##### Words: 2599

##### March 17, 2004

##### DRAFT

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# Chapter 6. Wholesale Competition

## 

## 1. Introduction

The previous chapter reviewed the information relevant to the grid's
support of wholesale markets. This Chapter considers the information
available to determine whether wholesale markets are competitive.
Competitive markets are desirable because they promote efficient
resource allocation.[^1] The Federal Government is responsible for
approving utility mergers and enforcing anti-trust law as well as wire
fraud and conspiracy statutes incident to recent prosecutions for
electricity market manipulation.

Somewhat surprisingly, competitive wholesale electricity prices are also
necessary for properly valuing congestion revenues and, therefore,
signaling transmission investment and new generator location. Congestion
can be reduced by investments in transmission capability and by locating
new generators to relieve bottlenecks. When energy prices are
competitive, the transmission price (difference in energy price at
either end of a line) is the marginal benefit (savings) from relieving
congestion. Consequently, when wholesale prices are competitive the
congestion charge is appropriate for signaling the (marginal) need for
investment and for guiding the location of new generation.

Section 2 presents conventional statistics that have been accepted by
Federal courts for describing competitive markets. Section 3 presents
the data for gauging wholesale competition and Section 4 describes how
the identified data gaps might be filled.

**2. Measures of Wholesale Competition**

Competitive markets are characterized by a large number of suppliers
vying to sell to a large number of informed customers. When there are
many buyers and sellers, each of which is small relative to the market,
no one has significant power over price. The market price is one that
causes demand to equal supply. In competitive markets, price just equals
the cost of producing the last unit sent to market, i.e., price equals
marginal cost. Price also equals the marginal benefit received by the
last customer willing to make a purchase.

A supplier has market power when he can sustain price significantly
above marginal cost.

***Number of competitors, concentration ratios and new entry*:** The
number of firms serving a regional market, their market shares and
market share indices, especially the Herfindahl-Hirschman Index (HHI),
are well-established indicators of a competitive industry.[^2] This
measure assumes that he relevant market can be identified. Thee
difficult problem in calculating market shares and HHI s is electricity
market boundaries are not obvious: establishing boundaries generally
requires electrical models. As discussed in Chapters 3 and 5 the Federal
Government does not maintain reference electrical models sufficient for
delineating regional markets.

While the courts pay attention to the HHI they also consider many other
factors before concluding that a firm is exercising market power.

***Price compared to marginal cost*:** Market price compared to marginal
cost is a litmus test for competition: wholesale price sustained above
the marginal cost of the last generator dispatched can indicate market
power. This comparison is called the Lerner index. The index is
variously calculated as the ratio of price to marginal cost or the
percent markup over marginal cost or the markup as a percent of price.
Accurately estimating and interpreting the Lerner index is often a
challenge.

To make a valid comparison, reference prices and marginal costs must
refer to the same time. This is important in electricity because prices
vary greatly during the day. PJM's hourly prices are illustrative of the
magnitude of price variation.

![](media/image1.wmf) Source: Data from
[www.pjm.com](http://www.pjm.com/) , markets, energy, real time, monthly
real-time LMP, file 200207-rt.csv, load weighted average prices

Accurate estimates of marginal cost are also critical to the results. As
pointed out by Timothy Brennan, many market power studies have used
average variable cost rather than true marginal cost. That would
overstate the extent of market power and might persuade regulators to
enforce artificially low price ceilings. [^3]

Selecting the right marginal cost to use in the Lerner index also
requires care. When transmission is unconstrained, the available
generators are ranked in order of their marginal costs from least to
most costly. The marginal cost of the *last* generator needed to meet
demand is the relevant marginal cost in the Lerner comparison.[^4]

In fact the transmission grid is at times congested-power cannot be
delivered as desired. PJM again provides an example. When the system is
congested, generators are recruited out-of-merit-order to stay within
security limits (see Chapter 3 for a discussion of security limits). A
congested system breaks into sub-markets, all operating at the same
time. Sorting out which generator's marginal costs to pair with observed
locational prices requires both an electrical model and information on
how much and where demand is located.

  ----------------- ----------------- ----------------- -----------------
  **Table 5-1.                                          
  Congested Hours                                       
  (Real Time) in                                        
  PJM, 2002**                                           

  **Month**         **Hours           **Month**         **Hours
                    Congested**                         Congested**

  January           245               July              505

  February          79                August            540

  March             120               September         595

  April             263               October           540

  May               596               November          533

  June              664               December          550
  ----------------- ----------------- ----------------- -----------------

Source: PJM, Figure A-15, Page 165, State of the Market Report

Areas that routinely find themselves in high priced sub-markets are
called load pockets. Since these areas have limited recourse to outside
suppliers, generators within the load pocket are well placed to increase
price well above marginal cost.

***Withholding and Manipulation of transmission markets:***
Concentration ratios and Lerner indices shed little light on how market
participants can sustain artificially high prices. They do not account
for the kinds of capacity withholding and grid manipulation that FERC
has observed in electricity markets. [^5] Withholding appears to have
been one way that generators were able to increase price during
California's crisis. FERC sees withholding as sufficiently important
that it has developed a pivotal supplier test.[^6] This test attempts to
identify generators whose absence would be enough to significantly
increase price. The data needed to calculate Lerner indices is adequate
to identify pivotal suppliers.

Enron showed how generators might take advantage of market rules to
manipulate transmission markets and increase their profits. To the
extent gaming impacts prices the Lerner index may indicate something is
amiss. The Lerner index would not detect strategies that only shift
profits.

Joskow and Tirole make a more subtle point about the ownership of
financial transmission rights (congestion revenue rights). Holders of
these rights are paid the congestion revenues associated with the
constrained lines their rights cover.[^7] They conclude "The possession
of financial rights by a producer in the importing region or by a
consumer in the exporting region aggravates their market power, since
financial rights give them an extra incentive to curtail their output or
demand to make the rights more valuable."[^8] Consequently in those
areas that use congestion rights, data on their ownership could be
important.

***Limits on market power:*** Firms with market power do not have an
unlimited ability to charge what they will. New entry and its threat are
disciplines to market power in many industries. To the extent new
competitors can enter quickly at low cost, incumbent firms are dissuaded
from exercising market power. If competitors actually enter in response
to high prices, they will diminish the price making power of incumbents.

In most industries price increases lead to demand reductions. If
pronounced, demand reductions limit how much suppliers can profitably
charge. There is presently a very limited degree of demand response to
the price of electricity. Essentially all retail customers face fixed
prices. Consequently when demand approaches the limits of supply,
generators could, absent regulatory intervention, raise price without
fear of losing sales. Currently regulatory pressure is more effective in
disciplining prices than is demand response.

The "natural" limits to market power in electricity are limited. And,
the grid provides some generators with protection from competition. Both
considerations suggest market prices may be above competitive prices, at
least when supplies are short.

# 

3\. Data on wholesale competition

This section discusses the official data available to detect and assess
market power.

***Number of firms and concentration ratios:*** Between FERC and EIA,
the Federal Government has a complete list of the larger generators,
their capacity, annual production and their ownership. The Form EIA-860
is the source of periodic reports: Inventory of Electric Utility Power
Plants in the United States and its companion Inventory of Non-Utility
Power Plants in the United States. The coverage of small generators,
especially co-generators, is less complete. Given market boundaries
official data is adequate to identify the competitors and their
capacities. EIA also collects data on individual generator output and
heat rates. That data allows calculation of market concentration ratios
and the fuel portion of costs. However, individual generator output and
heat rate data are not publicly available.

***Price compared to marginal cost:*** These comparisons are a basic
test of market competition. As explained above these comparisons require
market prices and quantities, net trade flow, good estimates of marginal
cost and, when the grid is congested, an electrical model.

The ISO's have complete market prices, quantities, trade flows, offers
to buy and sell and knowledge of operable units.[^9] They can also have
much of the detailed knowledge necessary to estimate marginal cost. Thus
ISOs or their market monitors are in a good position to properly compute
and interpret Lerner indices. [^10]

PJM has released estimates of the Lerner index for its system. PJM
reports the markup over price.[^11] In addition to having complete data
on generator availability and production, generator offers, demand
volumes and locations and valid electrical models, PJM also had cost
data on all units whose construction started before July 9, 1996.[^12]
PJM calculated the Lerner index for every five-minute interval and they
accounted for congestion. PJM has not released the underlying data and
models that would be necessary to replicate their results.

PJM reports two estimates of the average markup as a percent of price.
The first, called the adjusted markup, assumes that their marginal cost
estimates are precise. The resulting index averaged 11% for 2002, with a
maximum of 13% in July and a minimum of 10%. PJM also calculated the
index on the assumption that their estimates do not include all relevant
costs. They increased their marginal cost estimates by 10% presumably to
cover such hard to measure things as variable operations and maintenance
costs. The result is to lower the average markup to 2% in 2002, with a
maximum of 4% in July and a minimum of 1%.[^13]

PJM interprets these results as:

> "...the data on the price-cost markup are consistent with the
> conclusion that the energy market was reasonably competitive in 2002
> although the evidence is not dispositive."[^14]

Official data for areas outside of the ISOs is far less precise. EIA
collects but does not publicly release generator fuel costs, heat rates
and similar information for estimating marginal cost on the EIA-860 and
EIA-423. Fuel costs are monthly and heat rates tend to be long-term
averages. Since a generator's heat rate varies a great deal depending on
utilization, and its operating regime (start-up, shut down, etc.)
marginal costs estimates based on that data are likely to be imprecise
approximations of hourly marginal costs. Hourly generation data from
fossil fueled and hydroelectric facilities (pumped storage) are not
available from EIA.

In comparing price to the marginal cost of serving the wholesale market,
it is necessary to know which generators were available at the time the
comparison wholesale prices were observed. The Environmental Protection
Agency's Continuous Emissions Monitoring System records hourly emissions
and, sometimes, hourly output from fossil fueled generators. The absence
of emissions is an indicator that a particular plant is not operating.

Outside of the ISOs, there are no official hourly market prices. There
are commercially available prices at a few "hubs". How closely these
prices approximate market prices is controversial.

If market data were to show multiple prices, it would be necessary to
have an accurate electrical model to determine whether the differences
reflect congestion or something else. As mentioned previously, the
Federal government does not maintain such models.

Outside of the ISOs, official data does not support firm conclusions
about the presence or absence of competitive wholesale markets.

**Entry:** Chapter 4 showed that the Federal Government has complete
data on the connection of larger generators to the grid. A large number
of independent generators have entered the market since 1999. Official
data says little about the costs and time lags associated with entry.
And official access data is not archived in a form that allows
statistical analysis of access availability and the quality of service.

***Demand-Price Response:*** The Federal Government collects no data on
the amount of consumption that is metered for price response. Nor does
it routinely collect data on consumer participation and behavior in
price responsive demand programs. The ISOs periodically release
information about their programs. Such data as exists show demand
response is miniscule.

The New England ISO, for example, reports the number of customers signed
up for each program and the available megawatts for response on its web
site,

> "As of November 1, 2002 there were 248 customers signed up for the
> load response program providing 195.615 MWs of possible load relief.
> There are 122.494 MWs in the Class 1 Program and 73.121 MWs in the
> Class 2 Program."[^15]

The total possible load relief is only seven tenths of one percent of
New England's installed capacity in 2000.[^16]

Similarly, PJM's State of the Market Report finds:[^17]

> "The maximum hourly reduction in load that resulted from PJM programs
> was 1,833 MWh in 2002."[^18]

This compares with a maximum daily peak demand of 63,762 MW in 2002.

Demand response is not a counterweight to market power at this time.

**4. Filling the Information Gaps**

Outside of the ISOs the government does not have the data necessary to
monitor and evaluate the competitive status of wholesale markets.
Government can subpoena data in response to clear behavioral evidence of
anti-competitive behavior or as part of a merger approval. But the
subpoena is not a reasonable means of obtaining data for market
monitoring.

If Federal regulators and anti-trust officials are satisfied with market
share analyses, then the critical need is for high quality power flow
models and associated data described in Chapter 3. That information is
required to delineate market boundaries.

If Federal regulators and anti-trust officials require Lerner indices
for non-ISO areas, much more data than is currently available would be
needed. Critical missing data are high frequency wholesale price,
generator output and availability, and demand, net of power inflows.
High frequency, market specific wholesale price data would require new
collections.

Hourly generation from fossil fueled units would be available if EPA
were to require (rather than just encourage) generators to report actual
generation injected into the grid on the Continuous Emission Monitoring
System (CEMS). But CEMS does apply to generation from nuclear units,
hydropower (including pumped storage), wind, solar, and geothermal
units. Hourly generation data for nuclear and federal hydropower exists,
but is not readily available. Utilities and IPPs have production data
for the other sources, but neither EIA nor FERC currently collect it.
NERC maintains extensive data on generator availability.

Demand by control region is reported hourly on the FERC 714. As noted in
Chapter 3 that data are not disaggregated to individual buses, reporting
is incomplete and the data from different reporters is contradictory.
Hourly net power inflows are not reported, so net demand cannot be
calculated.

By contrast, the ISOs have all the data required to delineate markets
within their areas and to compute concentration ratios and Lerner
indices.[^19] FERC has the power to require that ISO data necessary to
gauge competition be made routinely available to government policy
makers and analysts. To date, FERC has not made such a requirement.

As mentioned in Chapter 3 information on demand response to prices could
be obtained by adding a new schedule to the EIA 861. The required
information would include potential MW metered to record hourly (or
higher frequency) consumption and MWh charged by time of consumption.

[^1]: Efficient in the sense that a competitive wholesale power market
    would minimize the social cost of meeting consumers' electricity
    demands and those demands would reflect the value to them of
    consuming electricity compared to other goods. Stated differently,
    competition has the potential to maximize the net benefit from
    electricity consumption less the costs of its production and
    delivery.

[^2]: See U.S. Department of Justice, 1992 Horizontal Merger Guidelines
    (with April 8, 1997, Revisions to Section 4 on Efficiencies),
    Section 1. Market Definitions, Measurement and Concentration.

[^3]: Brennan, Timothy J., Mismeasuring Electricity Market Power,
    Regulation, Spring 2003, pages 60-65.

[^4]: It can happen that market demand is met at exactly the maximum
    capacity of the most expensive generator. In that case a competitive
    price is consistent with any marginal cost between that of the last
    generator recruited and that of the generator required to meet any
    small additional demand. See Stoft, Steven, *Power System
    Economics*, IEEE Press, Wiley Inter-Interscience, 2002 for a
    detailed discussion of these issues. For the Lerner test to give the
    right answer, all generators able and economic to run at the time
    the comparison is made must be available for dispatch. If relatively
    cheap generators were in fact withheld from the market, price would
    equal marginal cost, but market prices would be above the
    competitive level.

[^5]: See, for example, FERC Staff Report, *Final Report on Price
    Manipulation in Western Markets, Fact-Finding Investigation of
    Potential Manipulation of Electric and Natural Gas Prices,* Docket
    No. PA02-2-000, March 2003.

[^6]: The test amounts to hypothetically removing some or all of a
    generator's capacity from the market supply. If that would cause
    price to increase much above the competitive level, that generator
    is said to be pivotal

[^7]: The congestion revenues are the difference of the prices at the
    receiving and sending location times the flow guaranteed by the
    right. When prices are the same at both locations, there are no
    congestion revenues.

[^8]: Paul Joskow and Tirole, J, *Transmission rights and market power
    on electric power networks*, the Rand Journal of Economics, Vol. 31,
    No. 3, Autumn 2000, page475

[^9]: The market prices that ISOs report are, on occasion, "mitigated":
    the ISO rejects the original market price and replaces it with the
    mitigated price when the ISO concludes the former is exorbitant.

[^10]: Independent researchers have made similar calculations using
    price data from ISOs. See, for example, Borenstein, Severin,
    Bushnell, James and Wolak, Frank, Measuring Market Imperfections in
    California's Restructured Wholesale Electricity Market, University
    of California Energy Institute, CSEM WP102, June 2002

[^11]: (market price-marginal cost)/market price).

[^12]: PJM, 2002 State of the Market, page 28.

[^13]: PJM, 2002 State of the Market, page 28.

[^14]: PJM, 2002 State of the Market, page 5.

[^15]: http://www.iso-ne.com/Load_Response/main.html January 22, 2003.

[^16]: EIA, Electric Power Annual 2000, Volume II, Table 3, New England
    installed capability, page 4.

[^17]: PJM Interconnection, L.L.C. "Load Response Programs 2002
    Statistics Estimated for 6/26/02 to 12/1/02".

[^18]: PJM, 2002 State of the Market, page 37

[^19]: In the event these statistics indicate non-competitive pricing,
    special purpose data collections could be employed to determine how
    (withholding, manipulation of transmission markets, etc.) market
    participants are thwarting efficient pricing.