Lessons from the First Year of Competition in the California Electricity Markets
The start of the California markets generally has been successful, with no large problems in the mechanics of their operation. But the data provides grounds for some concern about market power, particularly during high-load periods, and about efficiency in the ancillary services markets.
Robert L. Earle, Philip Q Hanser, Weldon C. Johnson, and James D. Reitzes
I. Introduction
ituated at the western edge of the continent and the eastern
rim of the Pacific, California has always possessed allure as a place of frontiers. California’s develop-ing competitive electricity markets represent another “frontier” that has attracted widespread interest. At the first birthday of these markets, it seems appropriate to review their current state of devel-opment, even though they are surely in a transitional state. We do not undertake to make a compre-hensive assessment of the effi-ciency of these markets, given their evolving nature. Rather, in review-ing one year of data, our goal is to
examine the economic and techni-cal relationships between the vari-ous power markets arising under the California Power Exchange (PX) and the California Indepen-dent System Operator (ISO).
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Our analysis also considers the deci-sion faced by generators selling into both the PX and ancillary ser-vices markets, identifying those areas where there may be losses in both efficiency and profits. Before proceeding further, some institu-tional detail would be useful.
II. A Little Institutional Detail
California’s electricity market centers around two entities, the
Robert Earle
is an Associate in theWashington, DC, office of The BrattleGroup. His most recent work has been
in the areas of power market priceforecasting, strategic behavior in power
markets, and optimization of hydropowerin a deregulated environment. He holds
a Ph.D. in operations research fromStanford University.
Philip Hanser
is an economist and aPrincipal of The Brattle Group at itsCambridge, MA, headquarters office.He was previously with the Electric
Power Research Institute.
Weldon Johnson
, a graduate ofYale University with a B.A. in
economics, is a research analyst atThe Brattle Group.
James Reitzes
is an economist andPrincipal of The Brattle Group, basedin its Washington, DC, office. He has
previously worked for the Federal TradeCommission, and has considerable
experience in analyzing competitionand firm strategies in network
industries. His recent electric industryexperience includes providing advice
on market power issues relatedto electric utility mergers, and
California Power Exchange and the California Independent System Operator. The role of the PX is to provide a liquid market for the buying and selling of electricity. It conducts energy auctions to deter-mine an hourly market price for electricity. The ISO is responsible for operating the transmission sys-tem and generally ensuring system reliability. It uses market mecha-nisms to obtain most ancillary ser-vices and set real-time prices for energy used to alleviate imbal-ances, relieve congestion, and ensure better system performance.
A. The Power Exchange
In California, the three major utilities (PG&E, SDG&E, and SCE) are required to buy and sell their energy through the PX until 2002.
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All other participants in power markets can trade electricity using a variety of means (e.g., bilateral contracts or electronic trading). These non-PX participants must submit schedules with the ISO through entities known as Sched-uling Coordinators (SCs), which submit to the ISO “balanced” schedules in which the quantity of energy supplied equals the quan-tity demanded. While technically the PX is just another Scheduling Coordinator for the ISO, it actually is much more important, because roughly 87 percent of the electric-ity under the authority of the ISO is scheduled through the PX.
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uring its first year, the PX has had two markets
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—the Day-Ahead market and the Day-Of market
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—where it calculates a market-clearing price for electric-ity. In both markets, generators are
paid only for energy. Unlike Pennsylvania-New Jersey-Maryland (PJM) and certain other power pools, generators receive no capacity payments or payments for startup costs. Consequently, generators must recover their fixed and capital costs through direct payments for energy on PX sales, as well as through the energy and capacity charges in the ISO ancil-lary services markets.
The Day-Ahead market takes
supply schedule. An analogous procedure is used to form an aggregate demand schedule. The unconstrained market-clearing price (UCMP) is the price where quantity demanded equals the quantity supplied, based on these schedules.
he PX notifies market partici-pants of each hour’s market-
clearing price by no later than 8:10 a.m. It then forwards its schedule, which specifies the amount of energy it will supply and demand (which are equal) for each hour of the day, to the ISO. Absent conges-tion, this market-clearing price represents the price actually paid by PX participants for buying or selling energy.
Just as the PX submits a Day-Ahead schedule to the ISO, every other Scheduling Coordinator also submits a schedule to the ISO as part of the Day-Ahead scheduling process. The ISO runs all of the schedules through its software to see whether the mix of schedules is compatible with the technical capabilities of the electric power grid. If the ISO detects no prob-lems, then each SC’s schedule is deemed final. However, if the ISO detects transmission capacity con-straints between zones (inter-zonal congestion) within the system, then it turns to congestion charges to relieve the constraints.
In order to calculate congestion charges, the ISO determines a mar-ginal price to use for the congested interfaces between zones. To do this, the ISO relies upon adjust-ment bids. When each Scheduling Coordinator (SC) submits its initial schedule to the ISO, it also has the
During its first year,the PX has had two
markets whereit calculates a
market-clearing
price for electricity.
place one day in advance of the actual flow of electricity. The basic structure of the market is straight-forward. By 7 a.m. on the day prior to the actual energy flow, each par-ticipant in the Day-Ahead market submits its supply or demand bids for each hour of the subsequent day. The bids are in the form of price-quantity pairs. Each partici-pant may submit up to 16 price-quantity pairs for each hour of the day. These price-quantity pairs represent the supply curves, or demand curves, for each PX partic-ipant. For each hour of the day, the PX combines all of the individual supply bids to form an aggregate
option of submitting adjustment bids, which are price-quantity pairs that denote how much the SC is willing to pay (receive) to use (produce counterflows across) the congested interface. The ISO uses the adjustment bids to calcu-late a usage charge for the inter-faces that each SC is charged (paid) for using (producing coun-terflows across) the congested interface. Once it has calculated this capacity charge and deter-mined which SC schedules will be adjusted, the ISO issues the final Day-Ahead schedules by 1 p.m. These schedules state the amount of energy each SC is responsible for producing (consuming).
The PX Day-Of market operates in a manner similar to the Day-Ahead market, except that the market consists of three separate auctions for separate hourly seg-ments of the day. Auctions are con-ducted at 6 a.m. for hours 11 a.m. to 4 p.m., at noon for hours 5 p.m. to midnight, and at 4 p.m. for hours 1 a.m. to 10 a.m. As time approaches the actual hour of the power flows, PX participants have better forecasts of their actual load commitments. The Day-Of market allows PX participants to more closely match their schedules with forecasted conditions, so they will be less reliant on the Real-Time imbalance energy market. The UCMP is determined the same way as in the Day-Ahead market. Since the participants are trading largely based on unexpected devi-ations in their schedules, the vol-ume of electricity traded in the Day-Of market is much smaller than the Day-Ahead market.
B. The ISO: Ancillary Services and Imbalance Energy
Since system reliability is the responsibility of the ISO, the ISO oversees procurement of all ancil-lary services in its jurisdiction. Other than black-start units and voltage control obtained through annual contracts, the ISO procures ancillary services through its Day-Ahead and Hour-Ahead markets. For the four types of ancillary ser-vices obtained on a daily basis (i.e., spinning, non-spinning, replace-ment, and regulation), each Sched-uling Coordinator has the option of self-providing or paying for ancillary services through the ISO’s procurement process.
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Table 1
provides definitions for each market-based ancillary service.
or the Day-Ahead market for ancillary services, the ISO uses
forecasted demand
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to determine how much of each service it will need during each hour of the day. When submitting its initial pre-ferred energy schedule at 10 a.m. on the day prior to the actual day
of electricity flows, each SC deter-mines how much of each ancillary service it will be self-providing. Then, the ISO procures the remaining requirements of ancil-lary services. At this stage of the procurement process, market par-ticipants are aware of the Day-Ahead price for energy purchased through the PX.
Providers of ancillary services submit bids for each of the four market-based services. The bids consist of two parts, a capacity bid and a Real-Time energy bid for each hour of the day. The capacity bid denotes how much the bidder must be paid to reserve capacity for providing the relevant ancillary service. It represents a physical, as opposed to financial, “option” held by the ISO to call on the bidder to produce energy for that ancillary service. The ISO does not pay any startup costs, so units that provide ancillary services must inherently incorporate any startup costs in their capacity bids. The Real-Time energy bid represents a “call” price. It is the price that the
Table 1:
Definition of Market-Based Ancillary Services
Ancillary Service Definition
Regulation reserve Unloaded generation capacity that can be achieved within 30 minutes that is online and subject to automatic generation control, and thus capable of responding in an upwards and downwards direction
Spinning reserve Unloaded generating capacity that is synchronized to the system and that is capable of being loaded in 10 minutes
Non-spinning reserve Unloaded generation capacity (or load that is capable of being interrupted) that can be synchronized to the system and reached within 10 minutes
Replacement reserve*
Unloaded generation capacity (or curtailable demand), that can be
synchronized to the system within 60 minutes
* Although the ISO views replacement reserve as an ancillary service, the FERC does not.
bidder requires to provide energy if the ISO exercises its option and calls on the unit to provide energy for the ancillary service.
hen setting the market-clearing price for reserve
capacity, the ISO looks only at the capacity part of the ancillary ser-vice bids. The energy part of the bids is used to determine if the ISO will use its option and call on the unit to produce energy. The ISO stacks the capacity bids in ascend-ing order, and, in general, moves up the bid stack until it is able to satisfy its requirement for the particular ancillary service. The marginal bid represents the market-clearing price for the ancillary ser-vice, and is the price that all of the units providing the particular ancil-lary service will receive for their capacity for that particular hour.
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This staged procurement proce-dure, where generators are first “chosen” based on capacity bids and then “called” based on energy bids, introduces potential ineffi-ciency into the ancillary services market. Generators offering low-priced capacity form the pool of generators from which energy is procured to satisfy ancillary ser-vices needs. However, generators with low capacity bids could have relatively high energy bids. Con-sequently, when attempting to minimize the overall cost of pro-curing ancillary services, one must simultaneously consider capacity and energy bids. The California ISO considers these bids sequentially, and so in the presence of startup costs may obtain a sub-optimal solution.
The ISO conducts each ancillary
service auction in sequential order, starting with regulation reserve and then moving in turn to spin-ning, non-spinning, and replace-ment reserves.
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In the Day-Ahead market, the process is done for each hour of the subsequent day. Each SC is notified of its ancillary services obligations when it receives its final Day-Ahead schedule at 1 p.m.
The ISO also conducts an Hour-Ahead ancillary services market.
vice, with units being selected to provide capacity only on the com-petitiveness of their capacity bids.
lthough all the SCs including the PX Day-Ahead and Day-
Of markets match load with gener-ation, Real-Time electricity use is bound to deviate from forecasted levels. The ISO Real-Time Imbal-ance Energy market creates mecha-nisms to deal with these devia-tions. To keep load and generation constantly in balance the ISO, in addition to relying on units pro-viding regulation reserve, often must instruct units to either increase or decrease the amount of energy they are generating. To do this, the ISO relies upon Real-Time energy bids of those units selected to provide capacity in the Day-Ahead and Hour-Ahead ancillary services markets, as well as sup-plemental energy bids. Supple-mental energy bids are received 45 minutes before the start of the hour, and denote how much units must be paid to increment their energy above the levels determined by the Day-Ahead and Hour-Ahead mar-kets (or are willing to be paid to decrement their energy supplied). All units, including those selected to provide capacity in the ancillary services markets, may submit sup-plemental energy bids.
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The ISO ranks the supplemental energy bids and the Real-Time energy bids of those units provid-ing ancillary services. If it has to increase energy provided, then it moves up the “increment” bid queue until it attains the desired increase in MW. The bid for the marginal unit of energy represents the market-clearing price paid for
The stagedprocurement procedure
introduces potentialinefficiency into
the ancillary
services market.
A Scheduling Coordinator that has its requirements for ancillary ser-vices diminished as a result of reduced load conditions can sell back its excess ancillary services in the Hour-Ahead market. Con-versely, a SC that faces unantici-pated increases in its load, and therefore unanticipated increases in its reserve energy requirements, can purchase ancillary services in the Hour-Ahead market. The Hour-Ahead market is conducted in the same manner as the Day-Ahead market. Each bidder submits capacity bids for each ancil-lary service in addition to Real-Time energy bids for each ancillary ser-
all MW purchased through the Real-Time market. If the ISO must decrease electrical generation, it begins with the highest-priced bid and moves down the “decrement” bid queue until it attains the desired reduction in MW. The bids represent the price that the genera-tor is willing to pay in order to forego supplying a given amount of generation. The bid for the mar-ginal unit of energy reduction rep-resents the market-clearing price paid to all generators reducing their output in the Real-Time market.
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C. Selling into Multiple Markets: A Generator’s Profit-Maximizing Puzzle
Given the presence of Day-Ahead and Day-Of markets for
energy, the Day-Ahead and Hour-Ahead markets for ancillary ser-vices, as well as a Real-Time energy market, a generator faces a complex decision concerning which markets to sell into. The sequence of decisions and infor-mation flows are presented in
Fig-ure 1
. The generator potentially faces a “sell now or sell later” deci-sion, as well as a “sell energy or sell ancillary services” decision. Each decision potentially fore-closes opportunities to sell into other markets.
he generator first decides whether to bid into the PX
Day-Ahead market by 7 a.m., and receives the results of that auction 90 minutes later. Then, the genera-tor has 90 minutes to determine its
bidding strategy for the ISO ancil-lary services auction. The results of that auction are determined by 1 p.m. Consequently, generators and other market participants must respond quickly to market signals. The bidding process con-tinues during the day when power flows actually occur. Market par-ticipants have the opportunity to place bids up to five hours before power flows in the PX Day-Of market, two hours ahead in the ISO Hour-Ahead ancillary services market, and 45 minutes ahead in the ISO Real-Time Imbalance Energy market.
III. Price Patterns: PX and ISO Energy Prices
A. Day-Ahead PX Prices vs. Real-Time ISO Prices
We now turn to some casual examination of energy prices. The load-weighted average PX Day-Ahead price for the first year was $26.60/MWh
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and the load-weighted average ISO-instructed Real-Time energy price was $47.10/MWh. Both of these num-bers compare with the approxi-mately $60/MWh
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formerly charged to consumers under regulation.
Figure 2
plots the average daily PX and instructed Real-Time energy prices, along with the total MW sold in the PX market.
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Hot weather in July and August caused increased demand, resulting in higher prices for those months. Note that, as described above, the instructed Real-Time energy price is $20.50/MWh above the Day-Ahead price.Figure 1: Decision and Information Flows in the California Market
enerators can sell electric power into the Day-Ahead
market, take their chances on sell-ing into the instructed Real-Time (supplemental energy) market if demand conditions require addi-tional power, or can overgenerate compared to their Day-Ahead and Hour-Ahead schedules. A genera-tor has less opportunity to sell into the instructed Real-Time market, where demand stems only from energy imbalances, than to sell into the Day-Ahead market, where demand stems from energy needs. Consequently, one might expect that generators would sell as much energy as possible into the Day-Ahead market, rather than selling incremental energy into the instructed Real-Time market, unless the Real-Time price were higher than the Day-Ahead price. The results in Figure 2 are consis-tent with that hypothesis.
from April 1, 1998, to March 31, 1999. Day-Ahead prices increase steadily throughout the day from 5 a.m. until 5 p.m. Prices then drift downward from 5 p.m. until 5 a.m. Notice the strong correlation between the hourly load patterns and the hourly prices on the Day-Ahead market. The Real-Time price movements largely mirror the Day-Ahead price movements, except that there is a much larger increase in prices between 11 a.m. and 4 p.m. The average price of roughly $80/MWh in the 4 to 5 p.m. time period suggests that there may be significant profit opportunities for generators that can ramp up production quickly and inexpensively during the peak afternoon period. It should be noted, however, that these are instructed Real-Time price aver-ages, so this opportunity does not occur every hour on average.
Note that while Day-Ahead prices and the Real-Time prices may sometimes diverge in their day-to-day movement, these prices generally move together. Real-Time prices do show greater volatility, however, as is evident in Figure 2. When high load condi-tions prevail, one would expect that Day-Ahead prices should be higher than under lower load con-ditions, since higher-cost genera-tors would be needed to service the market. For these reasons, also, Real-Time prices, on average, should be higher during high load conditions than during low load conditions. This suggests that there should be positive correla-tion between the Day-Ahead prices and the Real-Time prices.
igure 3
displays the load-weighted average price for
each hour of the day, and the Day-Ahead sales volume for the period
Figure 2: Average Daily Weighted (by MW) Day-Ahead PX and Real-Time Incremental Prices (April 1, 1998, to March 31, 1999)
o conclude our initial exami-nation of energy prices,
Fig-ure 4
presents a “scatter” diagram of the PX Day-Ahead price, expressed on an hourly basis, against the relevant PX sales level. This diagram clearly shows the relationship between increases in load and increases in market prices. Moreover, it is clear from this diagram that there are several hours, representing 1.6 percent of all hours, when the price is zero. One reason for this is that Regula-tory Must Take (RMT) generation bids into the PX at zero to guaran-tee dispatch. Another reason for zero bids is that units with signifi-cant startup costs, such as large steam units, can avoid shutting down during low load periods by entering sufficiently low bids. This behavior allows these units to avoid incurring additional startup costs. Overall, the RMT units and
the units that bid into the PX with a zero price for operational resources account for 18,000 MW of capacity.
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Figure 4 illustrates a pricing pat-tern that differs from that which would be obtained under tradi-tional economic dispatch or pro-duction costing models. First, the peak prices are beyond the upper bounds of short-run marginal costs of producing at peak load levels observed under regulation. Sec-ondly, prices at or near zero are not anticipated by many of these mod-els since they do not explicitly con-sider the effect of startup costs on the dynamic behavior of genera-tors. Thirdly, these models often ignore the impact of outages on price levels in the market. Finally, and perhaps most importantly, the economic dispatch approach to price forecasting neglects the potential for strategic behavior. In
the next section, we examine how prices in the California market compare to the predictions of vari-ous models, including those that allow for the strategic behavior of generators.
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B. Actual Prices vs. Model Predictions
Prior to the opening of the dereg-ulated California energy markets, many studies were performed to analyze the effect of deregulation on market prices. We analyze two of the more prominent studies, focusing on the relationship between their predictions and the performance of the market to date. We have not adjusted the predic-tions of these studies to address differences in estimated load con-ditions and actual market loads. Our casual comparison is not meant to be a judgment of the use-fulness of these studies. Each has
Figure 3: PX Day-Ahead and Real-Time Prices by Hour of Day, Weighted by MWh (April 1, 1998, to March 31, 1999)
Commission, has a fairly detailed physical model of the California system, including multi-area pro-duction costing and AC load flow. As a result the model implicitly allows for price differentials across geographical regions. It also includes an analysis of demand-side bidding and must-take and must-run generation. Startup and no-load costs are also explicitly considered in the dispatch algo-rithm. The model, however, does not consider the potential of gener-ators to exercise market power through strategic behavior.
Table 2
compares the actual prices obtained under the PX Day-Ahead market with those pre-dicted in the LCG study. Overall, the study accurately predicts that
deregulation will produce benefi-cial price effects for consumers. On the other hand, the LCG price pre-dictions do not suggest as much price variability as has actually occurred. The actual off-peak prices have been lower than the predicted prices in every month. In addition, the predicted peak prices in the high-load months of July, August, and September are lower than the actual peak prices.
A second study, by Borenstein and Bushnell,
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considers the abil-ity of generators to potentially engage in strategic behavior. It estimates prices for electrical power under the assumption that individual generators act as Cournot oligopolists. In the Cournot model, each generator chooses an output level to maxi-mize its profits with full knowl-edge of market demand condi-tions. Market equilibrium is
achieved when each generator’s output choice maximizes its profits given the output choices of rivals in the market. If generators believe they can exercise market power, they will attempt to increase the market price by restricting their own output.
ince Borenstein and Bushnell estimate prices that would
arise in the year 2001, we have attempted to facilitate the compar-ison of their estimates with the observed 1998 and 1999 PX prices by using an “inflation” adjustment for the period from 1998 to 2001. The actual PX Day-Ahead Prices during 1998 have been inflated at a 3 percent annual rate for the three-year period between 1998 and 2001.
Due to their use of Cournot com-petition, Borenstein and Bushnell’s results depend on their assump-tion concerning the sensitivity of demand to changes in price. We
Figure 4: Unconstrained PX Market Price vs. Supply of Energy, Day-Ahead Market (April 1, 1998, to March 31 1999)
focus on two assumed values for the elasticity of demand, 0.1 and 0.4. When the elasticity of demand equals 0.1, a price decrease of 1 per-cent leads to a 0.1 percent increase in electricity consumption. When the elasticity of demand equals 0.4, a price decrease of 1 percent leads to a 0.4 percent increase in electric-ity consumption.
Figure 5
contains both Cournot and “competitive” prices evalu-ated at elasticity values of 0.1 and 0.4. In the competitive scenario, generators do not engage in strate-gic behavior. Instead, they set the energy price for each generating unit equal to that unit’s short-run marginal cost. Units are then eco-nomically dispatched until expected load requirements are met. The competitive price equals the mar-
ginal cost of the last unit needed to satisfy the load requirement.
ith respect to Borenstein and Bushnell’s price pre-
dictions for March and June 2001, both the Cournot and competitive models overestimate our inflation-adjusted estimates of actual mar-ket prices for most hours (see Fig-ure 5A and 5D). For September (Figure 5B) and December (Figure 5C), the Cournot model again sub-stantially overestimates market prices during most hours of the month. However, for fewer than 10 percent of the hours in the month, the inflation-adjusted market prices lie between the prices pre-dicted by the Cournot model at the two illustrated elasticity values. This result suggests that the prices displayed in the market during
these peak-load hours are consis-tent with some strategic behavior by generators. Of course, given the wide gap between the two Cournot model curves it is clear that the exact elasticity is a crucial and sen-sitive driver of the results. Note that the competitive model predicts price behavior quite well during the 80 percent of hours that are associ-ated with relatively lower loads.
C. Prices for Ancillary Services
We now turn to the area of ancil-lary services. Remember that four ancillary services are bid into the market: regulation, spinning, non-spinning, and replacement. Each selected provider of ancillary ser-vices receives an “availability” payment for being “on call,” and then receives a Real-Time energy payment if chosen to actually provide electricity.
1. Availability Payments.
The ancillary services market was plagued by episodes of extremely high availability payments, partic-ularly during the summer of 1998.
Figure 6
shows the pattern of availability payments for three
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reserve types of ancillary services. This graph makes apparent the importance of the changing market structures. Until July 1, all entities bidding into the ancillary services markets were subject to FERC cost-based rates. Before June 10, nearly all of these rates were below $10/MW. Consequently, the ancillary services capacity prices were below $10 for nearly every hour. Starting June 10, some of the divested units from the Big Three utilities in California were granted new cost-based rates of
Table 2:
Actual PX Prices Compared to Predicted Prices
Average PX Prices (Zonal Prices for SP15)
LCG Study(Zonal Prices for SP15)
LCG
2
PX Prices(SP15)
Off-Peak Peak Total
Off-Peak Peak Total
Off-Peak Peak Total
April 17.02 25.96 22.61 20.68 27.73 25.09 3.66 1.77 2.48
May 5.83 15.80 12.06 23.94 27.88 26.40 18.11 12.08 14.34
June 4.03 17.32 12.34 21.08 29.18 26.14 17.05 11.86 13.80
July 19.63 41.25 33.14 23.88 36.60 31.83 4.25
2
4.65
2
1.31
August 23.16 50.04 39.96 25.07 33.22 30.16 1.91
2
16.82
2
9.80
September 22.45 39.73 33.25 26.37 33.66 30.92 3.92
2
6.07
2
2.33
October 15.98 28.68 23.92 25.44 32.76 30.01 9.46 4.08 6.09
November 14.03 28.25 22.92 26.07 35.06 31.69 12.04 6.81 8.77
December 19.71 30.95 26.74 27.60 39.20 34.85 7.89 8.25 8.11
January 15.74 24.30 21.09 31.31 35.82 34.13 15.57 11.52 13.04
February 14.68 21.90 19.19 28.33 36.51 33.44 13.65 14.61 14.25
March 14.67 22.37 19.48 22.78 29.65 27.08 8.11 7.28 7.60
Total
15.60
28.95
23.94
25.21
33.11
30.15
9.61
4.16
6.21
January, February, and March 1998 LCG prices were used for 1999 prices. All averages are unweighted. The LCG study uses an unidentified 15 hours to derive its peak hours, while we use hours 8:00 to 22:00 as peak hours.Source: California PX Data, and LCG Study, Table 3.14.6a: Average Monthly Buyer’s Market Clearing Price Base Case.
$250/MW on July 24. Looking at the reserve prices for September through November, a period when load levels were lower, the capped price was hit much less frequently. Although this historical price information is very useful in its own right, one should be careful in drawing too many conclusions about future prices from it because of the evolving nature of market regulations. Following FERC’s approval on Nov. 3, 1998, of market-based rates for all units in California for ancillary services, prices have occasionally hit their price caps, but with a frequency much lower than during the summer of 1998.
onsistent with the results in Figure 6, the availability pay-
ments for ancillary services have exceeded the Real-Time energy payments for a small, but signifi-cant, percentage of the time. Exam-
ining those hours where units were instructed to increment gen-eration (67 percent of the hours), the availability payment for capac-ity exceeded the Real-Time price of the energy produced by the capac-ity during 9.6 percent of the time for spinning reserves, 4.4 percent of the time for non-spinning reserves, and 4.3 percent of the time for replacement reserves. In this situation, the market is paying more for the option to have the energy available than it is for the energy itself. If the market-clearing energy price actually represented the marginal consumer’s willing-ness to pay for energy, the implica-tion would be that the payment to have the capacity available exceeded the marginal con-sumer’s valuation of the energy. This would represent an inefficient outcome. Specifically, it calls into question how demand-side influ-
ences enter into the procurement of ancillary services under the two-part California market mechanism.
ather than bear such high availability payments, it
would seem to be cheaper to pro-cure the energy through other mar-ket mechanisms. Note, however, that the availability payment is made before the Real-Time energy market clears. During tight demand conditions, the
ex ante
expectation of the Real-Time price of energy could be higher than the availability payment. However, once demand is realized, the market-clearing price may be lower than the availability pay-ment.
Figure 7
shows that the (Day-Ahead) availability payment for the four reserve ancillary ser-vices is usually below the Day-Ahead PX energy price. If the Day-Ahead PX price is often lower than the Real-Time price of energy
Figure 6: Day-Ahead Ancillary Services Prices, SP15 (April 1, 1998, to March 31, 1999)
(as we have shown earlier), then the market’s expectation of energy prices frequently exceeds the price for having capacity available to produce that energy.
oreover, the ISO market is an “administered” market
where demand-side influences do not enter explicitly into the pro-curement process. If the ISO is viewed as procuring ancillary ser-vices in order to avoid service interruptions, then the appropriate consumer valuation measure may be the value of lost load (VOLL). In this context, an availability pay-ment represents an “option” which the ISO purchases. When demand conditions warrant, the ISO “exer-cises” the option and purchases energy at a price that is, arguably, less than VOLL. With this justifi-cation for high-availability pay-ments, the ISO has two potential
options for improving the effi-ciency of this process. It may either directly assess the VOLL, a difficult task at best, or it may incorporate demand-side bidding in the market-clearing process, likely the most efficient long-term solution.
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One of the fascinating parts of Figure 7 is the behavior of regula-tion reserve. It is relatively high-priced during the shoulder periods and relatively low-priced during peak periods. Why would this counterintuitive picture make sense? One reason may be as fol-lows. On the shoulder, large units or, more generally, units that need to ramp up for peak periods (or ramp down for off-peak periods) would not want to provide regula-tion since this would interfere with their optimal ramping behavior.
These units effectively incur
higher costs in providing regula-tion during shoulder periods in comparison to other times of the day. Smaller units with more flex-ible ramping behavior may be better suited to providing regula-tion at these times.
21
2. Energy Payments for Ancillary Services. Note that, although Figures 6 and 7 describe the “availability” payments received for ancillary services, that is only one part of the two-part nature of ancillary services pricing. From the market’s efficiency per-spective, and from the generator’s perspective of maximizing its profits, one needs to know what the market-clearing price is for the energy itself, as well as the proba-bility that one will be called upon to provide the energy. This infor-mation is summarized in Table 3. Table 3 shows that the probability
Figure 7: PX and Ancillary Service Day-Ahead Prices by Hour of Day (Weighted by MW), With Max Price Equal to $250/MW (April 1, 1998, to March 31, 1999)
of being called on a percent MW basis during peak is quite small: 8.6 percent for spinning, 2.9 per-cent for non-spinning, and 4.7 per-cent for replacement reserves. On a unit participation basis (i.e., the number of units standing by, divided by the number called), the results are similar. Note that spin-ning reserves are called the most frequently, followed by replace-ment reserves, and then non-spinning reserves.
t is evident from Table 3 that the average call price for reserve
energy is inversely related to the frequency at which that reserve is called. This result is somewhat mis-leading since all ancillary services receive the same Real-Time energy payment per MWh. However, cer-tain reserves are called upon more often than others, implying that those reserves are called during shoulder and off-peak periods where Real-Time energy prices are relatively low. Consequently, the average price is lower for more frequently used reserves, such as spinning reserves.
Of course, the probability that a generator is called to provide energy depends not only on the demand for that particular ancil-
lary service, but also the genera-tor’s energy bid. Since generators are chosen to stand by based on their availability bids alone, a generator could bid low to try to guarantee standby status, but bid high to avoid being called. This would make sense for units that want to receive the availability payment but, given their cost con-ditions, would want to be dis-patched only if the energy pay-ment were sufficiently high. A hydroelectric unit might find this to be an attractive strategy during off-peak periods, so that it could capture the availability payment, but keep its water resources avail-able for high on-peak energy prices. Thus, a hydroelectric unit could face a high “opportunity” cost in providing energy during off-peak periods, given that it is constrained in its use of water resources. Note that the above example indicates the potential inefficiency in the California ancil-lary services market that arises from choosing providers based solely on their availability bids. This system could lead the ISO to procure energy from relatively high-cost providers.
IV. “Arbitrage” Opportunities, the Generator’s Decision Problem and Market Efficiency
In an efficient market, the gener-ator should expect, ex ante, to receive the same value (revenues less costs) from either setting aside capacity to provide power in the PX Day-Ahead market or reserv-ing that same amount of capacity, and providing power if called, in
the ISO Day-Ahead ancillary ser-vices markets.22 Since there are multiple Day-Ahead ancillary services markets (i.e., regulation, spinning, non-spinning, and replacement reserves), the expected value from selling any ancillary service should tend to equalize across the other ancillary services to the extent that genera-tors are technically capable of supplying all (or some) of the above ancillary services. Genera-tors, as well as other energy traders, face potential profit opportunities whenever these “equal-value” conditions are not satisfied. For example, generators should shift sales away from markets where the price expectations are lower than in other types of markets. In efficient markets, this “arbitrage” behavior by market participants eventually restores the equal-value conditions.
A. The Generator’s Decision Problem
Consider again the sequence of events in Figure 1. An owner of generation is faced with a series of decisions that must be made with respect to each event. Does it bid into the PX auction or reserve some capacity for the Day-Ahead ISO auction? Does the outcome of the PX auction reveal useful infor-mation for structuring its bids in the ancillary services auction, which in turn might reveal infor-mation useful for the Hour-Ahead markets, and so on. Clearly such considerations are important. The first PX Market Monitoring Report23 found that while some market participants bid in their
Table 3: Percent of Capacity Reserved that Is Called, April 1998 to March 1999, Weekday Peak Hours
marginal costs, others used very elaborate bid curves that varied by the hour. Not surprisingly, the latter often determined the market-clearing price since they were offering the “marginal” units of energy that equated the quantity supplied with the quan-tity demanded.
Figure 8 shows a simplified deci-sion tree facing a generator. We have simplified matters by assum-ing that the generator only can sell its electrical power, or available capacity, through the PX or ISO markets. At each node of the tree, the generator must decide what to do based on events that have occurred previously. Conse-quently, each decision forecloses some opportunities in the future with some probability. For example, selling power in the PX Day-Ahead market constrains the avail-ability of capacity and power that
can be sold in the ISO ancillary services Day-Ahead and Hour-Ahead markets. However, by selling generation into the PX Day-Ahead market, a generator would have its units in operation and thus, be able to sell spinning reserves. Units that were not already in oper-ation could only start up quickly enough to participate in the markets for non-spinning and replacement reserves.
iven these sorts of consider-ations, it is apparent that
generators should want to shift from markets where profits are low to those where they think profits might be higher. This notion applies to relationships among all markets, including the PX Day-Ahead, the ISO Real-Time (i.e., supplemental), and the ISO Day-Ahead and Hour-Ahead ancillary services markets.
B. Arbitrage Opportunities
Figure 9 shows the difference between the SP15 Real-Time and Day-Ahead ex post prices.24 On an hourly basis, the difference is not always positive, and on average here the Real-Time price is below the Day-Ahead price. This is differ-ent than what was presented in Figures 2 and 3, where the instructed Real-Time price was above the Day-Ahead price. This occurs because the instructed real time price and the ex post Real-Time price are different. The Real-Time prices graphed here are the ex post prices which are the Real-Time prices for all hours, not just hours with instructed deviations from load. The ex post price is used to settle non-instructed deviations from load. The instructed Real-Time price is the price paid to units called upon by the ISO from
Figure 8: Simplified Decision Tree of a Generator (Hour Ahead Markets Removed)
the ancillary service or supple-mental energy markets to gener-ate to keep the system in balance. Given that there is a positive probability that there will be no need for instructed Real-Time energy, one would expect the instructed Real-Time price to be higher than the ex post and Day-Ahead prices.
he notion of “arbitrage” opportunities among the vari-
ous ancillary service markets, and between the ancillary services market and the energy market, is specifically addressed in Table 4. The table shows the revenues earned from selling 1 MW of energy into the PX, and compares it to the revenues earned from selling 1 MW of capacity into the markets for spinning, non-spin-ning, and replacement reserves. We have assumed that the proba-
bility that a given MW of ancillary services capacity is called upon to provide energy is equal to the ratio of energy demanded relative to available capacity (for that particu-lar ancillary service).25 The table shows that a strategy of selling 1 MW of energy into the PX every hour would provide more revenue than selling 1 MW of capacity into each of the ancillary services mar-kets. This is to be expected, as
generators incur variable energy production costs by selling into the PX, but generators selling into the ancillary services markets only incur variable production costs during those hours where they are called to supply energy. Thus, all else being equal, genera-tors would need to receive more revenue from selling firm energy than from selling ancillary services.
Table 4 also provides informa-tion about the arbitrage between ancillary services. The similarity in availability payments for replace-ment reserves and non-spinning reserves, as indicated in Table 4, is consistent with the relative ease with which generators may offer up either of these ancillary ser-vices. In fact, a t-test indicates that there is not a statistically signifi-cant difference in the mean avail-ability payment for replacement and non-spinning reserves. Thus, these ancillary services are charac-terized by a high degree of supply-side substitutability (i.e., arbi-trage). On the other hand, the availability payments for spinning reserves are significantly higher than for replacement or non-spinning reserves. Spinning reserves command a higher avail-ability payment because fewer
producers are capable of supply-ing spinning reserves relative to non-spinning and replacement. As a result, although there may be nearly perfect arbitrage between replacement and non-spinning reserves for most generators, that cannot be said for spinning in relation to these other services.
ne would expect that, in choosing electricity markets
in which to participate, generators would sort themselves out based on their marginal costs of supply-ing energy. Thus, generators with relatively low marginal costs would sell successfully into the PX, and consequently, would also be able to offer spinning reserves. Other relatively high-cost genera-tors could not successfully sell into the PX or spinning reserves mar-kets, and would therefore try to
sell non-spinning and replace-ment reserves. In an attempt to delve into this hypothesis, Figure 10 shows the percentage of MWh provided in the instructed Real-Time energy markets by unit type over the course of a day. This pro-vides some indication as to how differences in generation technol-ogy affect the desire and ability to sell ancillary services. Steam tur-bines’ contributions represent the lion’s share of generation in this graph, but that is largely a function of their relative proportion of cycleable units. Hydraulic genera-tion’s share is much more interest-ing. Such providers have very low marginal costs and, thus, could bid into the PX Day-Ahead mar-ket. Recall, though, that Real-Time prices are somewhat higher than Day-Ahead prices. Thus, a hydro unit may find it to its advantage to
Figure 10: Percent of Real-Time MW Called by In Control Area Units (April 1, 1998, to March 31, 1999)
withhold its capacity from the Day-Ahead energy market, then wait and see what is happening and offer its production for Real-Time use. Figure 10 is suggestive of this.
n important point to note is that the different categories
of reserves represent different products because of the different performance requirements, as shown in Table 1. In terms of response time, spin can substitute for non-spin which in turn can substitute for replacement reserve. From this it has been argued that there is a quality ordering with respect to the services in the order of their response time and thus they should be ordered also in their prices.26 In terms of response time and from the perspective of the buyers this is certainly true. If a “higher quality” service is cheaper, why not buy it instead of the “lower quality” one? One diffi-culty with this is that spinning reserve must be on-line. While this might seem to suggest that it would be more expensive, it could be cheaper.27 This is because the generator with the lower startup costs could already be operating to provide energy. Thus, its costs to provide spin could be lower than substituting a higher-startup-cost generator for it. This is a form of “economy of scope in produc-tion.”28 Examining Figure 7 we see that spin, on average on a time-of-day basis, does cost more than non-spin or replacement. Going back to Table 4, note that the expected revenue from selling spinning is higher than non-spinning or replacement. That is,
to determine whether the higher-quality service is getting compen-sated at a higher or lower rate, one needs to look at both the availability and the call energy payments.
While opportunities for arbitrage between the Day-Ahead and Real-Time markets do exist, there are a number of institutional factors that must be taken into consideration. First, because supplemental energy could possibly not be dis-patched due to out-of-merit order dispatch for technical reasons (a
need for faster response, for instance) a low bid is no guarantee of dispatch. For instance, a supple-mental bid of $10 and Real-Time price of $30 do not necessarily imply that the generator will be called on to produce energy. Although we cannot tell how often this happens, it has been a source of concern for many generators. Second, there are no formal mecha-nisms for explicitly buying in one market and selling in another. Indeed, buying on the Real-Time market consists of not covering load through the PX or another Scheduling Coordinator. So, one
buys implicitly on the Real-Time market by “underscheduling.” This seems to be a common occur-rence (see the first PX Market Monitoring Report) though the PX Market Monitoring Commit-tee (MMC) thinks it may be an effort to avoid ancillary service charges.29 Third, the PX warns in somewhat vague terms in its tariff, that generators that sell but do not deliver on the PX Day-Ahead on a too-frequent basis will lose their certification.30 The concern of the PX seems not to be efficiency, but that since the settlement period for the ISO is longer than the PX, a generator selling but not delivering on the PX Day-Ahead gets an interest-free loan from the PX. A better solution may be to charge for actual, not scheduled, load and make those who arbitrage by selling on the PX and buying implicitly in Real-Time pay an interest charge. This way effi-ciency would be improved without encouraging “gaming” of rules.
V. Conclusions
As little analysis has been per-formed of the efficiency of the California energy markets as a group, we have examined whether “arbitrage” possibilities exist in shifting offerings from Day-Ahead to Day-Of or Real-Time Markets, and in shifting offerings between various types of Ancillary Services.31
• Instructed Real-Time prices are generally higher than Day-Ahead prices, which
There are noformal mechanisms
for explicitly buyingin one market andselling in another.
is consistent with what would be expected under efficient market behavior.
• During relatively low-load conditions, covering 80 percent of all hours, market behavior seems to be consistent with some studies’ predictions of a competi-tive model using marginal cost pricing.
• During 10 percent of hours with relatively high loads, the pric-ing evidence suggests the possibil-ity that some market power may be exercised.
• Previous models of the Cali-fornia energy market have ignored the importance of startup costs, and failed to predict the low energy prices observed during off-peak hours as generators essentially bid to avoid shutting off at night (and thereby incur-ring startup costs). Zero energy prices, as observed in California, were not generally predicted by prior models.
• Ancillary services pricing has been quite volatile. Payments to make capacity available have, at times, exceeded the price of the energy itself. This phenomenon raises concerns about market effi-ciency, including the possible exer-cise of market power, in the ancil-lary services markets.
• The close relationship be-tween the availability payments for non-spinning and replacement reserves indicates a large degree of supply-side substitutability (i.e., arbitrage) between these two ancillary services.
The California electricity mar-kets have had a fairly successful start with no large problems in
the mechanics of their operation. As these markets evolve and par-ticipants gain more experience, a number of issues become increas-ingly important. For regulators in California, market power con-cerns and other sources of market inefficiencies, particularly in pro-curing ancillary services, remain important issues for the future. For power producers, there are questions of how and when to best deploy resources into the multiple available electricity mar-kets. For power traders, new and
complicated issues arise with respect to managing market risks. For power consumers, the key issues are limiting market price volatility and choosing the appropriate market in which to purchase power. While producers, consumers, and traders face difficult issues, there are specific techniques available to choose the appropriate market for buying and selling energy, and to appropriately hedge against price uncertainty. However, discussion of these techniques is best left for another time. j
Endnotes:
1. While the discussion of the energy market here involves only the PX, there are other “Scheduling Coordinators” (defined below) that serve as intermedi-aries for purchasing or selling electrical power. These entities provide alternative marketplaces that are available only to certain market participants. As the regu-latory obligation to participate in the PX recedes, it will be interesting to see how the role of these Scheduling Coordina-tors evolves.
2. This might change due to the faster-than-expected recovery of stranded costs.
3. Roger E. Bohn, Alvin K. Klevorick, and Charles G. Stalon, Second Report on Market Issues in the Cali-fornia Power Exchange Energy Mar-kets, Market Monitoring Committee of the California Power Exchange, March 9, 1999.
4. The PX began a Block Forwards Mar-ket on June 10, 1999. The market consists of bids for 16-hour blocks (from 6 a.m. to 10 p.m.) for each on-peak day (all days except Sundays and some holidays).
5. The Day-Of market replaced the PX Hour-Ahead market on Jan. 19, 1999. Both markets are similar in the fact that their primary purpose is to allow partici-pants to adjust their Day-Ahead sched-ules as the hour of actual energy flows approaches. The Hour-Ahead market consisted of one separate auction for each hour of the day. The Day-Of market consists of hourly bids, but only three separate auctions are conducted for the entire day.
6. Entities selling energy through the PX cannot self-provide the ancillary services associated with those energy sales.
7. Prior to Aug. 9, 1998, the ISO used scheduled load to determine its ancil-lary service requirements. Under-scheduling of load led the ISO to make the change.
8. That is, unless they were subject to FERC caps. Until Nov. 3, 1998, the major-ity of units in California were subject to FERC-based caps on the amount they
Payments to make capacity available have, at times, exceeded the price of the energy itself.
could receive for providing capacity for ancillary services.
9. The ISO has proposed in Amendment 14 to develop a “rational buyer” approach to the ancillary service mar-kets. Instead of settling the ancillary markets sequentially, it proposes to procure more lower-priced, higher-quality services to substitute for higher-priced, lower-quality services, whenever possible.
10. Loads may submit supplemental energy bids also.
11. It has been reported that units are sometimes called out of order by the ISO. One of the reasons for this is techni-cal. Since instructions for many genera-tors have to be given by phone, when time is short, rather than try to call many small generators, the ISO calls a few big ones. These bigger generators might have higher prices than the small, uncontacted generators. The ISO is undertaking steps to rectify this techni-cal problem in Amendment 14 to the ISO Tariff.
12. These prices are weighted by the amount of MWh sold or procured in each market for each hour. The PX Day-Ahead average hourly price is weighted by the PX Day-Ahead hourly sales. The Real-Time average weighted price reported here represents the Real-Time price only in the hours where units were instructed to increment their generation. It is weighted by the amount the units were instructed to increase their generation. This price represents the average energy price paid to units for their ancillary service energy production.
13. Elec. Util. Wk., Oct. 5, 1998, at 7.
14. The Second PX Market Monitoring Report, supra note 3, has a table that indi-cates that on an average monthly basis the PX Day-Ahead price is above the Real-Time price. This is because they are not weighting their prices by MWh, and are looking at the Real-Time price for all hours (the ex-post price), not just when there is instructed generation, as we did. One question of interest is which presen-tation best indicates arbitrage opportuni-
ties? This issue is discussed later in this article.
15. Id., at 16.
16. For further discussion, see Robert L. Earle, Philip Q Hanser, and Frank C. Graves, Power Market Price Forecasting: Pitfalls and Unresolved Issues, Proceedings of the IAEE/USAEE, Oct. 1998.
17. LCG Consulting (Los Altos, Calif.), Modeling Competitive Energy Market in California: Anal-ysis of Restructuring, prepared for California Energy Commission, Oct. 3, 1996. Principal investigator Rajat K. Deb, co-investigators Richard S. Albert and Lie-Long Hsue.
18. Severin Borenstein and James Bushnell, An Empirical Analysis of the Potential for Market Power in California’s Electricity Industry, University of California Energy Institute, Sept. 1997.
19. Regulation, the fourth competitive ancillary service, has been excluded from the graph.
20. Another characteristic of these reserve call options that has generated some controversy is that they are pur-chased based on the cost of the premium alone, not taking into account the strike price. Wilson justifies this under a set of assumptions open to some question, including no unit commitment costs and “perfect” competition. Robert Wilson, Priority Pricing of Ancillary Services in Wholesale Electricity Markets, paper pre-sented to Maryland Auction Conference, May 29-31, 1998.
21. As part of its ancillary service re-design, in Amendment 14 the ISO has proposed having two different markets for upward and downward regulation.
22. Technically, value represents “eco-nomic” profits, which are adjusted for risk. The following analysis does not examine risk specifically, since we pre-sume that any differentials in risk-adjustment factors across the various energy and ancillary services markets are relatively small in magnitude, given that these markets are conducted no more than one day in advance of the actual provision of services.
23. Roger E. Bohn, Alvin K. Klevorick (Chair), and Charles G. Stalon, Report on Market Issues in the Cali-fornia Power Exchange Energy Mar-kets, The Market Monitoring Committee of the California Power Exchange, Aug. 17, 1988.
24. The Real-Time prices graphed here are the ex-post prices which are the Real-Time prices for all hours, not just hours with instructed deviations from load. The ex-post price is used to settle non-instructed deviations from load.
25. This assumption effectively treats all providers of a particular ancillary service as putting in identical energy bids. In this circumstance, the choice of who sup-plies the energy may be considered ran-dom.
26. See Frank Wolak, Robert Nord-haus, and Carl Shapiro, Preliminary Report on the Operation of the Ancillary Services Markets of the California Independent System Operator, California ISO Market Sur-veillance Committee, Aug. 19, 1998.
27. Of course, in a market, generators as discussed above will try to maximize profits. The point is that the cost of providing spin could be lower.
28. See Dennis W. Carlton and Jeffrey M. Perloff, Modern Indus-trial Organization 70–74 (2d ed., Harper Collins, 1994). Also see their discussion at 79–83 of cost concepts for multi-product firms.
29. Another reason that loads might underschedule, might be to lower their overall energy costs by lowering the mar-ket clearing price in the PX. For example, if underscheduling caused 90 percent of their load to receive a 10 percent price reduction, and the remaining 10 percent that must clear in the Real-Time market to receive a 10 percent price increase, overall the costs will decrease 6 percent.
30. See Section 6.25 of PX Tariff.
31. As this article was written, the Cali-fornia ISO Market Surveillance Unit in June issued its Annual Report on Mar-ket Issues and Performance that dis-cusses many aspects of market efficiency.
