20392 Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices

1 Inquiry Concerning the Commission’s Merger

Policy Under the Federal Power Act: Policy

Statement, Order No. 592, FERC Stats. & Regs.

¶ 31,044 (1996), order on reconsideration, 78 FERC

¶ 61,321 (1997) (Policy Statement).

2Appendix to DOJ Merger NOI Comments at A–

11, n12.

3Wisconsin Electric Power Company, et al.

(Primergy), 79 FERC ¶ 61,158 at 61,694 (1997).

4Typically, the interconnected areas would be

control or planning areas, but the exact geographic

area would depend on how the model was

implemented.

filed within the time required herein, if

the Commission on its own review of

the matter finds that permission and

approval for the proposed abandonment

are required by the public convenience

and necessity. If a motion for leave to

intervene is timely filed, or if the

Commission on its own motion believes

that a formal hearing is required, further

notice of such hearing will be duly

given.

Under the procedure herein provided

for, unless otherwise advised, it will be

unnecessary for Transco to appear or be

represented at the hearing.

Linwood A. Watson, Jr.,

Acting Secretary.

[FR Doc. 98–10899 Filed 4–23–98; 8:45 am]

BILLING CODE 6717–01–M

DEPARTMENT OF ENERGY

Federal Energy Regulatory

Commission

[Docket No. PL98–6–000]

Inquiry Concerning the Commission’s

Policy on the Use of Computer Models

in Merger Analysis; Notice of Request

for Written Comments and Intent To

Convene a Technical Conference

The Federal Energy Regulatory

Commission (Commission) hereby

announces that it is requesting

comments on the use of computer

models in merger analysis and intends

to convene a public conference to

discuss this matter. The purpose of this

inquiry is to gain further input and

insight into whether and how computer

models should be used in the analysis

of mergers, including whether computer

models can be useful in a horizontal

screen analysis that follows the

Appendix A guidelines of the Merger

Policy Statement.1

We are issuing this request

concurrently with the Notice of

Proposed Rulemaking on Revised Filing

Requirements Under Part 33 of the

Commission’s Regulations (Docket No.

RM98–4–000). In that NOPR we identify

the use of computer models as an

emerging issue in the analysis of

mergers. We are issuing this notice

concurrently in order to inform the

Commission’s understanding of the

current and likely future role played by

computer models in merger analysis.

The attachment to this notice provides

a framework for discussion of models

and includes a sample model intended

to serve as a starting point for

discussion and comment.

I. Introduction

The use of computer models—

specifically, computer programs used to

simulate the electric power market—has

been raised in comments on the Policy

Statement and also in specific cases. In

comments on the Policy Statement, the

Department of Justice (DOJ)

recommended using computer

simulations to delineate markets. DOJ

also noted that these simulations could

be helpful in gauging the market power

of the merged firm.2

In Primergy, the applicants used a

computer simulation in their market

power analysis. We did not accept the

results of this computer simulation, in

part because we felt that the model was

not properly structured or tested.

However, it was not our intention to

inhibit the use of computer models. We

emphasized that ‘‘we do not wish to

discourage the development of

computer models for use in merger

analysis’’.3

The Commission continues to believe

that a properly structured computer

model could account for important

physical and economic effects in

analyses of mergers and may be a

valuable tool to use in horizontal screen

analyses. A computer model could be

particularly useful in identifying the

suppliers in the geographic market that

are capable of competing with the

merged company. A computer model

may also provide a framework to help

ensure consistency in the treatment of

those data in identifying suppliers in a

geographic market.

Two important ways in which a

computer model could improve the

accuracy of the delivered price test are:

(1) by explicitly representing economic

interactions between suppliers and

loads at various nodes in the

transmission network and (2) by

accounting for the transmission flows

that result from power transactions. We

discuss these and other matters in

greater detail in the Attachment.

Interactions between suppliers and

loads. In competitive markets for

electric energy, decisions about what

suppliers would serve what loads are

likely to be driven by short-run marginal

costs, including the opportunity cost to

suppliers of serving one load rather than

another. Because there can be many

possible combinations of supplies and

loads, some form of computer model

could be helpful in estimating such

combinations.

Transmission flows from exchanges of

power. Because of the properties of

electric power flows, exchanges of

power between control areas affect

flows throughout the transmission grid.

Any reasonable approximation of these

effects may require a computer model to

make the many calculations needed to

simulate the electric power flows.

Developing and using a computer

model involves a number of choices

about the structure of the model, the

level of detail reflected in the model, the

sources of information, and other issues.

These issues are discussed in the

Attachment. If these technical aspects of

model design and development can be

addressed adequately, a computer

program could be helpful in defining

geographic markets. One common

approach to market simulation,

discussed further as an example in the

Attachment, is to model the dispatch of

generation to meet loads in the

transmission network. The simulation

model in the example estimates market

outcomes that minimize the total cost of

generation and transmission. The

contribution of such a program to a

delivered price analysis is illustrated by

briefly describing the output

information that the model could

provide. Typical output from a program

could consist of the following:

• Generation levels. The computer

model would show the level of output

of each generator.

• Power traded. The model would

show the net quantity of power traded

between interconnected areas 4 under

economic dispatch.

• Flows on the transmission grid. The

model would show the quantity of

power flowing through each

transmission facility represented in the

model, constrained by any transmission

capacity limits that have been input to

the model. The effects of binding limits

would be reflected in model output of

generation levels and power prices.

• Prices for power. For each area, the

model would show the marginal cost of

power. This price can also be

interpreted as the market-clearing price

for the area.

II. Request for Written Comments

If a computer model were available to

produce the types of output described

above, we believe that its use could both

enhance and potentially expedite

delivered price analyses. However, the
Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices 20393

1For example, the FERC Office of Electric Power

Regulation uses a load flow program called PSLF

from General Electric that is a package of programs

handling loadflow, fault analysis, and stability

calculations.

Commission also recognizes that there

are many technical and procedural

questions that need to be addressed

concerning whether and how to use a

computer model in merger analysis. To

assist in the discussion of these issues,

the attachment presents an overview

technical discussion, followed by a list

of questions for comment. These

questions are organized into five areas:

basic model structure, alternative

implementations of the basic structure,

data issues, application of models to

merger analysis, and model

development and maintenance. All

interested persons are invited to submit

written comments (not to exceed 25

pages) on these questions and any other

issues that the Commission should be

considering with regard to computer

models and merger analysis. Comments

must be filed on or before June 14, 1998,

in Docket No. PL98–6–000. All

comments will be placed in the

Commission’s public files and will be

available for inspection or copying in

the Commission’s Public Reference

Room during normal business hours.

Comments are also accessible via the

Commission’s Records Information

Management System (RIMS).

III. Intent To Convene Technical

Conference

The Commission intends to convene

one or more technical conferences to

discuss the use of computer modeling.

We will issue a notice of conference at

a later date.

By direction of the Commission.

Linwood A. Watson, Jr.,

Acting Secretary.

Attachment: Computer Modeling and Merger

Analysis

The purpose of this attachment is to

present a sample computer model as a

starting point for discussion of issues and

questions about how such models could be

helpful in merger analysis, specifically in

reference to the Commission’s delivered

price test and potentially in other aspects of

merger analysis. This attachment is a

Commission staff paper intended to facilitate

technical discussion. Specific comments on

the sample model should be considered in

light of the questions raised at the end of this

attachment.

Background and Organization of Attachment

This Attachment discusses computer

models and their use in merger analysis. A

computer model is a computer program

designed to implement a specific

mathematical procedure. The specific

procedures discussed here are typically

called ‘‘models’’ because they are, or at least

contain, abstract representations of real

world processes. We concentrate here on two

such processes: power markets and electric

power flows over transmission networks.

Computer models hold great potential in

merger analysis because they can simulate

both market processes and the electric power

flows that results from market processes.

Computer models of electricity markets

and networks have many potential uses, but

we are primarily concerned here with how

the market simulations produced by such

models can be used in performing a delivered

price test described in the horizontal analysis

section of this NOPR. In the context of a

delivered price test, computer models—in

the sense of simulations of markets or

electricity networks—must be distinguished

from other types of computer programs. A

wide range of computer programs could be

used to automate parts of the delivered price

test. For example, a computer program could

be used to identify all generating units that

could supply a destination market at a

particular price, given the variable cost of

power at each plant, and the transmission

cost to the destination, as inputs. Such a

program would not typically be called a

model, because it does not simulate either

market interactions or electricity flows.

For purposes here, the computer models

for our consideration can be grouped into

three broad categories:

• Electricity Market Models. These models

simulate electricity production and trade

between regions, but do not attempt to

represent the underlying electricity network

in the model. Examples of such models

include the Electricity Market Model (EMM)

from the Energy Information Administration

(EIA), and the more detailed Policy Office

Electricity Model (POEMS) developed for the

Policy Office of the Department of Energy.

• Electric Power Production/Transmission

Power Flow Models. Generally, these are

detailed models that simulate electric power

generation and/or electric power

transmission, but do not attempt to represent

the market interactions or power trade

between regions. There are several models

that implement standard power flow

simulation techniques.1 Detailed production

cost models (e.g., PROMOD and GE-MAPS),

when they are designed for detailed cost

analysis of a single utility, could also be

placed in this category.

• Hybrid Models. Hybrid models combine

a market simulation component with an

electricity production and transmission

component. We know of no standard model

designed specifically for this purpose. Some

production cost models, such as GE-MAPS,

have been expanded beyond single utility

territories and used as simulations of a

competitive regional electricity market.

However, these models remain highly

detailed and may be more difficult to use for

simulating electricity market trading of

electricity over large regions than a regional

market model with a more aggregated

representation of the power transmission

network. We seek comment on currently

available models in the questions at the end

of this attachment.

For examining the competitive aspects of

mergers, hybrid models are the computer

models of interest, because both market

processes and actual power flows are

important for the analysis. To understand the

role of a computer model in the analysis, it

is essential to distinguish between the

computer model itself and its application. A

run of the computer model simulates power

generation and power transmission for a

particular scenario. The outputs from the

simulation are then applied to a particular

problem—for example, power generation and

transmission levels from the simulation

output might be used in the identification of

suppliers in a delivered price test. In this

attachment, we will restrict the use of the

term computer model to the first function—

simulating results for a particular scenario—

but also discuss how these simulation results

could be used in a delivered price test. In

addition, we seek comment on other

potential uses of a computer simulation

model in the competitive analysis of mergers.

This attachment describes one type of

computer simulation model we have been

considering and its potential use in merger

analysis. It then raises a series of questions

about the framework and examples

presented. These questions are intended to

serve as a guide for commenters and perhaps

for discussion at technical conferences on

computer modeling and merger analysis. The

Attachment is organized into five sections, as

follows:

• Overview of a modeling framework for

electric power trading over a transmission

network. This framework is presented to

facilitate a discussion of whether the

Commission should consider a computer

model for use in the analysis of mergers, and

what role a computer model, if utilized,

should play in the analysis.

• Description of a simple model

implementing the general framework,

presented both qualitatively and as a

mathematical formulation. The purpose of

this simple example is to provide a

structured starting point for technical

questions about the design and development

of a more complex simulation model for use

in merger analysis.

• Data considerations in model

implementation using currently available

public sources of data. This section discusses

the data needed for a computer model and

the availability and limitations of publicly

available data.

• Application of a computer model in

merger analysis. This section addresses the

question of how computer model simulation

runs would play a role in a delivered price

test.

• Questions for discussion at a technical

conference or conferences. These questions

extend the earlier discussion by asking

questions about the design and development

of the framework and sample model, how a

model should be used in the competitive

analysis of mergers, what data sources are

available, and how the Commission should

proceed in developing and maintaining a

model.

Overview of Model Structure

The role of computer modeling in merger

analysis can be identified by first reviewing
20394 Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices

the Commission’s delivered price test. For a

delivered price test, applicants are expected

to estimate the cost of economic transactions

to acquire power and transmit it to a

destination, and also to determine how much

power is available to be generated and

transmitted to a destination, given the

limitations on power transactions imposed

by the transmission system. For example,

given a particular destination market, an

applicant should:

• Determine an appropriate competitive

price for wholesale electric power in that

destination market that is consistent with

available information, and adequately

support the method used to determine the

price.

• Estimate the available generating

capacity and variable cost of wholesale

electric power from potential supplier

facilities at the level of individual generating

units to the extent possible.

• Estimate the cost of transmitting power

(including ancillary services) from the source

of generation to the destination, using

maximum applicable tariff rates or other

conservative estimates that can be supported.

• Make other adjustments, as appropriate,

to reflect a supplier’s competitive presence in

a destination market, and support such

adjustments with adequate analysis, data and

assumptions, and

• Evaluate the impact of transmission

system limitations on the ability of potential

suppliers to deliver power to the destination

market, using simultaneous estimates of

transmission capacity limits to the extent

possible.

These requirements help delineate a

framework for analyzing electric power

transactions over a transmission network.

This process of analysis can be made more

explicit by first constructing a general

representation of the analysis and then

incorporating this general picture in a

mathematical formulation of the economic

problem and the constraints imposed by the

physical electricity transmission system

limits. Figure 1 gives a general representation

of the problem of combining the analysis of

electric power transactions with an analysis

of the physical limitations imposed by the

electric transmission grid. The upper diagram

represents the economic network of power

transactions, that is, the production and

consumption of power in each area, as well

as trades of power between interconnected

areas. The amount of trading that occurs

among areas depends on the load

requirement of each area, on the price and

availability of power in each area, and also

on the cost of transmitting power between

the areas. The lower diagram represents the

actual physical transmission network in

which these economic transactions occur. It

would comprise primarily the transmission

lines and transformers that are called

‘‘flowgates.’’ Transactions between areas (in

the upper diagram) cause flows across these

flowgates in the physical network (in the

lower diagram). These flows are then subject

to the actual physical limits imposed by the

electric transmission network.

Most of the key elements in the Figure 1

are the same elements that would need to be

considered in a delivered price test without

a computer model. In order to explain the

structure shown in Figure 1, we explain these

common components first:

Areas. These are locations in the

transmission network where electric power is

injected by generators and withdrawn by

loads. Although in principle they can be any

part of the network for which generation and

load data are available, in practice they often

correspond to control areas. In any case, the

considerations that go into defining the

locations of generating plants and loads can

be the same, whether or not a computer

model is used to conduct a delivered price

test.

Generators. In Figure 1, the generators

located in each area are shown as supply

curves. In the model, the width of each step

on the supply curve would correspond to the

capacity of a specific generator located in an

area. The height would correspond to the

variable cost of power from that generator. To

construct a supply curve, generators may be

arranged in order of the variable cost of

generation, just as they would be for a

delivered price test without a computer

model. Supply curves can be constructed in

others ways, and we seek comment on such

alternatives.

BILLING CODE 6717–01–P
Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices 20395

BILLING CODE 6717–01–C
20396 Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices

2 Groups of lines are referred to here as

‘‘flowgates,’’ discussed further below.

3For example, in the DC flow model used by the

NERC to generate the draft PTDFs, 20 transmission

lines make up the flowgate representing the

interface between APS and PJM, 12 lines represent

the interface between APS and AEP, 3 lines make

up the interface with Ohio Edison, 3 lines make up

the interface with Duquesne and 7 the interface

with Virginia Power. In addition to tie line

flowgates, the NERC model includes 34 flowgates

representing lines internal to the APS control area.

4For purposes of the example and discussion, we

are ignoring losses.

5See Fred C. Schweppe, Michael C. Caramanis,

Richard D. Tabors and Roger E. Bohn, Spot Pricing

of Electricity, Kluwer Academic Publishers, Boston,

1988. Appendix D describes the DC Load Flow.

6NERC plans to use the iIDC to support a flowbased transmission reservation and scheduling

process and line loading relief procedures. In

response to an NERC Board of Trustees

recommendation, the Engineering Committee and

Operating Committee approved the creation of a

Transmission Reservation and Scheduling Task

Force to ‘‘develop a process for the reservation of

transmission services and scheduling of energy

transfers recognizing the actual use being made of

the Interconnection’’. The task force developed a

detailed recommendation for a flow-based

transmission service methodology (FLOBAT) based

on flowgates and PTDFs. See ‘‘Transmission

Reservation and Scheduling, Transmission

Reservation and Scheduling Task Force’’, Report to

the Board of Trustees, December 12, 1996.

Loads. Loads in Figure 1 represent

demands to be met by generating power and

transmitting it over an electricity network.

Although a computer model of power

transactions would be expected to include

more than just destination market loads

explicitly considered in setting the

destination market price, the information

sources for these loads should be the same

as the sources for a delivered price test

without a computer model.

Power Transactions/Area Interconnections.

The specification of interconnections and the

cost of transmitting power between areas

included in the analysis should be the same

with and without a computer model. In

particular, transmission prices should

represent a conservative estimate of the cost

of transmitting power (e.g., by using

maximum tariff rates).

As noted above, a computer model of

market interactions would contain more

loads than just those at a particular

destination. To be adequate, it should

represent all relevant loads that would have

a significant impact on the market for power

at a destination. This type of computer model

could then calculate the suppliers’

opportunity cost of selling power, and market

prices that reflect these opportunity costs,

because the cost of power at each destination

would be considered in the model. Although

this opportunity cost can be informally

considered as an adjustment to a supplier’s

competitive presence when doing a delivered

price test without a model, a model removes

the ambiguity in this informal consideration

by explicitly calculating the opportunity cost.

A computer model should also represent

the physical electrical network and model

the relationship between power transactions

and actual power flows and the limitations

on power transactions that must be imposed

when actual power flows approach

transmission capacity limits. These two

considerations—the relationship between

electric power trading and physical power

flows, and the effect of transmission capacity

limits—should be included in any analysis of

a merger to the extent that information is

available. One value of a simulation model

lies in incorporating both of these

considerations in the computer program,

where the needed calculations can be

performed in an efficient, standard way. The

treatment of transmission flows and limits in

the computer simulation model are discussed

in more detail below.

Estimating Transmission Flows from

Power Transactions. The model structure

presented in Figure 1 shows the link between

transactions and transmission using power

transfer distribution factors (PTDFs). As

shown in Figure 1, these factors are used to

superimpose the effect of power transactions

shown in the upper diagram on the

underlying electricity network shown in the

lower diagram of the figure. These flows may

be on individual lines or groups of lines.2

The lines represented in a computer model

may correspond to tie lines between areas,

but they may also correspond to other lines

in the transmission network that are internal

to areas and not part of an interface between

areas.3

Figure 2 shows how the PTDFs are applied.

The exchange of power between areas shown

on the left side of the figure corresponds to

the injection of power (100 MW in the

example) into the transmission grid in Area

1 and the withdrawal of the same quantity of

power in Area 2.4 Because of the nature of

the electricity flows in networks, this

exchange of power induces flows on all lines

in an interconnected grid. While a precise

estimate of the electricity flows from a

specific change can only be determined from

a complicated power flow model, the flows

can be approximated by a standard modeling

technique, known as the DC Load Flow

model.5 Distribution factors can be used to

capture the DC Load Flow estimates as

shown in Figure 2. The quantity of flows on

each line in the actual transmission network

is estimated by multiplying the quantity

exchanged by a PTDF. For example, 70 MW

of the 100 MW power (a PTDF of 0.7 times

power trade 100 MW) exchanged between

Area 1 and Area 2 flows on the lines from

Area 1 to Area 2.

The Distribution Factor Task Force of the

North American Electric Reliability Council

(NERC) estimates PTDFs for input into the

interim Interchange Distribution Calculator

(iIDC).6 A computer program for market and

merger analysis could use these PTDFs, but

other forms of distribution factors are

standardly used in DC load flow analysis.
Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices 20397

7The Eastern Interconnection is the portion of the

transmission grid that covers the eastern part of

North America, extending from the Rocky

Mountains to the Atlantic Ocean (but excluding the

Electric Reliability Council of Texas (ERCOT)).

8As discussed above (page 4), these areas would

typically be control areas. Since the sample model

is general, we drop the specific qualifer.

We seek comment on the most appropriate

source for information on distribution factors

for modeling purposes.

Transmission Capacity Limits. NERC has

compiled distribution factors for the Eastern

Interconnection 7 that relate control area

power exchanges to flow across area tie lines

and their corresponding flowgates. These

flowgates are groups of transmission facilities

that are monitored for security purposes.

Using these factors, it should be possible to

model flows at points in the transmission

system that are most likely to constrain the

economic use of the transmission grid. These

flows become important for market analysis

when any flows reach a physical limit on the

flowgate. When the limit is reached, power

must be redispatched if the destination loads

are to be met. Redispatching power means

changing which generating units produce

power, so that power generation does not

cause transmission flows to exceed the limit

on the flowgate.

The physical limit on a flowgate is not a

simple, static quantity. Flowgate limits are

set for individual elements of the

transmission network to assure they are not

operated beyond safe loading, depending

upon such cond itions as thermal limits,

generating resource availability, line outages,

loop flow, stability and voltage conditions,

and so on. Because the limits reflect system

conditions at any point in time, the limits are

dynamic and care must be exercised if single

quantities limits are used in a computer

model. These considerations about the nature

of transmission limits are not limited to the

particular example of flowgates; they apply

as well to the Total Transfer Capability (TTC)

and Available Transfer Capability (ATC)

quantities posted on OASIS. We focus here

on flowgate limits because they appear to be

the limits most directly related to the

distribution factors used to estimate network

flows. Other approaches to estimating

physical flows and associated limits are

possible; we ask questions about such

approaches in the last section of this

attachment.

NERC is developing an Interregional

Security Network (ISN) that may include data

on flowgate capacities, but these limits are

not currently available. Estimates of the

capacity limits of these flowgates are

important data for the implementation of a

model based on that network. The

availability of these limits would be of

considerable value even if a model is not

used, since they could be used to estimate

limits on transmission flows for many types

of analysis of transmission grid transactions,

including conducting delivered price test

without a model.

Specification of a Simple Model

The two main benefits of implementing the

electric power modeling framework through

a computer program are: (1) Better

representation of the market interactions, in

particular the opportunities presented to

suppliers by the presence of other loads in

addition to the loads at the destination

market and (2) better representation of the

impact that transmission limits will have on

economic transactions. In order to make the

general structure specific for use in a

computer program, the mathematical

structure of the algorithm must be described

and the data used as input to this algorithm

must be specified. As a starting point for

discussion, this section describes an

algorithm that can be implemented using

most standard mathematical programming

software packages. The algorithm is

described qualitatively and also presented as

a mathematical formulation.

The problem solved in this example is

finding the lowest cost combination of

supplies (generating plants) and power

transactions between areas, to meet fixed

demand (loads) over an electricity

transmission network, given costs for power,

charges for transmission of power within and

among areas,8 transmission loss factors, and

physical limits to moving the power over the

grid. Solving this cost minimization problem

simulates the actions of a competitive

market. Under this least cost dispatch, buyers

of power can’t make any more trades among

suppliers to lower their purchase costs. This

is the expected result in a purely competitive

market, where buyers have alternatives and

are permitted to trade among these

alternatives until they get the best value for

their money.

In the ‘‘real’’ world, conditions are more

complex than in a computer program. The

clearest differences between generation and

transmission in the computer program and

the real world are assumptions about

information (the model assumes it is perfect

and costless) and the cost of transactions (the

model assumes no costs for searching for
20398 Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices

suppliers, negotiation of trades, or costs of

interruption.) The computer model makes

any trade that can lower costs, even if it

involves large and complicated combination

of individual trades among buyers and

generators across a transmission network.

Even simple transactions are assumed to

involve only variable costs of generation and

maximum transmission rates.

While these idealizations are limitations,

some idealizations of this sort are inevitable,

and point out the need to view computer

simulation model as a tool in an overall

analysis. These issues can be addressed with

model runs where assumptions change—i.e.,

by conducting sensitivity analysis under

different scenarios. In addition, computer

program results need to be validated by

checks against other sources of market

information before making use of the outputs

from the program.

The model specified here is a basic model

that could be used to examine electric power

transactions and transmission flows. This

model is presented as a ‘‘strawman’’ point of

departure for discussion. It represents only a

single period solution of the problem, that is,

it does not attempt to address startup costs

or other multiple period effects. It also

includes some parameters as a single

constant that may need to be varied across

areas, for example, adjustments for losses.

Further, other factors would need to be

addressed through adjustment of input data

(for example, through adjustments to plant

capacities for availability in each time period

analyzed). These issues will be raised below

in the section on issues and questions for

comment. However, even without such

modifications, staff believes that this basic

model does capture important market and

transmission effects. Even the use of a simple

model, not much more complex in structure

than the model presented here, could

potentially enhance the delivered price test

and expedite the analysis of mergers, if data

are available to implement the model. In the

next section we discuss data issues related to

this implementation.

The objective of the model, the constraints

that must be met in reaching this objective,

and the model inputs and outputs are

described below. The model is stated

mathematically in Figure 3.

Model Objective. Minimize the total cost of

delivered power, calculated as the sum of

generation and transmission costs to meet a

fixed set of demands (loads) in each area,

given costs for power generation in each area

and rates to transmit the power between

interconnected areas.

Subject to constraints that satisfy:

Generation capacity requirements.

Generation does not exceed a maximum

capacity for each unit or fall below a

minimum level if one is specified.

An energy balance in each area. The sum

of generation in each area plus power

imported from other areas over the

transmission network, adjusted for losses in

generation and transmission, is equal to the

demand in each area.

Flowgate requirements. The flow across the

flowgates defining the electricity network

does not exceed the maximum flowgate

capacity or fall below the minimum flowgate

level if one is specified.

Transmission system balance

requirements. The total power injected into

the transmission system equals the total

power withdrawn from the transmission

system, adjusted for losses.

The model inputs needed to compute the

objective function and determine the

constraints are:

• The variable cost of generation at each

unit in each area.

• The capacity of each generating unit in

each area (and the minimum run level if

needed).

• The demand (load) in each area.

• The applicable transmission rate

between each pair of interconnected areas.

• Power transfer distribution factors for

each interconnection between control areas.

• Losses in generation and transmission.

• The maximum capacity of each flowgate.

BILLING CODE 6717–01–P
Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices 20399

BILLING CODE 6717–01–C
20400 Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices

10This is the only data element required for the

sample model that would not be needed without it.

However, a more complex model might impose

additional data requirements. These additional

requirements are addressed in the last section of

this attachment on questions for a technical

conference.

This information is used to determine the

generation levels and transmission

interchange between control areas that

minimizes the sum of generation costs and

transmission charges as specified above in

the objective function. The key outputs from

this algorithm are:

• Power production at each generating unit

in each control area.

• Net power interchange between areas.

• Power flowing on each flowgate.

• Marginal cost of power in each area.

Implementing the Basic Model: Data

Considerations

In principle, the sample algorithm in the

last section could be implemented at a high

level of detail, where areas were

geographically small, for example, at a level

of detail below a utility service territory. This

level of detail could approach the level of

detail used in detailed power flow and

transmission system analysis. In practice,

data limitations may make a such a detailed

model generally impractical as a screening

tool for merger analysis (although in specific

cases, more detail can be developed as

needed). A reasonable starting point for data

considerations is the information currently

required to conduct a delivered price test. As

discussed above, one would expect many of

the sources of information used for computer

modeling to be the same as the sources for

the non-model application of the delivered

price test. Variable generation costs and

capacities by area, area demands,

interconnections between areas, transmission

tariff rates could be the same in both

analyses. A computer model would need data

on a larger geographic area than a delivered

price test for a single destination. However,

most of the publicly available sources are not

limited to single regions, but provide

nationwide coverage. Sometimes this

coverage is limited to a particular class of

market participants—e.g., Investor-Owned

Utilities (IOUs), Municipal utilities, etc.

However, it is generally possible to compile

nationwide data on the key variables needed

in the analysis; consequently, data for the

larger geographic areas that may be required

for a computer model should be generally

available and relatively easy to incorporate in

the analysis.

The availability and format of data

circumscribe the ways in which key variables

in a model can be defined. For parameters

that are common to calculations with or

without a model the issues of definition are

the same in either type of analysis. As an

example, consider the question of what areas

to use in an analysis. Answers to this

question depend on how data are reported

geographically, as follows:

• Generator locations can be assigned to

specific geographic locations within control

areas.

• Tariffs are filed by utility areas (or

sometimes for a single holding company such

as Southern Company).

• For load scheduling purposes,

interconnections are most naturally defined

by control area, and Form 714 data are

reported on that basis.

• System lambda data are filed on a

control area basis.

• Historical loads are most easily derived

from the Form 714 filings which are reported

on a planning area basis.

These data limitations suggest that areas

for modeling purposes might be defined by

combining control and planning areas. This

definition would permit a modeling analysis

to consider different time periods defined on

the basis of hourly load data, and to estimate

the system lambda corresponding to the load

data on a basis that is consistent with the

requirements for a delivered price test

without a model. Staff seeks comment on this

and related issues below.

PTDFs are needed in the model specified

in the previous section, but would not be

needed if the merger analysis did not use a

computer model.10 Recall that PTDFs relate

power exchanges between areas to flows

across flowgates. The sample model assumes

that the areas in the model are the same ones

used to define PTDFs. Although PTDFs are

not needed in an analysis that does not use

a computer model, they are nevertheless a

valuable piece of information for any analysis

that needs to examine the implications of

loop flow and transmission limits.

Transmission limits are also important data

inputs to the computer model. As discussed

above, flowgate limits have not yet been

defined for the flowgates identified in the

NERC data on PTDFs. The best currently

available information for estimating limits

appears to be OASIS values for Total Transfer

Capability (TTC) and Available Transfer

Capability (ATC), and transmission

capacities reported in various NERC studies

and other systems assessments. Since these

are the same sources that are needed for a

delivered price test analysis, the model does

not impose additional data requirements

beyond those of the delivered price test. One

caveat may be noteworthy, however. A

computer model may be more sensitive to

data limitations, because the model

automatically enforces the transmission

system limits on electricity trade. This

automatic nature of the computer model is a

great benefit if consistent and accurate data

are available, because the model can

automatically capture the effects of trade

across an interconnected electricity grid.

However, this characteristic of a computer

model can also make results more sensitive

to data imperfections than an analysis relying

more directly on the analyst’s judgment, and

suggests that analysts should conduct studies

to determine the sensitivity of market

simulations results to a range of transmission

limits.

Finally, a computer model simulation is a

valuable tool for examining the consistency

of the data used in the analysis. The model

uses all the same information used in the

current delivered price analyses for the key

parameters: generation costs and capacities,

transmission tariffs and limits, and

destination market loads. From this

information, the computer model simulates

generation levels, generation costs, control

area prices, and transmission flows between

areas. It should be possible to reconcile these

simulation results with corresponding

reported information. For example, the

simulation results (such as control area

prices and the costs the marginal generator)

should be consistent with reported values for

system lambda. Inconsistencies may indicate

deficiencies in either the model or the

information sources, or both, and large

inconsistencies need to be understood before

proceeding with the analysis. This is

particularly important for system lambda

data, since the system lambda data may be

used to set the destination market prices. If

estimated prices from a simulation are not

consistent with system lambda data, the cost

information used in a delivered price test

(such as the generation costs reported on

Form 1) may not be consistent with the

destination market prices. Since

inconsistencies between estimated and

reported values can also arise because of the

limitations of the model itself, however,

some degree of inconsistency may be

inevitable. However, the model would still

provide a valuable tool for linking the

different sources of information used for the

delivered price test and potentially

corroborating the system lambda data as a

destination market price indicator. As

experience is gained in calibrating a model

with other sources of information on prices

and generation levels, judgments of what

destination market prices to use in an

analysis should improve.

Applying a Computer Model to Merger

Analysis

The discussion has not yet considered the

role of a computer model in a delivered price

test. It is important to distinguish between

the computer model itself and use of the

output of the model for merger analysis and

the delivered price test. A model simulates

generation and power flows in the

transmission network based on economic and

electrical engineering principles. It is then

applied to a particular analysis as defined by

a particular procedure. Using a model as a

tool in this way does not alter the basic

objectives or principles underlying the

delivered price test.

To assist the discussion of applying the

model to a delivered price test, we divide

this section into three parts, as follows:

• A Delivered Price Test Without a Model.

The delivered price test is not intended to be

applied in a rigid, inflexible manner.

Accordingly, staff has tailored the basic steps

described here to fit the circumstances in

each case.

• Model Outputs Relevant to the Delivered

Price Test. This part briefly reviews

computer modeling methods and results that

are important in the delivered price test.

These features are described without

reference to technical details of model design

and data discussed in previous sections.

• A Delivered Price Test With a Model. A

delivered price test with a model will follow

the same basic pattern, but details of the

procedure will change. This section describes

where the model would fit in the context of

a typical DPT application.
Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices 20401

11For example, the Rural Utility Service Form

RUS–12 provides information on generators owned

by cooperatives, and the Energy Information

Administration Form EIA–412 provides information

on municipals.

Staff’s Framework for a Delivered Price Test

Without a Model

The competitive screen analysis focuses on

one aspect of merger analysis: whether the

merger would significantly increase

concentration. The four steps in the

competitive screen analysis are:

• Identify relevant products.

• Identify affected customers.

• Identify potential suppliers to affected

customers.

• Analyze effect on concentration.

For purposes of comparing a delivered

price test with and without a computer

model, the key step is the identification of

suppliers in the market. This step will be

described in detail, but other steps will be

also be briefly described for completeness.

These descriptions are not meant as a fixed

prescription, and we do not mean to imply

that there is a single way to conduct a

delivered price test. Rather, they describe a

set of choices we have found appropriate in

previous cases. These choices are guidelines

that staff believes can be improved upon as

analysis evolves. Their purpose is to distill

experience and provide reasonable common

ground as guidance, without restricting

innovation in future applications.

Identify Relevant Products. Although other

products can be appropriate, the relevant

product for the delivered price test has

typically been short-term energy. Short-term

energy has been further differentiated by time

period. For most purposes, staff has divided

time periods into nine time categories,

defined by season and hourly load

conditions: winter, summer and spring/fall

seasons, with peak, shoulder and off-peak

periods being identified for each season.

Short-term energy is then analyzed as a

separate relevant product for each of the

temporal categories.

Identify Affected Customers. Customers

have generally been identified based on the

facts of each case, the Applicants’ filing, and

analyses filed by intervenors. The result has

been the identification of destination markets

with higher probabilities of negative effects.

Each destination markets has been analyzed

separately for each time period.

Identify Suppliers to Affected Customers.

Identifying suppliers to each destination

market in each time period involves several

choices and related calculations. The

identification starts with a decision on how

to limit the total group of suppliers included;

that is, with how many ‘‘wheels’’ away a

supplier must be in order to be excluded

from consideration. Generally, three wheels

has been deemed adequate, but no rigid

number of wheels can be determined a priori,

so the boundaries need to be fitted to the

facts of each case. The main remaining

components in supplier identification are:

• Competitive price in the destination

market.

• Generation costs and capacities.

• Transmission prices and transmission

system capability.

• ‘‘Native’’ loads.

A general summary how each of these

components has been included in the

delivered price test is given below.

Competitive price in the destination

market. The destination market system

lambda provides a default indicator that can

be calculated for each of the time periods

considered. However, differences in methods

underlying the system lambda and well as

differences in reporting (such as inclusion or

exclusion of purchases) mean that system

lambda data should to be compared with

other indicators such as published spot

prices for consistency. One approach to the

problem of uncertainty in any estimate of the

competitive price is to analyze concentration

for different price levels, in order to

determine how sensitive the concentration

results are over a plausible range of prices.

Generation costs and capacities. The

primary source of information for the

capacity and variable cost of generation has

been the FERC Form 1 and related forms.11

These data are available for individual

generating plants, but do not provide

information on specific units when there are

multiple units at a plant. However, it does

provide information by prime mover type

(e.g., fossil steam, internal combustion) and

type of fuel. For purposes of variable cost

estimation, this level of detail is a reasonable

approximation to unit level information in

most cases.

Generation capacity is adjusted for

availability, based on estimates of planned

and forced outages. Planned and forced

outage rates should be based on historical

outages, and varied at least by fuel type. If

more detailed data are not available on the

temporal patterns of outages, outage rates

should be applied to represent typical

patterns. For example, forced outages are

applied equally to all time periods, unless

another allocation can be supported. Planned

outages are assigned to spring/fall where they

would be most expected, except where more

explicit scheduling patterns can be

supported.

Transmission prices. In general, staff has

used firm ceiling rates from open access

tariffs. Generally, the maximum applicable

hourly rate, in $/MWh, is used. In cases

where discounted rates a generally available

and posted on OASIS, these discounted rates

are used.

Transmission rate structures are

undergoing changes, so no single approach is

always the best one to use. Where new rate

structures have been adopted, the new rate

structure should be used. For example,

MAPP rates are distance-based, and these

current regional rates are used for

transmission analysis involving MAPP

companies.

In order to determine the transmission

costs for a supplier to reach a destination

market, it is necessary to trace a ‘‘contract

path’’ between the supplier and the

destination market. The basic information

source for identifying the individual

companies in these interconnections has

been the FERC Form 714. Where there are

multiple paths between the supplier and the

destination, staff has chosen to assign

suppliers to the path with the lowest

transmission cost.

Transmission capacity. There are two

different publicly available sources that can

be used to estimate transmission capacity:

NERC Regional Reliability Council

transmission assessment studies and OASIS

reports of Total Transfer Capability (TTC)

and Available Transfer Capability (ATC).

Staff has used both of these sources, but the

specific uses have been based on the

strengths and weakness of each source. NERC

data provide better supporting detail and can

be used for estimation of simultaneous

transmission capabilities. However, NERC

reports generally report simultaneous

transmission capability at the regional or subregional level, not at the more detailed

geographic area reported on OASIS. OASIS

data provide a desirable level of detail (the

control area and some sub-control-area

detail), but the reporting is not generally on

a simultaneous basis and reporting has not

fully matured. For example, different OASIS

sites report differing TTC/ATC capacities

between areas over the same path. Therefore,

OASIS data, while detailed, need to be

reviewed closely for use in estimating

transmission capacity in the delivered price

test.

The total generation capacity on a

particular path from a supplying area to the

destination market is determined by the

suppliers assigned to that path. When the

available transmission capacity on a path is

less than the total generation capacity

assigned to the path, it is necessary to

allocate capacity to the suppliers comprising

the path. The merger policy statement does

not endorse any particular method for

making this allocation, but the two

approaches used by staff are to reduce each

supplier’s capacity pro rata and to select

suppliers in order of generation cost.

Native load estimation. When the measure

of capacity used is available economic

capacity, an estimate of native load in each

area is needed. This estimate is used to

reduce the generation capacity available for

sales to the destination markets that are being

analyzed. For this purpose, FERC Form 714

data on hourly loads can be used to estimate

the load in each time period. Because these

data are reported on the basis of ‘‘planning

areas’’, some adjustments to these data are

necessary for use in estimating native load by

control area.

Analyze effect on concentration. The final

step in the analysis is to examine the preand post-merger concentrations and compare

them to the appropriate thresholds. These

concentrations are based on the estimated

supplier shares from the supplier

identification step, for pre-and post-merger

combinations of the following cases:

• Products—short term energy.

• Periods—nine periods by season and

load conditions.

• Capacity measure—economic capacity

(supplier capacity deliverable at 105% of the

competitive price) and available economic

capacity (subtracting native load from a

supplier’s economic capacity).

Model Outputs Relevant to the Delivered

Price Test

The steps in supplier identification

described above could be conducted using a
20402 Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices

computer program that uses information on

generation costs and capacities, transmission

costs and capacities, and other inputs. Such

a program would provide a list of suppliers

and capacities making up the supply to each

market. Without a computer model of the

market and transmission grid, these programs

cannot take into account certain factors that

are important in determining what suppliers

can deliver power economically to a

particular destination. The two main factors

not accounted for are:

• Interactions between suppliers and

loads. In a competitive environment,

decisions about which suppliers will serve

which loads will be driven by opportunity

costs, in particular the opportunity cost to

suppliers of serving one load rather than

another. Because there can be many possible

combinations of supplies and loads, some

form of computer model could be helpful in

estimating such combinations.

• Transmission flows from exchanges of

power between areas. Because of the

properties of electricity, exchanges of power

between areas affect flows throughout the

transmission grid. Any approximation of

these effects may require a computer model

to make the many calculations needed to

estimate electric power flows.

Developing and using a computer model

involves a number of choices about the

structure of the model, the level of detail, the

sources of information, and other issues.

These issues are discussed elsewhere in this

attachment. The main question to raised here

is what information the computer program

provides to the analyst. Once this question is

answered, the discussion turns to the

question of how that information can be used

in a delivered price test.

For purposes of this discussion, the

computer program is assumed to be a simple

representation of dispatch of generators to

meet a fixed set of loads in a single time

period. The program is assumed to simulate

the economic dispatch of power over an

electric transmission network, by finding the

dispatch of generators and exchanges of

power between areas that gives the lowest

total cost of producing and transmitting the

power. Output from this computer program

would include generation levels, the quantity

of power exchanged between areas, flows on

the transmission grid, and the marginal cost

of power in each area. Each of these

computer model outputs is described briefly

below:

• Generation levels. For each generating

unit, the computer model estimates the level

of output of each generator. It does not

estimate which generator sells to which load,

but only how much power is generated by

each generator when dispatch of that power

is at least overall cost.

• Power exchanged. For each pair of

interconnected areas, the model gives the net

quantity of power exchanged between the

areas under economic dispatch.

• Flows on the transmission grid. For each

of the transmission facilities represented in

the model, the model outputs the quantity of

power flowing through that facility. These

flows will be limited by any transmission

capacity limits that have been input to the

model.

• Marginal costs for power. For each area,

the model would find the marginal cost of

power under economic dispatch. For

purposes of this analysis, this cost can be

interpreted as the market clearing price for

the area.

These model outputs can be used to apply

the model in a delivered price analysis. This

application is discussed in the next section.

A Delivered Price Test With a Model

One use of a computer model is to use it

in a delivered price test analysis. A computer

model would be used only in the supplier

identification step. The model could be

helpful in two parts of this analysis:

determining the destination market price and

identifying the suppliers that can deliver to

each destination market. The role of a

computer model in each of these steps is

described below:

• Determine destination market price. The

default approach to market price

determination would still be the system

lambda data. However, a computer model

could be used here to help corroborate the

price used for the destination. As discussed

above (p. 14), a computer model could be

used to simulate a destination market price

for the loads in each time period. This

simulated price would not be a substitute for

a price estimated from system lambda data,

but could be an additional factor in

determining how to establish the price and

whether to examine a range of market prices

rather than a single estimate.

• Identify suppliers to the destination

market. A computer model could be used to

determine what suppliers could deliver to

the destination market. It could simulate the

supplier identification procedure of the

delivered price test. In the delivered price

test, suppliers are considered in the market

as long as they can deliver to the destination

market at a price less than or equal to a

threshold price equal to 5% above the

destination market price. A computer model

could simulate the same test by considering

only the load in the destination market (i.e.,

assuming all other loads to be zero). Under

these conditions, the computer model would

be run with increasing destination market

demand until the market price reached

threshold price. All suppliers running at this

price would be identified as supplying the

destination market.

In addition to these steps, adjustments to

supplier capacity that can be delivered to a

destination may be appropriate. One possible

adjustment could be to consider other

destinations that provide selling

opportunities for suppliers and the

likelihood that supplier’s opportunities may

alter their capacity available for delivery to

a particular destination market. A computer

model is one tool that could be used to assess

the effect of these alternatives in a delivered

price test. Staff seeks comments on whether

these types of adjustment may be appropriate

in a delivered price test and how a model

could be used for this purpose.

Finally, computer models hold additional

potential for application in other areas of the

competitive analysis of mergers. In the next

section, staff seeks comment on these and

other issues.

Issues/Questions for a Technical Conference

Below are questions for comment and

perhaps also discussion at a technical

conference. Commentors should also raise

any other issues they believe need to be

considered. In considering these questions or

in raising further issues, it is important to

specify whether the model is intended

primarily as a screening tool or as a detailed

and full analytical tool. In the former case the

model must therefore strike a balance

between detail (with the presumption of

greater accuracy and precision) and ease of

application within the requirements for a

screen.

Questions are listed in five groups: basic

model structure, implementing the basic

structure, data issues, application to merger

analysis and process issues.

Basic Model Structure

The sample model assumes the general

form of a mathematical programming

problem. Is this the most appropriate

technique to simulate economic equilibrium

problems in the electricity market? Please be

explicit about any proposed alternatives.

The sample model is structured as a linear

program. Would another mathematical

programming form be better (for example, a

quadratic program with piecewise linear

supply curves)?

Demands are assumed to be fixed in the

sample program, so the demand side of the

market is not represented in the sample

model. Should demands be made responsive

to price? If so, what is the appropriate price

elasticity? Should the objective function then

be to maximize social welfare (the sum of

producer plus consumer surplus)?

The sample model uses distribution factors

to estimate power transmission flows. Is this

approach adequate? Should Commission staff

rely on transmission distribution factors

supplied by others (either NERC or another

third party) or perform its own transmission

system analysis to derive distribution factors

for market analysis?

In the sample model, the generator cost

functions are represented as a constant

variable cost for a unit, even though unit

efficiencies vary over the operating range of

a generating unit. Is a formulation with a

constant variable cost sufficient for purposes

of a screening model? Are there alternative

formulations of the cost function that can be

easily implemented with available

information?

How should generating unit availabilities

and losses be represented in the model?

Could availabilities be treated outside the

model, as adjustments to available capacity

for each time period studied? Should losses

be represented only for transmission flows,

or for all generation and transmission, and

should different loss factors be supplied for

each area? Should losses associated with

generation or load within each area be treated

differently from losses associated with

transmission exchanges or flows across

areas? Should losses be transaction based or

flow based?

How should generation and transmission

reserve requirements be modeled? How

should transmission reserve margin (TRM)

and capacity benefit margin (CBM) be used?
Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices 20403

What additional adjustments are required to

account for generation operating reserves,

generation planning reserves, or transmission

reserves?

Are there other operating conditions that

would need to be represented in a model for

screening purposes? For example, would a

model need to represent operating costs for

startup or ramping in order to capture

whether particular unit might be available to

respond to price increases? Are there any

special design considerations for hydropower

that need to be incorporated in the model,

and how can these best be added?

Alternative Implementation of Basic Model

Is a geographic level of detail

corresponding to control areas the best level

of detail for purposes of a screening model?

If a greater level of detail is necessary, please

explain how this detail can be represented

with public sources of data or how it can be

made part of the filing requirements. Also

explain how a more complex analysis with

a detailed model could be conducted within

the time requirements of a screening analysis.

If geographic areas larger than control areas

are recommended, please explain how the

approach could adequately capture

competitive issues required in a merger

screen.

The model represents transactions between

control areas. Transactions between control

areas follow a contract path and pay for each

control area transfer between source and

destination. As rate structures change and

power pools evolve, these rate structures will

also change. What design elements should be

incorporated to ensure that the model is

sufficiently flexible to accommodate these

evolving structures?

How should firm sales and contracts be

represented in the modeling structure? For

example, should generation capacity be

reassigned from the selling region to the

purchasing region? If capacity is reassigned,

which generating units should be associated

with the reassignment? Should the

transmission capacity be made unavailable

for both scheduling and use, that is, should

it be assumed that the purchaser is obligated

to use the power rather than resell it, so

capacity will be used and not available for

short-term trading in the model?

The model can simulate a market

(minimize costs) over any arbitrary area for

which data are available. Should the overall

area be broad, for example, the Eastern

Interconnection, or should it be limited to a

smaller area surrounding the parties to a

merger? Discuss how trade with areas outside

the area represented in the model should be

analyzed and incorporated in the model.

Should different modeling structures be

used to simulate the different characteristics

of power trading and power flows for

different regions? For example, is the sample

model considered equally applicable to the

analysis of the Eastern Interconnection and

WSCC? If not, what key differences between

regions should be reflected in the structure

of the model, and how should they be

represented?

Data Issues

Are there alternatives to using FERC Form

1 data (and data from related public sources)

for generator costs and capacities that

provide comparable geographic and company

coverage?

What are the best data for estimating the

fuel cost component of variable cost? Should

historical costs, such as those reported on

Form 1 be used? Or should other estimates,

such as spot prices, be used? If a single heat

rate is used for each unit to convert fuel costs

to a cost per unit of electricity, should that

heat rate be taken from Form 1? Or are other

heat rates, such as those filed by unit on the

Energy Information Administration Form

860, a better estimator of the cost of power

from the unit?

Should variable cost include non-fuel

operating and maintenance costs? What

components should make up non-fuel

operating costs? Can these costs be estimated

from Form 1 data with sufficient accuracy for

a model? If they can, what methods should

be used for estimating these costs from Form

1 data? If they cannot be estimated from

Form 1 costs, what sources of information

should be used in their estimation?

Should NERC PTDFs and flowgate limits

(if available) be used? What are the strengths

and weaknesses of using the NERC PTDFs

and flowgate limits? If flowgate limits

associated with NERC-calculated PTDFs are

available, can they be used in the way they

are represented in the sample model

discussed in this attachment? If they should

be incorporated in a model using an

approach that is different from the one

described in this attachment, what should

that approach be?

If NERC flowgate limits are unavailable, is

the approach of using PTDFs and flowgate

limits to represent the physical network still

practical? If the PTDF approach is practical

in the absence of flowgate limits provided

from NERC, how should other sources of

transmission limit information (such as

OASIS TTC or ATC data or system reliability

studies) be used to estimate flowgate limits?

If the PTDF approach is not practical, how

should actual power flows and transmission

limits be modeled?

Environmental factors can influence the

variable cost of operating plants. For

example, the variable cost of operating coal

plants is affected by the cost of SO2

allowances, and environmental programs in

California and the Northeast could have a

significant impact on costs. Are these costs

adequately captured by publicly available

sources, such as the reported costs on Form

1, or do they require separate cost

estimation?

Application to Merger Analysis

Can the model be straightforwardly applied

to simulate the supplier identification step of

a delivered price test that is consistent with

a delivered price test performed without a

model? First, consider the delivered price

test as it is described and applied currently,

without adjustments to supplier capacity.

Then consider how a model might be used

to adjust supplier capacity for the presence

of loads at other destination markets, and

how such adjustment could be made in a

manner consistent with the purposes of the

delivered price test.

In addition to using a model in a delivered

price analysis, what are the other areas of

market definition or of the analysis of the

competitive effects of mergers where a

computer model could be used? Comments

may address the general use of computer

models in antitrust analysis, such as their use

in a hypothetical monopolist test or their use

in simulating dominant firm behavior.

However, comments should address how

these applications might function as a

screening tool and in the Policy Statement.

In your comments, specify what these areas

of application are and what benefits are

provided by using the model, how the model

would be used in the analysis (in as much

detail as possible), and how use of the model

can be made consistent with the practical

constraints of time and resources available in

the screening context.

Process of Model Development and

Maintenance

The staff believes that a computer model

can be a feasible part of a horizontal screen,

and will aid the analysis. The model may

also have the potential to expedite the

analysis by providing agreed-upon standard

methods that can be applied in merger

analysis. Are these beliefs sound, or are there

limitations in principle or practice that make

the use of models infeasible as part of a

horizontal merger screen?

What should the Commission require with

respect to computer modeling in merger

analysis? Should it endorse a specific

computer model, a particular modeling

approach (such as an economic dispatch

model), or only a general framework? Or

should it only seek to provide guidance on

how a model should be used if applicants

choose to include one in their application?

Are there existing models that meet the

requirements for use in a horizontal screen?

Explain how any candidate model could be

used by staff, applicants and/or intervenors

in the context of a merger application?

Address issues of technical adequacy,

practical issues such as complexity and ease

of use, and procedural issues such as the

proprietary nature of third-party commercial

software products. If there are other existing

models, should the Commission staff acquire

a existing model, or should Commission staff

develop a model for its own use and the use

of applicants and intervenors?

If the Commission staff were to develop a

model rather than acquire an already existing

model, what development approach should

be taken? Should the model be developed by

Commission staff based on technical

discussion and input from industry, by

industry groups with Commission oversight,

or some other way? If the Commission

adopted the approach of issuing guidelines

only, but not developing a single model for

general use by staff and applicants, would

independent development of models by

others provide models of sufficient quality

and standardization for merger analysis

purposes?

How should a model be tested prior to use

in specific merger cases? If a model has been

used in other contexts, under what

conditions should that use be regarded as

sufficient to validate its use as part of a

horizontal screen analysis? If the

Commission staff were to develop or adopt a
20404 Federal Register / Vol. 63, No. 79 / Friday, April 24, 1998 / Notices

new model for use in merger analysis, how

should it be tested to ensure that the design

criteria have been met?

How should a model and associated

databases be maintained and updated? What

process should be followed to identify

needed modifications to the model and create

new versions of the computer code? Should

a fixed set of data inputs be identified, in

order to avoid this potential difficulty and

provide consistent a starting point for

analysis (assuming applicants can file

additional data for further analyses if they

choose)? As an alternative, should applicants

be permitted to substitute the most recent

data from the same sources even if these data

have not previously tested in the model? Or

should a standard set of model inputs be

maintained and updated as a group? If a

standard set of inputs is maintained, should

Commission staff be directly responsible for

the maintenance of these data or can this

responsibility be carried out by third parties?

[FR Doc. 98–10687 Filed 4–23–98; 8:45 am]

BILLING CODE 6717–01–P

ENVIRONMENTAL PROTECTION

AGENCY

[ER–FRL–5491–2]

Environmental Impact Statements and

Regulations; Availability of EPA

Comments

Availability of EPA comments

prepared April 06, 1998 Through April

10, 1998 pursuant to the Environmental

Review Process (ERP), under Section

309 of the Clean Air Act and Section

102(2)(c) of the National Environmental

Policy Act as amended. Requests for

copies of EPA comments can be directed

to the OFFICE OF FEDERAL

ACTIVITIES AT (202) 564–7167.

An explanation of the ratings assigned

to draft environmental impact

statements (EISs) was published in FR

dated April 11, 1998 (62 FR 16154).

Draft EISs

ERP No. D–AFS–L67036–OR Rating

EO2, Nicore Mining Project,

Implementation, Plan-of-Operations,

Mining of Four Sites, Road

Construction, Reconstruction, Hauling

and Stockpiling of Ore, Rough and

Ready Creek Watershed, Illinois Valley

Ranger District, Siskiyou National

Forest, Medford District, Josephine

County, OR.

Summary: EPA expressed

environmental objections based on lack

of information or alternatives, the

potential cumulative impacts of

additional mine patents in the area, a

failure to meet the intent of the Aquatic

Conservation Strategy in the President’s

Forest Plan, a lack of a detailed

reclamation plan, a lack of a monitoring

plan and potential sediment impacts to

Rough and Ready Creek.

ERP No. DR–BLM–K67040–CA Rating

EO2, Imperial Project, Open-Pit

Precious Metal Mining Operation

Utilizing Heap Leach Processes, Plan of

Operations, Right-of-Way, Conditional

Use Permit, US COE Permit and

Reclamation Plan Approvals, El Centro

Resource Area, California Area District,

Imperial County, CA.

Summary: EPA expressed

environmental objections based on

potential significant environmental

degradation to waters of the United

States, and requested additional

alternatives analyses and data. EPA also

expressed serious concerns that the

project could interfere with basic rights

of Native Americans to practice their

religious beliefs, and asked BLM to

provide information on its policies,

guidelines and standards with respect to

this issue.

Final EISs

ERP No. F–AFS–J65251–CO Arapaho

and Roosevelt National Forests and

Pawnee National Grassland,

Implementation, Land and Resource

Management Plan, Boulder, Clear Creek,

Gilpin, Grand, Larimer and Weld

Counties, CO.

Summary: EPA review finds the

alternative selected in the FEIS to be

responsive to the Forests and Grasslands

need and to environmental

considerations for Plan Implementation.

ERP No. F–AFS–J65276–CO Dome

Peak Timber Sale, Timber Harvesting

and Road Construction, White River

National Forest, Eagle Ranger District,

Glenwood Spring, Eagle and Garfield

Counties, CO.

Summary: EPA review has not

identified any potential environmental

impacts.

ERP No. F–COE–G39031–LA

Mississippi River—Gulf Outlet (MRGO)

New Lock and Connecting Channels

Replacement and Construction for

Connection to the Mississippi River,

Implementation, Orleans and St.

Bernard Parishes, LA.

Summary: EPA expressed lack of

objections to the recommend plan and

have no other comments to offer.

ERP No. F–NPS–K61144–HI Ala

Kahakai ‘‘Trail By the Sea’’ National

Trail Study, Implementation, Hawaii

Island, Hawaii County, HI.

Summary: Review of the Final was

not deemed necessary. No formal

comment letter was sent to the

preparing agency.

ERP No. FS–NOA–K90025–CA

Monterey Bay National Marine

Sanctuary Management Plan, Updated

Information, To Amend the Designation

Document and Regulations to Allow

Jade Collecting in the Sanctuary, San

Mateo, Santa Cruz and Monterey

Counties, CA.

Summary: Review of the Final EIS

was not deemed necessary. No formal

comment letter was sent to the

preparing agency.

Dated: April 21, 1998.

William D. Dickerson,

Director, NEPA Compliance Division, Office

of Federal Activities.

[FR Doc. 98–10990 Filed 4–23–98; 8:45 am]

BILLING CODE 6560–50–U

ENVIRONMENTAL PROTECTION

AGENCY

[ER–FRL–5491–1]

Environmental Impact Statements;

Notice of Availability

Responsible Agency: Office of Federal

Activities, General Information (202)

564–7167 OR (202) 564–7153.

Weekly receipt of Environmental

Impact Statements Filed April 13, 1998

Through April 17, 1998 Pursuant to 40

CFR 1506.9.

EIS No. 980122, Draft Supplement, COE,

DE, Delaware Coast from Cape

Henlopen to Fenwick Island

Feasbility Study and Bethany Beach

and South Bethany Interim Feasbility

Study, Additional Information, Storm

Damage Reduction and Construct a

Protective Berm and Dune, Sussex

County, DE, Due: June 08, 1998,

Contact: Steve Allen (215) 656–6559.

EIS No. 980128, Draft EIS, BLM, WY,

Newcastle Resource Management

Plan, Implementation, Updated

Information, Evaluates Alternatives

for the Use Public and Federal Lands

and Resources in Portions of

Wyoming, Crook, Niobrara and

Weston Counties, WY, Due: July 23,

1998, Contact: Floyd Ewing (307)

746–4453.

EIS No. 980129, Final EIS, FHW, TN,

I–40 Reconstruction, I–40/I–240

Directional (Midtown) Interchange to

TN–300 Interchange, Funding and

Possible COE 404 Permit, Shelby

County, TN, Due: May 26, 1998,

Contact: James E. Scapellato (615)

736–5394.

EIS No. 980130, Final EIS, AFS, CO,

South Quartzite Timber Sale, Timber

Harvesting and Road Construction,

White River National Forest, Rifle

Ranger District, Grizzly Creek Rare II

Area, Garfield County, CO, Due: May

26, 1998, Contact: David T. Van

Norman (970) 927–5715.

EIS No. 980131, Final EIS, AFS, CA,

Emigrant Wilderness Management