West Average 39.6 37.1 33.8 32.0 28.4

ERCOT 25.9 23.6 24.4 30.2 28.1

Midwest COMED 30.6 29.3 30.4 31.5 30.2

Midwest ILMO 29.4 28.3 30.2 31.2 29.5

Midwest MAPP 31.9 31.4 31.4 31.2 28.3

Midwest MECS 31.0 29.7 31.5 32.8 31.4

Midwest So. ECAR 32.3 30.9 32.4 32.1 30.9

Midwest SPP-North 30.2 29.6 31.5 30.8 28.3

Midwest SPP-West 38.1 34.8 32.8 31.2 28.3

Midwest WUMS 33.6 32.0 31.1 30.7 29.2

Midwest Average 32.3 30.9 31.8 31.7 29.9

Southeast Entergy 24.6 22.9 24.7 29.4 27.7

Southeast CP&L 34.5 33.2 32.6 31.3 31.2

Southeast DUKE 34.3 33.2 32.8 31.5 31.2

Southeast SCEG 35.0 33.8 33.4 31.9 31.7

Southeast Southern 34.3 33.4 33.0 31.5 31.1

Southeast TVA 32.4 31.1 32.7 31.2 29.1

Southeast FRCC 39.5 37.0 35.5 33.8 31.8

Southeast Average 33.6 32.1 32.2 31.7 30.6

Northeast Downstate NY 39.5 36.5 36.1 34.7 34.1

Northeast LILCO 50.3 40.9 38.6 37.1 36.9

Northeast New York City 43.5 39.3 39.0 37.6 37.3

Northeast Upstate NY 33.0 31.1 32.4 31.9 31.5

Northeast NEPOOL 34.3 35.1 35.7 35.1 34.0

Northeast PJM-East 37.3 35.4 34.7 33.5 32.9

Northeast PJM-South 35.6 34.2 33.9 33.1 32.8

Northeast PJM-West 33.2 31.9 32.2 31.4 30.8

Northeast VIEP 37.1 34.5 33.3 31.9 31.5

Northeast Average 36.7 34.9 34.7 33.6 33.1
73

These economic results indicate the importance of fully functioning markets, in that the 

tradeoffs between demand levels and the need for generating capacity drive both 

production costs and prices down in the Demand Response Case relative to the other 

cases presented here. Demand response also helps avoid short-term price spikes and 

can moderate the potential for market power abuse, effects this study does not explicitly 

capture. If RTOs do present opportunities to improve market functioning, including 

enhancing demand response, the economic gains could be quite large.

3.5 Sensitivity Case I: Larger RTOs

One of the critical issues for this study concerns the geographic scope and configuration 

of RTOs. A primary purpose of this study is to assist with a quantitative basis for 

determining the appropriate number of RTOs. In order to address this issue directly, 

two sensitivity cases were prepared. This first sensitivity case considers very large 

RTOs, encompassing the entire Western and Eastern Interconnects (with ERCOT 

remaining separate). This three-RTO configuration is described in Section 2 in 

conjunction with the RTO Policy Case configuration. Results for this Larger RTOs Case 

are as follows:

Table 3.13: Larger RTOs: System Level Annualized Production Costs 

(Million 2000$)

2004 2006 2010 2015 2020

Fixed Costs 27,050 27,393 28,144 29,563 31,311

Variable Costs 5,396 5,740 6,216 6,837 7,573

Fuel Costs 52,575 52,096 57,542 65,884 73,142

Capital Costs 3,280 6,665 12,283 20,716 30,164

Total System Costs

Savings from Base

% Savings from Base

88,301

1,192

1.3%

91,893

2,267

2.4%

104,185

5,304

4.8%

123,000

6,374

4.9%

142,190

7,568

5.1%
74

Table 3.14: Larger RTOs: Regional Firm Electricity Prices

 (2000$/MWh)

RTO Sub-Region 2004 2006 2010 2015 2020

West AZ-NM 38.2 35.9 33.6 31.0 27.4

West RMA 37.5 37.0 34.3 31.6 28.1

West Montana 35.6 33.1 32.1 31.4 28.1

West NWPP-East 33.8 31.7 30.3 29.9 26.8

West Pacific Northwest 38.5 35.9 32.5 31.5 27.9

West Northern CA 42.0 39.4 35.0 33.2 29.4

West Southern CA - NV 41.4 38.9 34.8 32.9 29.1

West Average 39.5 37.1 33.8 32.1 28.4

ERCOT 25.9 23.6 31.1 30.1 28.1

East COMED 31.0 30.4 32.2 31.9 30.3

East ILMO 29.9 30.3 30.6 31.4 29.6

East MAPP 32.3 32.1 31.9 31.5 28.4

East MECS 31.5 30.9 33.7 33.2 31.3

East So. ECAR 32.8 32.2 32.8 32.6 31.1

East SPP-North 30.7 31.8 31.7 31.1 28.4

East SPP-West 38.0 34.8 32.8 31.1 28.2

East WUMS 34.2 32.4 31.5 31.0 29.2

East Entergy 24.4 23.0 25.5 29.3 27.6

East CP&L 34.2 33.5 32.8 31.4 31.2

East DUKE 33.9 33.4 32.8 31.5 31.2

East SCEG 34.8 33.8 33.4 31.9 31.6

East Southern 34.1 33.4 33.0 31.5 31.1

East TVA 32.1 31.5 32.7 31.3 29.1

East FRCC 39.2 37.0 35.5 33.8 31.8

East Downstate NY 39.4 37.6 36.1 34.6 34.1

East LILCO 48.8 40.9 38.6 37.2 36.9

East New York City 43.5 40.9 39.0 37.5 37.3

East Upstate NY 32.3 31.7 32.6 31.8 31.3

East NEPOOL 30.7 36.0 36.4 35.1 33.9

East PJM-East 36.9 35.3 34.6 33.4 32.9

East PJM-South 34.7 33.8 33.9 32.9 32.8

East PJM-West 32.2 31.3 32.1 31.3 30.8

East VIEP 35.6 34.2 33.3 31.9 31.5

East Average 33.5 32.8 32.9 32.2 30.8

These results tend to confirm the conclusion drawn from the primary policy cases 

reported first, that the scope and configuration of RTOs does make a difference in the 

potential economic benefits of RTO policy. Larger RTOs could reduce more barriers to 

inter-regional trade, leading to greater efficiency gains. But the size of these gains is 

small relative to the much larger gains that could come from market improvements and 

better generator performance. 
75

In the analysis carried out here, it is more important to have well-functioning competitive 

markets than it is to have one specific RTO configuration, although fewer and larger 

RTOs do lead to the greatest potential benefits. To the extent that a clear link can be 

established between RTO scope and competitive market effectiveness, the benefits of 

larger RTOs would be more significant. Further research, and perhaps further 

experience, would be needed to fully assess such possible links between RTO scope 

and the functioning of competitive markets.

3.6 Sensitivity Case II: Smaller RTOs

A second sensitivity case was developed to complement the Larger RTOs Case 

described above. This case maintains a greater number of RTOs, including leaving 

existing ISOs largely intact and creating three Western RTOs instead of one. This RTO 

configuration is described and mapped in Section 2. Results for this sensitivity case are 

as follows:

Table 3.15: Smaller RTOs: System Level Annualized Production Costs 

(Million 2000$)

2004 2006 2010 2015 2020

Fixed Costs 27,045 27,396 28,134 29,571 31,313

Variable Costs 5,391 5,736 6,214 6,836 7,560

Fuel Costs 52,719 52,166 57,669 65,991 73,281

Capital Costs 3,297 6,733 12,302 20,795 30,214

Total System Costs

Savings from Base

% Savings from Base

88,452 

1,041

1.2%

92,031 

2,130

2.3%

104,319 

5,171

4.7%

123,192 

6,182

4.8%

142,368 

7,390

4.9%
76

Table 3.16: Smaller RTOs Firm Electricity Prices

 (2000$/MWh)

RTO Sub-Region 2004 2006 2010 2015 2020

Rockies AZ-NM 37.4 33.8 32.9 30.9 27.4

Rockies RMA 37.6 36.1 34.2 31.6 28.1

Rockies Average 37.5 34.5 33.4 31.1 27.6

Pacific-NW Montana 35.3 32.3 31.8 31.6 28.1

Pacific-NW NWPP-East 32.9 29.9 27.7 28.2 25.3

Pacific-NW Pacific Northwest 38.6 35.3 33.0 31.6 28.0

Pacific-NW Average 37.5 34.3 32.2 31.1 27.6

California Northern CA 43.4 39.3 35.0 33.1 29.4

California Southern CA - NV 42.8 39.0 34.7 32.9 29.1

California Average 43.1 39.1 34.9 33.0 29.2

ERCOT 25.8 23.6 31.1 30.1 28.1

Midwest COMED 30.6 29.5 31.9 31.6 30.2

Midwest ILMO 29.4 29.5 30.6 31.2 29.6

Midwest MAPP 32.0 31.5 31.8 31.3 28.4

Midwest MECS 31.0 29.9 32.7 32.7 31.3

Midwest So. ECAR 32.3 31.2 32.4 32.2 30.8

Midwest SPP-North 30.3 30.9 31.7 30.8 28.4

Midwest SPP-West 38.0 34.8 32.8 31.1 28.2

Midwest WUMS 33.9 32.0 31.3 30.8 29.2

Midwest Entergy 24.6 23.0 25.6 29.3 27.4

Midwest Average 31.3 30.2 31.3 31.4 29.6

Southeast CP&L 34.4 33.4 32.5 31.3 31.2

Southeast DUKE 34.3 33.3 32.6 31.5 31.2

Southeast SCEG 34.9 33.9 33.3 31.9 31.6

Southeast Southern 34.1 33.2 32.8 31.4 31.1

Southeast TVA 32.3 31.5 32.6 31.2 29.1

Southeast Average 33.8 32.9 32.7 31.4 30.7

FRCC 39.6 37.2 35.5 33.8 31.7

New York Downstate NY 40.2 38.2 36.1 34.8 34.1

New York LILCO 49.7 40.9 38.6 37.2 36.9

New York New York City 43.4 41.3 39.1 37.6 37.3

New York Upstate NY 34.0 33.5 32.9 32.2 31.6

New York Average 40.3 38.0 36.3 35.1 34.7

NEPOOL 30.6 35.9 36.5 35.1 33.9

PJM & VIEP PJM-East 37.2 34.6 34.0 33.3 32.8

PJM & VIEP PJM-South 35.5 33.9 33.8 33.0 32.7

PJM & VIEP PJM-West 33.1 31.4 31.7 31.3 30.7

PJM & VIEP VIEP 36.4 34.4 33.1 31.9 31.5

PJM & VIEP Average 35.9 33.8 33.3 32.5 32.1

Again, the results using the assumptions and analytic approach adopted here support 

the idea that RTO configuration does matter, with larger RTOs being more beneficial. 

Market improvements lead to greater potential economic benefits than changes to the 
77

transmission system alone, but changes to the transmission system do offer the 

potential for economic gains.

Note that benefits in these sensitivity cases are derived only from changes in the 

transmission assumptions. As noted earlier, to the extent that RTO scope is linked to 

overall market improvements the importance of scope for overall benefits would be 

greater.

Having presented results from the modeling scenarios, the next section of the report 

turns to integrating these results with potential RTO costs, and placing the modeling 

results into a more comprehensive framework. The section also discusses a number of 

important economic issues that are not directly represented or fully analyzed in the 

modeling framework alone.

3.7 Discussion and Integration of Costs

The results of the analysis show that there are large potential benefits to RTO policy as 

envisioned by the Commission. Even accounting for significant uncertainty as to the 

effectiveness of incentives for market improvements, the scenarios analyzed suggest 

that multi-billion dollar net benefits are the most likely outcome of a nationwide move to 

an RTO structure. The most important driver of this result is the set of assumptions 

regarding competitive market incentives and the potential for improved generator 

performance resulting from Commission policy.

Summarizing the results of all the cases, and taking a net present value of changes in 

total production costs over a 20 year period, shows that benefits of the policy are 

uncertain but lie within a positive range under the analytic approach adopted for this 

study.

Table 3.17: System Level Production Costs Across Cases

 (Billion 2000$)

2004 2006 2010 2015 2020

NPV1

2002-

2021

Base Case 89.5 94.2 109.5 129.4 149.8 1,076.8

RTO Policy Case

Savings from Base

88.4

1.1

92.0

2.2

104.3 

5.2

123.1 

6.3

142.3 

7.5

1,035.9

40.9

Transmission Only Case

Savings from Base

89.1 

0.4

93.8 

0.4

108.7 

0.8

128.6 

0.8

148.5 

1.3

1,070.6

6.2

Demand Response Case

Savings from Base

88.3 

1.2

90.0 

4.2

101.9 

7.5

120.5 

8.9

139.4 

10.4

1,016.8

60.0

1

Assumes 6.97% discount rate

It is reasonable to expect that these benefits will vary across regions and will increase 

over time. The wide range of potential economic benefits assessed here indicates 

substantial uncertainty with regard to the exact mechanisms and magnitudes of policyinduced changes to the electric power system. It is likely that further research would do 

little to narrow this range at the present time, although evidence from other industries 
78

and countries that have undertaken competitive market transitions can offer limited 

analogies and evidence. Estimating a wide range of benefits allows for the actual 

uncertainty of potential policy effects to be taken into consideration. 

In comparison to the other studies summarized in Section 1.3, the estimated production 

cost savings from this study appear to fall into a reasonable range. In percentage 

terms, cost savings in the range of 1-5% are consistent with other work of a related 

nature. Note that these percentages are in comparison to the relevant production costs 

calculated in the IPM® framework and not the total industry revenues as noted in 

Section 2.5. In comparison to the more than $200 billion in overall industry revenue the 

percentage savings estimated here are in the range of 0-3% per year.

As has been made clear throughout this report, there are some economic issues that 

the analytic framework adopted here cannot address directly. This is a consequence of 

the challenging set of analytic requirements laid out in Section 1.4. The approach taken 

in this study is to place these issues into perspective and make any informed 

conclusions that can be developed from available information.

In particular, the geographic and temporal distribution of potential economic impacts is 

an important consideration in evaluating the overall policy. A number of economic 

issues arise in this context including: 

• The costs of RTO establishment;

• Avoidance of short-term market imbalances and market power abuses;

• Regional variations in economic outcomes; and 

• Net impact of near-term costs and long-term benefits.

Each of these topics is discussed in this section. 

3.7.1 Costs of RTO Establishment

In order to fully evaluate RTO policy from an economic cost/benefit standpoint, 

estimates of the costs of RTO establishment are required. As noted in Section 2, the 

IPM®framework does not estimate costs that are not relevant for system dispatch and 

generation investment. In addition, available information on the costs of RTO 

establishment indicates a great deal of variation and uncertainty.

To make the best assessment of the net economic impact of RTO policy, a range of 

RTO startup costs can be considered. The relationship between the expense of RTO 

establishment and the functional effectiveness of a specific RTO remains unclear, so it 

is premature to expect that more or less costly RTO structures will ultimately be needed 

for an effective nationwide system. Taking this uncertainty into account explicitly is 

therefore the most accurate assessment at present.

There are five established independent system operators in the US: NEPOOL, NYISO, 

PJM, ERCOT and CAISO. For purposes of this cost estimate ERCOT is excluded due 
79

to the limited amount of information available on startup costs. In considering how the 

startup costs of these existing structures might be extended throughout the country, 

several metrics for relative cost were considered: cost per MW of installed capacity, cost 

per GWh of delivered energy, cost per customer served, and cost per network node. 

Table 3.14 below shows the existing ISOs in comparison to the entire US (excluding 

Texas and Alaska).

Table 3.18: Characteristics of Existing ISOs

CAISO PJM NEPOOL NYISO Total National 

(Less TX+AK)

Installed 

Capacity (MW) 44,200 57,100 24,600 36,100 630,710

Annual Energy 

(TWh) 220 249 121 149 3,434

Population 

Served 

(Millions)

27 22 13 22 257

Network Nodes 3,000 1,900 1,100 1,168 46,000

Two existing assessments of RTO startup costs form the basis for a low and high 

estimate of nationwide RTO establishment costs. On the low end, the extension of 

PJM’s operating systems throughout the Northeast was estimated to cost $71 million, 

reflecting maximum use of existing infrastructure. If extended nationwide using this 

starting cost estimate, total startup costs could be as little as $500 million-$1.5 billion 

nationwide, for a central low cost estimate of $1 billion.

On the high end, startup costs can reflect the construction of dedicated infrastructure 

such as IT systems and new, separate control centers. If these costs are extended 

using the various relative cost metrics, costs for nationwide RTO startup could range as 

high as $4.2-7.3 billion, for a central high cost estimate of $5.75 billion.

This range of more than 5 to 1 in startup cost uncertainty could probably be narrowed 

with a more focused research effort. For the purposes of this study the major 

observation is that even if startup costs are at the high end of the range, they are 

essentially one-time costs that are netted out against the ongoing economic benefits of 

RTOs. Even a $5 billion initial cost would be rewarded after several years with 

economic gains that appear to justify the initial expense.

Startup costs and operating costs are two distinct cost categories. Although some 

comparative studies of ISO operating costs have been completed, these studies have 

not compared the ISO operating costs to the operating costs of the existing systems or 

the systems replaced by the ISOs. As a general matter, it could be argued that merger 

and acquisition-type savings could be realized from a move to larger ISO or RTO 

structures. At the same time the increased functional responsibilities of RTOs could 

lead to higher operating costs. For this analysis it is assumed that operating costs will 

be a relatively unimportant element of the overall economic impact of RTO policy once 
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existing system operating costs are taken into consideration. It remains an open 

question whether a small overall cost or benefit may be realized in this area.

It is worth noting that if RTO costs are at the high end of the range and RTO benefits 

are at the low end of the range (as reflected in the Transmission Only Case results), the 

national net cost/benefit outcome is close to even. This indicates that there is relatively 

little downside risk to the Commission’s policy. Based on the analysis carried out for 

this study, the chances of a net loss from RTO policy is small on a nationwide basis. 

However, a major portion of the potential net gains from RTO policy could be lost if 

startup costs are high or if realized benefits are low. This reinforces the importance of 

policy implementation as a means of maximizing the net benefits of RTOs.

3.7.2 Short-term Market Imbalances and Market Power

As discussed in Section 2, the analytic approach relied on for this economic cost/benefit 

assessment had to be national and long-term in scope. The simulation modeling 

framework and associated analysis is therefore limited in several important respects. 

One important limitation concerns short-term price volatility. The modeling framework 

estimates prices by load segment, including a peak pricing segment, based on an 

efficient spot or pool pricing mechanism. This approach yields good estimates of prices 

over time, but as configured for a national long-term analysis, this use of the modeling 

framework will not predict or assess market imbalances that can cause significant 

divergence from equilibrium pricing in certain times and places. Additional analysis 

could focus on such short-term pricing effects, and the Commission has conducted 

retrospective analyses of such effects. Market and regulatory responses could limit the 

duration of market imbalances, but they can represent significant short-term energy 

price risk for market participants. 

The analysis conducted here also does not attempt to assess the potential for market 

power abuse, and assumes that all individual supply units participate in least-cost 

dispatch under spot pricing mechanisms. Several types of market conditions can 

contribute to a given market’s vulnerability to market power. These include 

concentration of ownership, lack of demand response, transmission constraints and 

barriers to timely and sufficient entry of new supply options (including substitute 

markets). Such market conditions can be assessed. Similarly, instances of noncompetitive pricing can be addressed as they occur. 

3.7.3 Regional Variations in Economic Outcomes

An important finding of this analysis is the persistence of regional variations in costs and 

benefits of RTO policy. Different regions have different starting points in terms of their 

supply and demand characteristics, and their degree of interconnection with other 

regions. These variations play out over a long time horizon as RTO policy allows 

increased inter-regional trade. 
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Persistent increases in production costs and/or firm electricity prices can occur in a 

particular region if that region has an effective supply curve that is steeply sloped 

relative to other regions. In other words, when a relatively small amount of power is 

exported from such a region, it requires that other generating units operate to meet local 

demand, and these units can be considerably more expensive that the supply that was 

operating in the absence of the increased inter-regional trade. So for such effects to 

occur there must be a relatively low-cost region with a relatively steep supply curve that 

can export to a higher-cost region. As a result of the special characteristics of each 

region’s market conditions, some regions experience long-term price increases, while 

others do not. 

There are analytic methods that go beyond the net efficiency analysis conduc ted for this 

study; changes in production cost and energy prices are not the only measures of 

economic impact. Within a region, revenues including net imports and exports and 

producer earnings can also be estimated. Regions where prices increase should also 

experience gains from trade in the form of increased export revenue and supplier 

earnings. This suggests that more detailed regional analyses could trace the revenue 

flows and begin to consider distributional questions that fall more properly into other 

policy contexts. Such detailed regional analyses could also consider the impact of 

market and regulatory uncertainties on local economic outcomes, and bring a finer 

degree of resolution to specific transmission flow and network characteristics.

In addition, this analysis does not consider macroeconomic impacts such as secondary 

benefits, economic development, and employment. Such effects could offset (or 

magnify) the consumer impacts of energy price changes, but these dynamics are highly 

specific to local economic conditions and have not been assessed here.

This study estimates changes in wholesale electric power prices that could result from 

RTO policy. However, concerns have been raised about the role of contracts and 

especially native load commitments in effectively reducing the responsiveness of the 

power system to changes in regulatory policy. If contracts, including native load, are in 

fact non-responsive to underlying market conditions, then consumers will not 

experience the potential benefits (or costs) of policy changes as much or as quickly as 

they would in a more responsive transactional environment. This ‘dampening’ effect of 

contracts and native load treatment is not directly represented in the analysis, but is a 

factor to be kept in mind when interpreting results.