[Federal Register: April 24, 1998 (Volume 63, Number 79)]
[Notices]               
[Page 20392-20404]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr24ap98-53]

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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.<SUP>1</SUP>
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    \1\ Inquiry Concerning the Commission's Merger Policy Under the 
Federal Power Act: Policy Statement, Order No. 592, FERC Stats. & 
Regs. para. 31,044 (1996), order on reconsideration, 78 FERC para. 
61,321 (1997) (Policy Statement).
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    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.<SUP>2</SUP>
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    \2\ Appendix to DOJ Merger NOI Comments at A-11, n12.
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    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''.<SUP>3</SUP>
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    \3\ Wisconsin Electric Power Company, et al. (Primergy), 79 FERC 
para. 61,158 at 61,694 (1997).
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    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:
    <bullet> Generation levels. The computer model would show the level 
of output of each generator.
    <bullet> Power traded. The model would show the net quantity of 
power traded between interconnected areas <SUP>4</SUP> under economic 
dispatch.
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    \4\ Typically, the interconnected areas would be control or 
planning areas, but the exact geographic area would depend on how 
the model was implemented.
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    <bullet> 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.
    <bullet> 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

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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:
    <bullet> 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.
    <bullet> 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.<SUP>1</SUP> 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.
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    \1\ For 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.
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    <bullet> 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:
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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

[[Page 20394]]

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:
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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
    <bullet> 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.

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[GRAPHIC] [TIFF OMITTED] TN24AP98.000



BILLING CODE 6717-01-C

[[Page 20396]]

    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\
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    \2\ Groups of lines are referred to here as ``flowgates,'' 
discussed further below.
    \3\ For 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.
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    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.<SUP>4</SUP> 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.<SUP>5</SUP> 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.
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    \4\ For purposes of the example and discussion, we are ignoring 
losses.
    \5\ See 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.
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    The Distribution Factor Task Force of the North American 
Electric Reliability Council (NERC) estimates PTDFs for input into 
the interim Interchange Distribution Calculator (iIDC).<SUP>6</SUP> 
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.
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    \6\ NERC plans to use the iIDC to support a flow-based 
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.


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    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 <SUP>7</SUP> 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.
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    \7\ The 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)).
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    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,<SUP>8</SUP> 
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.
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    \8\ As discussed above (page 4), these areas would typically be 
control areas. Since the sample model is general, we drop the 
specific qualifer.
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    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

[[Page 20398]]

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:
    <bullet> The variable cost of generation at each unit in each 
area.
    <bullet> The capacity of each generating unit in each area (and 
the minimum run level if needed).
    <bullet> The demand (load) in each area.
    <bullet> The applicable transmission rate between each pair of 
interconnected areas.
    <bullet> Power transfer distribution factors for each 
interconnection between control areas.
    <bullet> Losses in generation and transmission.
    <bullet> The maximum capacity of each flowgate.

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    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:
    <bullet> Power production at each generating unit in each 
control area.
    <bullet> Net power interchange between areas.
    <bullet> Power flowing on each flowgate.
    <bullet> 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:
    <bullet> Generator locations can be assigned to specific 
geographic locations within control areas.
    <bullet> Tariffs are filed by utility areas (or sometimes for a 
single holding company such as Southern Company).
    <bullet> For load scheduling purposes, interconnections are most 
naturally defined by control area, and Form 714 data are reported on 
that basis.
    <bullet> System lambda data are filed on a control area basis.
    <bullet> 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.<SUP>10</SUP> 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.
---------------------------------------------------------------------------

    \10\ This 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.
---------------------------------------------------------------------------

    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:
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.

[[Page 20401]]

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:
    <bullet> Identify relevant products.
    <bullet> Identify affected customers.
    <bullet> Identify potential suppliers to affected customers.
    <bullet> 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:
    <bullet> Competitive price in the destination market.
    <bullet> Generation costs and capacities.
    <bullet> Transmission prices and transmission system capability.
    <bullet> ``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.<SUP>11</SUP> 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.
---------------------------------------------------------------------------

    \11\ For 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.
---------------------------------------------------------------------------

    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 sub-regional 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 pre- and 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:
    <bullet> Products--short term energy.
    <bullet> Periods--nine periods by season and load conditions.
    <bullet> 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

[[Page 20402]]

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:
    <bullet> 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.
    <bullet> 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:
    <bullet> 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.
    <bullet> Power exchanged. For each pair of interconnected areas, 
the model gives the net quantity of power exchanged between the 
areas under economic dispatch.
    <bullet> 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.
    <bullet> 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:
    <bullet> 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.
    <bullet> 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?

[[Page 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 SO<INF>2</INF> 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

[[Page 20404]]

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