EXHIBIT 99.307
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A REPORT TO THE CALIFORNIA POWER
EXCHANGE:
ITERATIVE BIDDING IN THE PX MARKET
January 28, 1999
Dr. Peter H. Griffes
ANALYSIS GROUP / Economics
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A REPORT TO THE CALIFORNIA POWER EXCHANGE:
ITERATIVE BIDDING IN THE PX MARKET
I. INTRODUCTION AND PURPOSE OF STUDY...........................................................3
II. DESCRIPTION OF ITERATIVE BIDDING............................................................5
A. PURPOSE OF ITERATIVE BIDDING.............................................................5
B. DESCRIPTION OF ACTIVITY RULES............................................................6
1. Opening rule..........................................................................6
2. Revision rule.........................................................................6
3. Exclusion rule........................................................................8
4. Withdrawal rule.......................................................................8
5. Closing rule..........................................................................8
C. EXAMPLE OF ACTIVITY RULES................................................................9
III. STATUS OF ITERATIVE BIDDING IN THE PX MARKET...............................................11
A. PRIOR TO THE OPENING OF THE MARKET......................................................11
B. SINCE THE OPENING OF THE MARKET.........................................................12
IV. SUMMARY OF RESEARCH DONE IN JUNE 1998......................................................12
A. BENEFITS FROM ITERATIONS................................................................13
1. Review of London Economics study.....................................................13
2. Theoretical Benefits.................................................................14
B. COSTS OF ITERATIONS.....................................................................15
1. Feasibility constraints..............................................................16
2. Strategic behavior...................................................................21
3. Transactions costs...................................................................23
C. INTERVIEWS WITH PARTICIPANTS............................................................24
D. CONCLUSIONS FROM JUNE 1998 STUDY........................................................25
V. SUMMARY OF RESEARCH DONE IN NOVEMBER 1998..................................................26
A. EXCERPTS FROM 'BETA TEST OF ITERATIVE BIDDING IN THE PX DAY-AHEAD MARKET'...............27
B. COMMENTS AND OBSERVATIONS FROM NOVEMBER RESEARCH........................................30
1. Comments on results..................................................................30
a. The report's discussion..............................................................30
b. The report's omissions...............................................................31
c. Interpreting the report's results....................................................31
2. Comments on interviews...............................................................35
a. Benefits and costs...................................................................36
b. Concerns about gaming................................................................36
C. CONCLUSIONS FROM NOVEMBER RESEARCH......................................................37
VI. CONCLUSIONS................................................................................39
VII. SOURCES.................................................................................40
APPENDIX A: SURVEY RESULTS......................................................................41
APPENDIX B: ITERATIONS RESULTS FOR BETA TEST....................................................44
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I. INTRODUCTION AND PURPOSE OF STUDY
In the original design of the PX energy market, iterations were a feature of the
auction design. Iterations were to allow allowed suppliers a chance to adjust
their bids to better achieve feasible schedules. In approving the market design,
FERC had some questions about the efficiency of design of the iterations in the
market. As a condition of approving the market structure, FERC required further
study on this topic.
In its October 30, 1997 decision conditionally approving the market structure
FERC states:
We will require that the PX conduct additional studies to further evaluate
the proposed auction, which must be completed and submitted to us by January 1,
1999. The studies should analyze whether the Phase II auction results in an
efficient, least-cost dispatch. The effect of limiting the number of iterations
in the Phase II auction (so that the auction may terminate before reaching an
equilibrium) should be explored, since the ISO/PX proposes only one round of
bidding initially, and only five rounds of bidding later on. Also, the effects
of transmission congestion and the existence of no-load costs on the part of
generators should be explored for each auction.
The studies should also examine the effects of the regular repetition
of auctions involving the same participants and similar costs from day to day.
The studies should pay specific attention to the susceptibility of the auction
format to overt and tacit collusion and the potential to exercise market power.
This report addresses some of the issues raised in the evaluation and possible
implementation of iterative bidding in the market. It describes the research
effort sponsored by the PX on the topic of iterative bidding in the last year.
The research has been motivated for the purpose of addressing the possible
implementation of the market iterations, and not for the purpose of explicitly
answering the questions raised by FERC in its decision.
The PX has not yet implemented iterations into its market. In evaluating
possible implementation of iterations, there has been significant concern that
the costs imposed on the PX and market participants would significantly outweigh
the benefits that may result. Consequently, the PX Board has postponed the
implementation of iterative bidding indefinitely.
In coming to this stance, the PX has undertaken two separate episodes of
research. The first was in June 1998. The purpose of the June research was to
assess the need for iterative bidding in the market and explore issues
pertaining to its implementation. In particular, there were concerns whether
there would be enough time for iterations and how much iterations would burden
participants. Further, opportunities for strategic behavior (or gaming) were
identified
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and discussed in the June research. A number of issues would have to be
addressed before implementing iterations.
The June research summarized the purpose of iterations in the market and the
possibility of increasing efficiency through iterations. It described the
revision rules and how they would work to move prices. The research explicitly
laid out the benefits from iterations and identified three costs to
implementation. The costs are feasibility constraints; strategic behavior and
transactions costs. In each of these areas, previous research was summarized and
considered.
The second episode of research was in November 1998. Between June and November,
the PX developed software to be able to undertake iterations. One of the
purposes of the research was to test that the software performed as it should.
Thus, market simulations were run with PX participants for five separate days in
early November.
In revisiting iterations, many of the same issues were raised including benefits
from iterations, feasibility of having enough time for a sufficient number of
iterations, transactions costs imposed on participants. The PX realized that
many of the benefits and costs of iterations would accrue to participants, so it
conducted a formal survey of participants after the market simulations were
complete. As described by participants, the costs of implementing iterations
outweighed the benefits they would produce. Consequently, the PX postponed
indefinitely the introduction of iterations.
The November research highlights the benefits to the demand side of the market
of seeing energy prices before deciding how much to buy from the day-ahead,
hour-ahead and real-time markets. This could be a significant benefit from
iterations.
Further the November results display market price and quantity movements that
are consistent with strategic behavior on the supply side of the market.
However, results are also consistent with unprofitable portfolios exiting the
market. Further investigation would be needed to determine whether suppliers
were manipulating the price in these tests. The research did not reveal price
and quantity movements that suggest strategic behavior on the demand side of the
market. However, such behavior is possible. Because the interests are
diametrically opposed, it is not clear what the value of iterations would be
when both suppliers and demanders are behaving strategically. More research is
needed on this topic.
The rest of the report is laid out in the following manner. Section II provides
a description of iterative bidding. It specifies the benefits from iterations
and works through examples of the revision rules applicable to the iterative
process. Section III provides a brief history of the consideration of iterations
in the PX market. Section IV describes in some depth the research effort
undertaken in June 1998. The research specifies the costs and benefits
associated with adopting iterations into the market. Section V summarizes the
Beta Tests that took place in November 1998. Besides reporting the conclusion
made at that time, it discusses in some detail some of the results and
implications of the research that was done. Section VI concludes the report.
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II. DESCRIPTION OF ITERATIVE BIDDING
A. PURPOSE OF ITERATIVE BIDDING
Iterative bidding in the day-ahead PX market allows market participants to
change their bids in response to prices revealed in earlier rounds of the
auction. This price discovery process assists suppliers in securing feasible
production schedules. It also provides information to suppliers so they can
calculate their revenues and costs to determine whether they will be able to
recover their relatively fixed costs attributable to start-up and no-load. It
also allows them to adjust their bids (or withdrawal) to improve their financial
position.
The design of the PX day-ahead energy market is a one-part energy bid. The
bidding instrument is a 15-segment linear bid curve that must be increasing in
the price over the entire quantity offered. Bidders can submit separate bid
curves for each of 24 hours in the day-ahead auction. As such, bidders are
expected to bid in such a way as be able to cover their costs with the awards
and prices. Further the PX evaluation process evaluates each hourly market
independently of all other hours. Thus, an award in one hour does not insure
awards in adjacent hours.
Some of a generator's costs are avoidable by not starting, but once started act
like fixed costs. In particular, start-up energy costs become a sunk cost once
the generator starts. No-load costs are avoidable if a generator shuts off, but
are fixed for each hour of operation. The bidding structure does not explicitly
account for recovering these costs. These costs may need to be recovered on a
daily basis, thus, bidders would need to incorporate recovery of these costs
into their bids. Nonetheless, there is no simple way to do this and be assured
that resulting schedules will be feasible or allow full recovery of costs.
Iterative bidding is a way for bidders can get some idea about prices and awards
without being financially obligated for meeting generator schedules. Iterative
bidding would allow participants the opportunity to change their bids in
response to quantities and prices revealed in earlier rounds of the auction.
Bidders may also be able to withdrawal from the auction entirely if prices are
not high enough to provide sufficient revenues to cover costs. This will allow
bidders to adjust their schedules through the iterative process, resulting in
feasible production schedules.
Iterations are a risk management tool that hedges against potential losses due
to infeasible schedules. Suppliers with large portfolios can allocate production
across units to meet their awarded quantities and recover costs. Suppliers with
small portfolios or single units are much more vulnerable. They run a greater
risk of not recovering start-up and no-load costs. Similarly, hydro generation
can better allocated scare water resources to periods that will provide the most
value.
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In order to ensure the market converges to a suitable price and quantity for all
participants. Activity rules limit the ways in which bids can be revised.
Essentially, suppliers must lower their bid prices through the iterations while
demanders must increase their bid prices. The activity rules determine how
quickly the auction will converge on an equilibrium.
B. DESCRIPTION OF ACTIVITY RULES
This section will discuss in some detail the activity rules proposed by the PX
for its iterative auction. The iterative auction uses these rules to govern how
bidders can change their tenders. The rules were designed to provide quick and
decisive price discovery. They attempt to limit strategic behavior by bidders
who may try to signal false quantity and price information in order to benefit
themselves. The bidding rules also encourage timely convergence to an
equilibrium. Five activity rules have been proposed for the PX market. Each will
be discussed briefly.
1. OPENING RULE
The Opening Rule describes how supply and demand bidders initially submit
tenders. Under the proposed PX iterative bidding protocols, each market
participant wishing to participate in the auction must make a bid in the first
iteration. No new bids will be accepted after the first iteration. The purpose
of the opening rule is to be sure that all quantities in the market are
represented at the beginning of the auction. Without an opening rule, agents may
hold back their bids to discover information about other participant's
valuation. After seeing how others in the market value output, the withholders
can formulate their bids to work to their advantage. Anyone bidding at the first
of the market is disadvantaged by this behavior.
2. REVISION RULE
The revision rule dictates how bidders can change their bids between iterations.
The rule only allows for prices to be revised; quantity levels cannot be
changed. If suppliers choose to revise their bids, the rules require that they
must lower the prices at which they are offering to sell. Similarly, it requires
buyers who want to adjust their bids, to increase the price at which they are
willing to buy.
The hourly bids into the market take the form of 16 price-quantity combinations
that are connected by straight lines to form the bid curves. Each price-quantity
combination is called a breakpoint. Supplier's breakpoints must be increasing in
prices and quantities. Demander's breakpoints must be decreasing in prices and
quantities. The first and last points define the bidder's minimum and maximum
quantities. To be in the market, each participant must submit hourly bids for
each of the 24-hours of the day
In particular, the revision rule requires that, a supplier (buyer) must lower
(raise) the price of a breakpoint in the next iteration if it wants to keep that
breakpoint active. In each iteration i, the
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PX calculates a market-clearing price (MCP(i)). This MCPi defines what portions
of the bid are active or passive for iteration i+1. The active portion of the
bid curve defined as the segment with breakpoints above MCP(i). These
breakpoints are extra-marginal. The passive portion of the bid curve is the
segment with breakpoints below MCP(i). These breakpoints are infra-marginal.
Figure 1 illustrates the definition of active and passive breakpoints on a
supply curve. Points A, B, and C represent breakpoints above the MCP from the
first round. The revision rule requires that for these three breakpoints (A, B
and C) to remain active, the supplier must lower their price to a level below
MCP(1). The bidder need not adjust its bid at all; however, as will be discussed
below in the exclusion rule, the bidder will not be able to adjust these
breakpoints in subsequent iterations of the market.
FIGURE 1: EXAMPLE OF ACTIVE AND
PASSIVE BREAKPOINTS
[GRAPH]
The revision rule requires suppliers to lower the price for each active
breakpoint below MCPi if the breakpoint is to remain active. Passive breakpoints
do not have to be revised, but can be if the supplier decides to lower them as
well. An analogous rule applies to demand bidders. Namely, the adjustment to any
break points must be in an increasing direction.
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3. EXCLUSION RULE
As mentioned above, the exclusion rule freezes active breakpoints that are not
revised at the first opportunity in subsequent iterations. Frozen breakpoints
cannot be changed as long as the market price is falling. This rule requires
bidders to lower their prices in each iteration if they want to be able to
adjust the bid in subsequent iterations.
More formally, any breakpoint on the supply tender becomes frozen in the current
iteration (i) if: the breakpoint was active in iteration (i-1) because the
breakpoint's price exceeded MCP(i-1) and the breakpoint's price is not lowered
in iteration (i) to be less than MCP(i-1). This means a supplier must lower its
price bids below the MCP if it wishes to be able to adjust those parts of the
bid in subsequent rounds.
A breakpoint is always frozen relative to the MCP of the previous iteration.
Specifically, suppliers can always adjust a breakpoint if they have adjusted it
below the MCP from the previous round. If a breakpoint has become frozen, it can
only be adjusted if it is "un-frozen" in subsequent iterations if the price
rises. For a breakpoint frozen in iteration i, MCPi-1 is the breakpoint's
activation price to un-freeze it. A bid is no longer frozen if the MCP in
subsequent iterations (i+1) rises above the activation price, MCPi-1.
Demand side bidders have analogous exclusion rule, where they must increase the
price portion of the bid to be able to adjust it in subsequent iterations.
The exclusion rule forces suppliers to commit to progressively lower prices when
prices are falling between iterations or to signal that they can sell at no
lower price. Similarly it forces demanders to commit to progressively higher
prices when prices are increasing between rounds or to signal that they cannot
buy at any higher price.
4. WITHDRAWAL RULE
The withdrawal rule allows bidders to remove its entire tender from an hourly
market at the end of an iteration. A supplier may pull its portfolio if prices
are iterating to levels that may be insufficient to cover the its costs.
Alternatively, a buyer may pull its portfolio if prices are iterating to levels
that impose too great of a cost on consuming.
However, there are some restrictions on this withdrawal. All portions of the
hourly tender must be withdrawn. Perhaps more importantly, the tender cannot be
re-offered in subsequent iterations once it has been withdrawn. Further,
withdrawal can occur at the end of any iteration except for the final iteration.
Once the auction has finished, no accepted bid can be withdrawn.
5. CLOSING RULE
The closing rule governs when the auction terminates and awarded prices and
quantities are finalized. All hourly markets will close simultaneously. The
iterative process will be
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terminated when one or more of the following has occurred. First, the auction
will end when no notable improvement is made in a MCP from prior iterations.
Second, the market closes when no valid bid revisions are received from the
previous iteration. Specifically, the active bidders choose not to make
improvements to their bids. Third, a maximum number of iterations is reached.
Fourth, the time allotted for iterations elapses. Under these last two rules,
the auction may not have iterated to its equilibrium values.
C. EXAMPLE OF ACTIVITY RULES
This section describes an example of the bidding rules in effect. The purpose of
this exercise is to show how a tender can be changed under these rules. The
example will focus on a supply bid. An analogous example could be constructed
for the demand side of the market.
Figure 2 describes a supply curve tendered at the opening of the market and the
resulting MCP and awarded quantity at the end of the first iteration. MCP1 is
the market-clearing price from the first iteration. Three of the bids break
points are active at this point, namely, A, B and C. The bidder has the choice
of adjusting its bids or remaining satisfied with its bids. It should be
highlighted that other bidders are likely to adjust their bids. Thus, this
bidder would likely end up with a quantity less than Q1 if it did not adjust its
bids.
FIGURE 2: SUPPLIERS' INITIAL TENDER
[GRAPH]
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In this example, suppose the supplier decides to adjust two of these
breakpoints, A and B, before the second iteration. While the bidder could adjust
the price associated with A and B to a level greater than MCP1, this would mean
that it could not make any further adjustments in subsequent iterations unless
the price were to go above MCP1. Assume the bidder wants to keep these
breakpoints active, it must then set their prices below MCP1.
This can be seen in Figure 3. A new bid curve results, containing A1, B1 and C.
Again C is not revised, reflecting the supplier's unwillingness to supply QC at
a lower price.
FIGURE 3: SUPPLIER LOWERS BREAKPOINTS
[GRAPH]
After bids are submitted in the second iteration, the PX calculates MCP(2). This
can be seen in Figure 4. In this example, MCP(2) < MCP(1), but this is not
necessary in all cases. By lowering the bid prices associated with A and B, the
bidder has increased its awarded quantity. Namely Q(2) is greater than Q(1). The
level of MCP2 renders A passive. As long as subsequent MCPs do not drop below A,
this breakpoint remains passive. Since it is above MCP(2), B is an active
breakpoint. The supplier must lower the price for B in the next iteration or
risk freezing B at its current bid price. Breakpoint C is frozen because its
price was not lowered below MCP(1) when bids for iteration 2 were made. It
cannot be adjusted unless a subsequent MCP moves above its activation price,
MCP1. If subsequently MCP rises above MCP1, breakpoint C is unfrozen and becomes
active or passive, depending on the MCP(i+1).
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FIGURE 4: RESULT OF ITERATION 2
[GRAPHIC]
This example provides insight into how the bidding rules are designed to work in
the market iteration process.
III. STATUS OF ITERATIVE BIDDING IN THE PX MARKET
A. PRIOR TO THE OPENING OF THE MARKET
Before the initial filing, iterative bidding came up in the discussions of
market design. A single-part bidding structure with iterations was proposed as
an alternative to a multi-part bidding mechanism. Iterative bidding was part of
the market design that the PX submitted to the FERC in its in March 1997 Phase
II filing. Much of the market rules and mechanism were still being worked out.
In the design and implementation of the market, time constraints became binding.
Part of the problem was the requirement for coding of software to implement the
market before all design issues had been worked out. The impending opening of
the market and resolving difficult
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design and implementation problems forced the PX to delay the introduction of
iterative bidding. In October 1998, FERC approved the delay of iterative bidding
until after the opening of the market to be implemented in June 1998.
B. SINCE THE OPENING OF THE MARKET
In June of 1998, there were still many issues to be resolved before iterative
bidding could be introduced. With the delay in the opening of the market and
other design features that still needed to be introduced. There was some concern
about the introduction of iterations. While there appeared to be theoretical
benefits to iterations, there were also unforeseen costs of implementing such a
mechanism. These included finding the time for the market to iterate. At that
time, an assessment of the role of iterative bidding was done.
While this report will examine the results of this assessment in greater detail
below, the research involved examining how iterations would fit into the
schedule. Concerns about the adequacy of time schedule were significant, both on
the part of the PX and its participants. Interviews examining the costs and
benefits of iterations were done with market participants. At that time,
iterations had been scheduled for implementation in August 1998. However, as a
result of that research effort, the PX board decided to delay further the
implementation of iterations. It also decided to undertake more research and
revisit the issue in the fall.
The issue of iterations came before the board again in November 1998. Prior to
this consideration, a beta test of an iterative mechanism was performed. In the
test, market participants were given the opportunity to bid in an iterative
fashion. After the tests, interviews were conducted with participants. Again the
research done in the fall will be discussed in greater detail below.
In November 1998, the PX board decided to postpone indefinitely the introduction
of iterative bidding into the market. The general conclusion was that, while
some participants may find it helpful, implementing iterations would impose
significant cost on the PX and participants. The PX would have to refine the
mechanism to avoid gaming. Further, market participants would have to incur
significant costs to be able to take advantage of the iterative process. Also,
bid strategies and cost recovery mechanisms from a single shot auction had been
worked out over time.
IV. SUMMARY OF RESEARCH DONE IN JUNE 1998
This section will discuss the research that was conducted in June 1998. The
research effort focused on the issue of whether the benefits of the introduction
would outweigh the costs imposed of the market. The research was qualitative in
nature; specifically, it did not attempt to quantify the costs and benefits of
the introduction of iterative bidding. Benefits were examined. Previous
quantitative estimates of benefits were reviewed. Theoretical benefits were
enumerated. Cost were also specified including, feasibility constraints,
strategic behavior, and
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transaction costs. Finally, interviews were conducted with market participants
to gain their insights into the introduction of iterations. The findings of each
of these areas will be summarized below.
A. BENEFITS FROM ITERATIONS
1. REVIEW OF LONDON ECONOMICS STUDY
There were a number of studies done on the iterative bidding mechanism. Robert
Wilson, Charles Plott and London Economics completed these studies. Each of the
studies has been filed with FERC at various stages of the proceedings approving
the market structure. The research done by Wilson and Plott focused on the
efficiency of the auction mechanism, particularly, the bidding and activity
rules. The research completed by London Economics addressed the overall
efficiency of the market from the delay of various market features, including
iterations. Because of its focus on quantification, particular attention was
paid to the London Economics study.
London Economics completed research in September 1997. Among other market
features, the study examined the loss in efficiency caused by staging iterative
bidding. The LE study considered the efficiency of the PX market with the
without iterative bidding. The methodology used a market simulation technique
that assumed bidding behavior by market participants. The differences between
the results in the single-shot market and the iterative market provide a basis
to quantify the potential benefits of iterative bidding.
The study compared single-shot versus iterative bidding by measuring three
different impacts. First, the study compared the market prices with and without
iterative bidding to determine how much they would change. Specifically, it
measures how well the resulting prices indicate the cost of the generators that
are chosen in the auction. Second, the differences in total thermal generation
costs under single-shot versus iterative bidding were measured. This measures
what the efficiency loss on the supply side between the cases by not having the
least cost generators producing. Third, the quantity of capacity that would
change under iterative bidding was examined. This variable measures how much
capacity would be producing with iterations that would not be producing without
iterations. It indicates how much trade between generators changes.
In terms of methodology, LE used a simulation model that accounts for underlying
generator costs and formation of bids. Two different methods were used to
estimate results with and without iterations. First, to simulate one-shot
auctions, the model was first used to produce optimal bids, market prices and
generation schedules assuming perfect information about demand and supply
conditions for "typical" spring, summer and winter weekdays. The resulting bids
were then fixed. These fixed bids were submitted for a series of 20 days, each
with different demand and supply conditions. Given the variation in supply and
demand
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conditions, the fixed bids could only approximate the optimal bids for
those conditions. The results of these runs indicate how bidders would fair
without iterations.
These results were compared to the bids produced using iterative bidding. Under
these conditions, the same series of 20 days were used to allow bidders to
iterate to a market solution. The difference between the results without
iterations and the results with iterations measures the impacts on not having
iterations.
There were five different scenarios run for this comparison. These scenarios
vary with the amount and type of uncertainty introduced into the market. One
demand side scenario reflected the possibility of demand being different than
expected. Three supply-side scenarios reflecting different levels of uncertainty
in the availability of supply with cases for 1%, 3% and 5% difference from
expected. Finally, a scenario was constructed with both the demand uncertainty
and supply uncertainty.
Table 1: Results from London Economics Study
PARAMETER WINTER SUMMER
--------- ----------------------------- --------------------------------
Allocative Thermal Allocative Thermal
Effc'y Cost Trade Effc'y Cost Trade
---------- ------- ----- ---------- ------- ------
Demand uncertainty 0.1% 1.1% 3.8% 0.1% 3.9% 8.1%
1% supply uncertainty 0.0% - - 0.3% - -
3% supply uncertainty 0.0% 1.8% 10.3% 1.0% 3.0% 12.2%
5% supply uncertainty 0.0% - - 0.9% - -
Combined 0.3% 2.5% 10.3% 0.8% 3.8% 12.2%
Table 1 contains the results of the London Economics study for each measure for
each scenario. The deadweight efficiency loss from the lack of iterations
indicates the societal loss from lack of iterations is .3 to .8% of the total
market value. This means that market prices under a single-shot market are
within one percent of those resulting under iterations. The research showed that
the costs of thermal production could be as high as 3.9% higher without
iterations than with iterations. The trade number indicates how different
generators' outputs were with and without iterations. This difference was as
much as 12% of average market demand. Of course, this benefits some generators
and costs others.
2. THEORETICAL BENEFITS
The theoretical benefits from iterations are much the same as those described
above in section II.A. As described there, iterations enhance the ability to
submit feasible schedules. They also allow better recovery of start-up and
no-load costs. Iterations are a risk management tool for smaller portfolio
bidders. Each of these benefits is based on the reduction of uncertainty bidders
gain from iterations.
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Supply bidders face uncertainty as to the prices that will prevail in the
market. With a better idea of prices, it is easier to formulate bids that will
allow sufficient production to ensure the recovery of costs. The benefits from
iterations come from reducing uncertainty. Iterations will have a greater value
if they reduce more uncertainty. It is possible that iterations could increase
uncertainty if they are sufficiently abused to signal false valuations.
Over time, there has been a reduction of benefits from the introduction of
iterations in the market. This has come from greater knowledge of the market and
introduction of other risk management tools.
The novelty of the market has been a source of uncertainty. As time passes, the
history of market operation extends. Participants gain greater experience with
predicting market conditions. Thus, participants can better assess their ability
to recover costs and schedule output, and gain less of a benefit from the
introduction of iterations.
The value of iterations also depends on the availability of other risk
management instruments. For example, the introduction of the hour-ahead market
reduced supplier's exposure to infeasible schedules since the quantities
associated with feasible schedules could be more easily bought or sold.
Consequently, as other risk management instruments have been introduced, the
benefits of iterations are reduced.
To summarize the benefits from iterations, smaller portfolio bidders may gain a
benefit since they would be able to better avoid infeasible and unprofitable
schedules. The London Economics study shows a modest gain in societal efficiency
from iterations altering the price of energy. It also showed a reduction in
production costs and reallocation of generators providing power. Finally, the
benefits from the introduction are reduced over time as more market experience
occurs and risk management instruments introduced.
B. COSTS OF ITERATIONS
The research effort in June identified three categories of costs of introducing
iterative bidding into the market. They are feasibility constraints, strategic
behavior and transaction costs. Feasibility constraints address how easily the
iterative procedures could be incorporated into the PX's market and scheduling
process. The value of iterations comes from the ability of bidders to adjust
their offers. If there is insufficient time to make adjustments, the benefits of
iterations could be significantly reduced. Strategic behavior involves the
ability of participants to signal others a false valuation in order to take
advantage of the responses to the false valuation. While this sort of behavior
is not encouraged, participants who do this may be operating well within the
market rules. This type of behavior may produce inefficient prices. Transaction
costs address the cost to participants of operating in the market. The
introduction of iterative bidding may increase the costs born by participants to
buy and sell in the PX day-ahead market. Each of these cost categories will be
discussed in detail.
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1. FEASIBILITY CONSTRAINTS
As mentioned above, feasibility constraints address how easily the iterative
procedures could be incorporated into the PX's market and scheduling process.
This discussion addresses the overview of the problem and offered potential
solutions. One of the outstanding issues centered on the number of iterations
needed to ensure convergence of the market.
The feasibility constraints focus on the central question of whether there is
enough time to incorporate iterations into the market. For iterations to be
effective, a sufficient number need to be incorporated into the auction process.
However, there was serious question as to the number needed and how long each
iteration should last. For iterations to be effective, it is necessary to adjust
the auction and scheduling timetable to get the number and frequency of
iterations correct. It appears to be a challenge to accommodate the correct
duration and number into the market process. Figure 5 illustrates three steps
and the time associated with each.
FIGURE 5: THE CURRENT MARKET SCHEDULE
[GRAPHIC OMITTED]
It is highly likely the market schedule may have to be adjusted for iterations
in order to introduce them effectively into the market. Bids are submitted
between 5:00 and 7:00 a.m. to the PX. Some participants submit bids the night
before. Most participants refine their bids throughout this two-hour period and
re-submit tenders up until the deadline. The distribution of submission times in
April and May can be seen in Figure 5. Each diamond represents a bid
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submission. Most bids are submitted between 6:15 a.m. and 7:00 a.m. It is not
clear whether participants need the full two hours to submit bids. Closing the
period for bid submissions earlier may be one way to make more time for
iterations.
FIGURE 6: TIMING OF BIDS
APRIL & MAY 1998
[GRAPH]
After bidding closes at 7:00 a.m., the PX officially has an hour to calculate
the market-clearing prices for each hour. This is the time frame that is
currently set aside for iterations if they were to be introduced. On average,
the PX is able to calculate and post market-clearing prices by 7:15 a.m.
Currently the extra time available between 7:15 and 8:00 is used to increase the
time for bidders to break their awards into schedules and develop adjustment and
ancillary service bids. The hour period from 7:00 to 8:00 a.m. may or may not
provide sufficient time for the market to iterate. This will depend on the
number of iterations needed and the time required for effective bid alteration
to be made.
It may also be possible to cut into the time bidders have to schedule. In this
1.5 hour time period, bidders must create initial preferred schedules, ancillary
services bids and adjustment bids. Participants, particularly those with large
portfolios, have difficulty meeting the 9:30 submission deadline. Figure 7
illustrates the distribution of times at which bidders submitted schedules in
April and May, 1998. Notice that some participants take nearly the full period
allotted for submitting schedules. It should be highlighted that this includes
the leftover time
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from the PX's calculations. It appears that this is the least feasible place to
be able to increase the time for iterations.
FIGURE 7: SUBMISSION OF SCHEDULES TO PX
APRIL & MAY 1998
[GRAPH]
There are four possible options for altering the market schedules for iterations
to take place. They are, make no change, start the market earlier, extend the
market long and a combination of starting earlier and extending the market
longer. Each option will be discussed briefly.
The first option is to maintain the current schedule. Under this alternative,
iterations would start at 7:00 a.m. All iterations would need to be completed
within one hour (from 7:00 - 8:00 a.m.). Under the current schedule, the PX
would need to publish its first price by 7:15 a.m., leaving approximately 45
minutes for subsequent iterations. Depending on the iteration length, this would
leave only a relatively small number (less than 10) iterations for convergence
to take place. This approach would risk the possibility that the market does not
converge before the hour has ended.
The second option would be to start the market earlier. Instead of the market
being open from 5:00 a.m. to 7:00 a.m., the PX would stop accepting bids at
perhaps 6:00 a.m. Iterations would then start at this earlier hour after the PX
has calculated an initial price. They would last until 8:00 a.m. when the
schedule continued as previously. This would allow in the neighborhood of
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2 hours for iterations. Starting the market earlier would put the burden on
generators to begin the bidding process in the early morning hours. Generators
would also have to commit quantities farther in advance of delivery, increasing
the uncertainly of operation.
The third option is to cut the schedule time. Again iterations would start at
7:00 a.m. but would continue into the time period previously reserved for
scheduling until perhaps as late as 9:00 a.m. The length of the extension is
limited by the ISO's scheduling process that requires initial preferred
schedules to be submitted by 10:00 a.m. This option would provide as much as two
hours for iterations and convergence. However, this timetable leaves little time
for bidders to translate their awarded quantities into generators schedules and
ancillary services bids. In the present single-shot market, submitting
scheduling, incs/decs and ancillary service bids is the most time-constrained
activity.
FIGURE 8: POSSIBLE SCHEDULE OPTIONS
FOR THE ITERATIVE MARKET
[GRAPH]
The final option would be to start the market earlier and extend the market into
the scheduling period. This combines the second and third options, by starting
iterations by perhaps 6:00 a.m. and continuing them until perhaps 9:00 a.m. This
would provide the most time available for iterations to converge to an efficient
market price. However, this option also imposes the greatest costs on suppliers
to the market since they would have to start early and have to rush to get
schedules in to the PX.
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These options are summarized in Figure 8. There are three periods, submission,
iterating and scheduling. The desirability of any particular option depends on
the number of iterations needed to reach convergence on an efficient price. If a
small number of iterations is needed or the iterations move quickly, it should
be possible to introduce iterations into the market. However, it is not clear
how much iteration is needed and how long each iteration should last.
Rough estimates indicate that if the maximum amount of time is give to
iterations - about two hours - no more than 24 five-minute iterations could be
processed. It is unclear whether the market could converge in this number of
iterations.
Research findings suggest that the actual number of iterations needed may be
higher, particularly if there are technical constraints or demand/supply
volatility. A London Economics study in March 1997 used market simulations to
estimate the number of iterations under different scenarios. In "best case"
scenarios, London Economics found that it took about 10 iterations for the PX
auction to converge. In these scenarios, the London Economics model assumed
smooth demand profiles, no technical constraints, and no gaming behavior. Less
ideal scenarios were run to estimate how many iterations would take to achieve
convergence. Technical constraints increased the number of required iterations
to about 18. The model assumed generators operate for a minimum amount of time
and only start once daily. "Unusual" bidding behavior increased iterations to
more than 30. In this scenario, the model used two scenarios: hydro generation
was modified to include two additional small peaks and troughs that introduced
more variability in the residual demand met by non-hydro bidders. The number of
iterations was 32. A burst of hydro generation was introduced during peak hours.
The number of iterations was 42. This is a significant number of iterations that
may not fit into the timeframe allotted, even with relatively quick iterations.
The London Economics study noted there are ways to speed up convergence.
Activity rules, such as minimum step size from previous price, can quicken
convergence, but at a cost. There is a trade-off between efficiency and
convergence. When the model was run using a minimum step size for bid or PX
prices, convergence improved. But in the most complex cases, iterations did not
move below 20. As the size of the minimum step increased, so did the
market-clearing price, implying that there is a trade-off between efficiency and
convergence. However, it is unclear how much of an improvement these rules can
provide.
To summarize the feasibility issues, the time for iterations is very limited. In
order to expand it beyond the current 1 hour, it would be necessary to impose
costs on participants either by starting earlier or shortening the scheduling
time. It is not clear whether iterative bidding can achieve convergence within
the current timeframe allotted. No research has been done to show whether too
few iterations are better than no iterations. Seed prices and other activity
rules can speed convergence, but their impact on efficiency needs to be studied
further.
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2. STRATEGIC BEHAVIOR
As described above, the purpose of iterations is to disseminate information
about the market. In order for this to happen, participants must be willing to
reveal what they are willing to pay or be paid. One of the problems with
introducing iterations is to have participants reveal misleading information
about their intentions.
While the revision rules were designed to elicit true valuations from
participants, it still may be possible for participants to follow the rules and
mislead others to their own advantage. While this behavior is often termed
`gaming,' no pejorative association should be given to those who follow the
rules. Rather, it is incumbent on market designers to craft rules in such a way
that their intended outcome is achieved.
Gaming opportunities may or may not lead to material adverse effects on the
market. If gaming is pervasive and the rules not constructed well, the impact on
the market can be significant, leading to inefficient prices and misallocation
of generation. One of the difficulties of designing market rules to discourage
gaming is knowing how the rules can be gamed and how the rules should be
adjusted to avoid it. The games may not be apparent until the market is
established.
Research on the proposed bidding structure did not focus explicitly on gaming
opportunities. The inquiries by Wilson, Plott and London Economics on the gaming
issue were limited. In his experimental work, Plott did not explicitly examine
some of the issues surrounding gaming. His report noted that the behavior of the
auction when prices are moving up has not been explored. Similarly, it stated
withdrawals were not studied and that sticking around and driving price down for
others becomes cheap talk if exposure to risk is not present. Thus, strategic
behavior was not fully explored.
There is at least one way to game these bidding rules that involves making
fictitious bids. The description below lays out this potential source of
problems. It is not clear how much of an impact the described behavior will have
on the market results. As will be discussed below, it is also difficult to
address the elimination of this gaming opportunity through additional rules. The
point of the discussion is to highlight a potential gaming problem and how it
may be addressed. Other gaming opportunities are probably possible with this set
of rules.
Fictitious bids could allow some bidder to provide misinformation about their
true valuation. Portfolio bidding does not require the identity of generating
units to be assigned to particular portfolios. Thus, it is possible to bid more
than one portfolio representing the same units. By introducing multiple bids for
the units, suppliers could depress the price in early iterations only to remove
their low cost bid in subsequent iterations to raise price. By this point in the
iterations, some of the rivals who would be economic at the higher prices have
exited the market because they saw the lower prices set by the fictitious bid.
This leads to higher prices to consumers.
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For example, a bidder initially bids two separate portfolios, one at a low cost
and another at a high cost. In early iterations, bidder adjusts its low bid
portfolio while freezing its high bid portfolio at its initial level. As price
falls and low bid portfolio is awarded significant quantity. The reduction in
price forces other bidders to withdraw from the market. In later iterations, the
bidder withdraws its low bid portfolio and price subsequently increases. High
bid portfolio is awarded output since other bidders have been forced out of the
market. This behavior does not violate the market rules or the revision rules
described above. This Figure 9 illustrates this behavior.
FIGURE 9: EXAMPLE OF GAMING
WITH FICTITIOUS BID
[GRAPH]
It may be possible to eliminate this type of behavior by changing some of the
rules; however, doing so would significantly alter the nature of the market. One
solution would be to limit multiple portfolio bids for the same units. However,
this requires units be pre-assigned to portfolio bids and eliminates some
sources of power from the market. Another solution would be to limit
withdrawals, but this would defeat the purpose of iterations to allow uneconomic
generation to get out of market and not lose money. A third solution would be to
have uncertain stopping rule or time, so bidders gaming in this way may be
caught prior to withdrawal. Over time expectations will form about stopping
rules and when they would apply. None of these options eliminates the ability of
bidder to profit from fictitious bids.
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To summarize, gaming opportunities are likely to exist in whatever rules are
adopted. Unless the rules are crafted well these gaming opportunities will lead
to greater price volatility. Research in the area has not focused in depth on
potential gaming opportunities or how they may be addressed. More research could
be done to identify the extent of potential problems and how they may be
exploited to the detriment of the market.
3. TRANSACTIONS COSTS
The introduction of iterations could significantly increase the costs
participants in the markets will have to bear to bid in the market. These are
transaction costs for bidding into the PX market. From the participant's
perspective, the benefits of introducing iterations into the market have to be
at least as large as the increase in cost of dealing with iterations. It is
likely these costs will increase significantly with the introduction of
iterations.
The bidding process will become much more complex under iterations. In order to
take advantage of iterations, participants must calculate profitability of the
awarded quantity. This involves estimating revenue and costs associated with the
quantity awarded in each iteration. To do this, bidders must separate the
portfolio quantity into unit loading levels. Then, bidders must calculate costs
of each unit loading level allocated. From these costs and revenues, profits (or
losses) can be calculated. Bidders must also figure out how to alter their bids
to reduce losses or increase profits. They must also check to see that bid
adjustments conform to iteration rules. Finally, they must resubmit bid to PX.
These steps are numerous and complicated. Further, each of these calculations
will have to be done for each iteration. It is likely to be a challenge for
bidders to accomplish this in a short time period. While the process could be
automated, it will still take an effort to automate.
It may be possible for bidders to ignore the opportunity to revise their bids
under the proposed system. This means they would simply maintain the original
bid curve introduced. This may be adequate. However, given the possibility of
gaming the system, bidders who do not monitor and react to the market during the
iterations run the risk of being a victim of the market.
To accomplish all of this analysis in the period of the iteration, it is likely
that participants will be required to increase staff to perform analysis on bids
and changing bids. Iterations will require an increase in communication with the
PX. Undertaking these calculations in a short time period will require more
computation power.
Further, these costs do not fall evenly on all bidders. In particular, these
calculations will be more easily done on smaller portfolios and single unit
bids, so bidders may gravitate to smaller portfolios. Bidders with larger
portfolios are likely to have more staff and computing power. To the extent
there are scale economies in bid revision, larger participants will be able to
take advantage of these lower costs.
Although no study was done to quantify the costs of iterations on market
participants, they are likely to be significant. It may well be the case that
the increase in market efficiency arising
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from iterations will not be large enough to offset the transaction costs that
must be incurred by participants.
C. INTERVIEWS WITH PARTICIPANTS
As a part of the June research, a number of informal interviews were undertaken
with various PX participants. From the period of May 22, 1998 through June 15,
1998, five telephone interviews were completed. Representatives of the following
companies were interviewed: Pacific Gas & Electric, Southern California Edison,
San Diego Gas and Electric, NorAm Energy and Electric Clearinghouse. The purpose
of these interviews was to gain insight into the issues surrounding the
introduction of iterative bidding into the PX day-ahead market. A number of
topics were discussed in these interviews, including many described above.
Specifically, each interviewee was asked about four topics. They are: the
benefits and use of iterations; the time allotted for iterations; the time
allotted for scheduling; and possible gaming of iterations. The results of these
interviews will be summarized below by these four topics.
The participants were unanimous in their belief that iterative bidding could
bring benefits to the market; however, they were divided as to whether they
would use the iterations if introduced. All respondents said that smaller
portfolio generators would benefit since they could avoid infeasibilities. One
respondent stated that the information provided by the iterative process would
help it make market arbitrage decisions. However, only two of the five said that
they would make use of iterations if they were introduced. The reasons were
varied for declining the use of bids. One stated it did not need iterations
because of divestitures of generation. A second said the market was too new to
make significant changes such as adding iterations. It also stated it would need
to add additional resources to accommodate iterative bidding. The third stated
the size of its portfolio was significant and it could not incur the transaction
costs needed to alter bids during iterations.
Although the interviewees gave various opinions with regard to the time needed
for iterations, they were unanimous with regard to one aspect of the timing.
None was in favor of moving the close of bidding any earlier than 7:00 a.m.
Their opinions about how much time should be allotted for iterations varied. One
believed the one hour originally specified was the appropriate time. Another
stated that only one-half hour should be allotted since more time was needed for
scheduling. Two others did not specify a particular time period, but noted the
allotted one hour would not be sufficient. They noted that a significant amount
of time would be taken in uploading and downloading information from the PX.
Further, they would need a sufficient amount of time to complete analysis and
compare the PX market price with other opportunities. The fifth stated that
perhaps as much as two hours were needed, but scheduling time should not be
sacrificed for iteration time.
The respondents also varied considerably in their responses to the need for
scheduling time. While all were unanimous in rejecting an earlier start time,
some thought scheduling time could be shortened to allow more time for
iterations. Others thought more time was needed for scheduling. The two
interviewees who represented entities that were bidding a large number of
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plants stated that more time was needed for converting PX awarded quantities
into generation schedules. One stated that it takes about 45 minutes to
apportion awarded quantities to schedules and then another hour to hour and a
half to calculate adjustment bids and ancillary services bids. The other stated
that it on occasion had difficulty submitting its initial preferred schedules
even with the extra time from the 7:00 a.m. to 8:00 a.m. hour. The three other
interviewees thought the time was either adequate or could be shortened. One
stated that no change was needed to the schedule. One observed that the time
needed to schedule depended on whether it bid single generators or portfolios,
with portfolios taking longer to schedule. The third expressed a desire to
shorten the time for scheduling and also to have the ISO push back its
requirement for schedules to 12:00 noon from 10:00 a.m. Given that these
interviews were done approximately two and one half months into the market, it
is to be expected that the assessments of time needed varied widely.
The interviewee's views about gaming were more consistent. Almost all of them
had not given much thought to the specific opportunities for gaming; however,
they were concerned that it may become a problem. One observed that his company
had not thought of any particular ways to game the system, but, given the
incentives, there are probably ways to game the system that no one has yet
discovered. This interviewee suggested that more research be done involving
market simulations to estimate the extent of the problem. Two others stated that
they were concerned that opportunities may arise, but had not thought of any
specific opportunities. One interviewee stated that its firm had little or no
concern about gaming. Finally, the fifth interviewee stated that it did not
consider behavior within the rules to be `gaming;' however, there was concern
about being affected by behavior outside the rules. A strong set of rules would
significantly reduce this possibility.
D. CONCLUSIONS FROM JUNE 1998 STUDY
The conclusion drawn at the time the research was done was that the market was
not yet ready for the introduction of iterations. The policy decision was made
at the time that the topic should be taken up at a later date in the fall of
1998. This would allow more time for bidders to become familiar with the market
and its operations. In particular, bidders would have become better at
transforming their awards into generator schedules. Similarly, they would have
more experience in having learned about their bids affected their profitability
from the daily repeated auctions. These are countervailing effects. The
transaction costs would be lower, but so would the value of the information
produced by the iterations.
One of the conclusions from this investigation was that it was not clear whether
bidders would have enough time to adjust their bids in the each of the
iterations. Participants believed they needed sufficient time to undertake the
proper analysis to respond to the information they faced. Over time the required
time would be reduced, as they became more familiar with the process and data
flows between themselves and the PX. Nonetheless, transactions costs for
participants was going to be significant since much data processing would be
needed to respond appropriately to information in iterations.
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From this research, it was clear there are potential gaming opportunities that
need to be addressed before implementation could take place. In particular, the
opportunity for fictitious bids to provide a means to signal false valuations
was possible. Activity rules need to be developed to adequately address problems
such as those associated with fictitious bids. Further, more research may be
needed to address other potential gaming problems.
Overall, in June, the market institutions were still too new to have settled
down significantly for iterations to be introduced. At that time, the hour-ahead
market had not yet been introduced which could have contributed significantly to
reducing risk from infeasibilities. Further, the amount of learning that was
being done by daily repeated bidding was also limited. Significantly more
learning would take place in the intervening period between June and November.
Thus, by putting off consideration to a later date, the market would be better
able to assess the value of iterations in a more mature market.
V. SUMMARY OF RESEARCH DONE IN NOVEMBER 1998
Between June and November, the PX developed software to implement iterations.
This involved incorporating the revision rules that had been specified. These
are essentially the rules described above adapted to apply to demand as well as
supply bids. Beta Tests of the software were undertaken to answer a number of
questions. First, did the software work as expected? What modifications would
have to be made before iterations could be introduced? Second, how many
iterations would fit into the time allotted? Could changing the timing of the
market increase the number of iterations? Third, how would its participants
react to the introduction of iterations and necessary modifications to the
market? Fourth, given the answers to all these questions, was the time right to
introduce iterations? What problems might still have to be worked out before
they could be introduced?
Because most of the costs and benefits of iterations would accrue to its
participants, they would be in a much better position to assess whether there
would be a net benefit from introducing iterations. Would their benefits be
large enough to outweigh their costs? The best way to assess this would be to
survey participants after they had been involved in the Beta Test. A survey was
constructed and participants responded. The results of the Beta Tests and the
survey were presented to the PX Board at its November meeting. A brief report
was written to convey the research findings. The PX Board decided to postpone
the introduction of iterations indefinitely.
The author of this report was not involved with the research undertaken in
November 1998. Therefore, there is no immediate knowledge of the research
effort. However, a copy of the report to the PX Board was provided to the author
of this report. Large portions of that report will be excerpted below as an
explanation of the November efforts. The portions not directly spelled out are
contained in Appendices A and B. These appendices contain, respectively, the
specific answers to the questionnaire and the price and quantity results for
each iteration for each day tested.
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The large excerpt will provide a basis to critique the report and discuss issues
that the Beta Test was not specifically designed to address. Particularly, are
there any benefits or costs participants identify that have gone unnoticed?
Also, is there any evidence of behavior consistent with gaming in the Beta
Tests?
The excerpt of the report will be followed by discussion and comment on the
results. After the excerpt from the November report, comments and observations
will be made concerning some of the specific answers given to the questionnaire
and iteration results that were included.
A. EXCERPTS FROM `BETA TEST OF ITERATIVE BIDDING IN THE PX DAY-AHEAD MARKET'
EXECUTIVE SUMMARY
The PX operated a Beta Test of iterative bidding with PX participant involvement
from November 2, 1998 through November 6, 1998. The purpose of the Beta Test was
to provide PX Participants the opportunity to preview iterative bidding and
submit comments based on this preview. The Beta Test also gave the PX an
opportunity to evaluate in a market simulation environment the task of operating
an iterative Day-Ahead Market.
Many of the PX Participants that took part in the Beta Test shared some common
concerns about iterative bidding such as potential for gaming, reduced time for
[Initial Prefered Schedules] IPS's, Adjustment bids, and Ancillary Services
bids, and additional costs for staffing and system modifications. Many felt the
costs to implement iterations outweighed the potential benefits. Over half of
the participants that submitted comments recommended not implementing iterative
bidding at this time. None recommended implementation.
The PX observed that iterative bidding would initially require 30 minutes per
iteration, which would allow for at most 3 iteration if the final iteration
closed at 8:00AM or 1.5 iterations if PX maintained current schedule of
publishing final auction results at 7:15 AM. Over time, this could be reduced to
15 to 20 minutes per iteration, which would allow up to 4 or 5 iteration if the
final iteration closed at 8:00AM or 2 iterations if PX maintained current
schedule. Prior studies indicated that at least 10 iterations, sometimes many
more, would be required to reach convergence. The benefit of 2 to 5 iterations
would likely be small relative to the costs incurred by all stakeholders. The
Majority of PX participants are against modifying the current PX timeline to
allow for additional iterations. Before iterative bidding could be implemented
the PX and PX Participants would incur additional costs associated with software
fixes and modifications, additional testing, and training.
PX PARTICIPANT INVOLVEMENT
On October 26, 1998, the PX published a PX participant Notice (Notice 98-58)
announcing a Participant Beta Test of Iterative Day-Ahead Bidding to be held
from November 2, 1998
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through November 6, 1998. The initial conference call took place on October 28,
1998 to explain iterative bidding, answer any questions, and discuss the Beta
Test. A total of 14 PX Participants opted to take part in the Beta Test. On
average, the 14 PX Participants collectively represent 90% to 95% of the PX
Day-Ahead market volume. A conference call was held after each session to
discuss in an open forum any observations from the Beta Test.
PX PARTICIPANT COMMENTS
At the conclusion of the Beta Test, the 14 participants were asked to respond to
the following seven questions:
1. Do you think you would modify your bids during iterations? 11
responded.
5 might, but not often.
4 probably would not.
1 yes, but stated against implementing iterations.
1 no, and would consider no longer participating in PX market if
iterations became mandatory.
2. How much time should be allowed per iteration? 12 responded.
8 were in the range of 20-30 minutes.
2 felt 15 minutes would be too short, but wanted to re-evaluate with
software bugs fixed.
1 could not answer until software fixes are in place and re-tested. 1
stated that 5 minutes would be sufficient.
3. Are you willing to move the deadline for bids from 7:00 AM to 6:00 AM
if necessary to provide for iterations? 12 responded.
9 said no.
1 said yes.
1 said yes if other participants that would normally participate in
iterations agreed.
1 suggested 6:40 AM.
4. Are you willing to reduce the amount of time available for submitting
IPS's, adjustment bids, and A/S bids, if necessary to provide for
iterations? 12 responded.
8 said no.
2 said yes.
1 said yes, but would be pressed for time.
1 very reluctantly would agree to a reduction in time.
5. Are you concerned about gaming during iterations? 11 responded.
8 said yes.
1 uncertain.
2 said no.
6. What benefits do you see for your company if iterations are
implemented? 12 responded. 7 identified potential benefits such as
price discovery, potential for higher profits, opportunity to reduce
costs, or more feasible schedules. 5 mentioned minimal benefit, if
any.
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7. What negative impacts do you see for your company if iterations are
implemented? 11 responded. 11 identified potential negative impacts
such as reduced time for IPS's and adjustment and A/S bids, additional
personnel requirements, costs for developing analytical and
data-management software, costs associated with human errors and
computer system or software problems resulting from more complex
iterative process, conflicting timeline with bilateral markets, higher
prices due to gaming, withdrawal of bids or programmed response to
iterative results, and making self-provision more difficult to
implement.
Some participant provided unsolicited comments. Six participants recommended not
implementing iterations at this time. Reasons included negative impacts outweigh
benefits and PX should pursue more beneficial changes such as additional forward
markets or improvements to the hour-ahead markets. Various software
modifications or fixes were also identified. If iterations were implemented,
these modifications and fixes would have to be addressed. None of the 14
participants recommended implementing iterations. The following tables include
the participant responses. Some responses were edited at the request of the
participant to exclude bidding strategy. Other comments were summarized or
paraphrased.
[Table of responses reproduced in Appendix A.]
BETA TEST RESULTS AND CONCLUSIONS
The Beta Test was intended as a preview for participants of the iterative
bidding process. This preview was intended to provide additional basis for
participants' comments regarding the implementation of iterative bidding. These
comments were presented in the previous section. The PX also made some
observations concerning operation an iterative Day-Ahead market which are
summarized as follows:
o During iterative bidding, the PX would not have enough time to
manually enter bids for participants having connectivity issues. This
could cause some participants' bids to be come frozen prematurely and
unintentionally.
o Participants will initially require at least 30 minutes per iteration
to successfully submit modified bids.
o Gradually, the time per iteration could be reduced to 15 to 20
minutes.
o PX will likely have to begin iterative bidding earlier or reduce the
amount of time for IPS's, Adjustment Bids, and Ancillary Service bids
to provide enough time for iterations.
o Iterative bidding should eliminate the need for the Anomalous Bid
Protocol.
o If iterative bidding were implemented, additional costs would be
incurred to modify or fix core trading software based on comments
during Beta Test.
o Substantial training and market simulation testing would be required.
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The Beta Test was not designed to prove or disprove theoretical results.
However, the following observations were made regarding the results of the Beta
Test:
o Session 11-03-98 exhibited slight movements in price and volume until
a bid was withdrawn that caused prices to increase an average of 80
percent while volume decreased by 20 percent.
o Session 11-04-98 exhibited generally increasing prices with increasing
volume.
o Session 11-05-98 exhibited prices and volume that fluctuated modestly
up and down.
o Sessions 11-06-98 and 11-07-98 exhibited a pattern of generally
increasing prices while volume initially increased, but later
decreased.
The following tables and graphs show the movement of princes and volume during
each of the iterative bidding sessions during the Beta Test.
[Tables reproduced as Appendix B.]
B. COMMENTS AND OBSERVATIONS FROM NOVEMBER RESEARCH
The PX made the decision to move forward with setting up the software for
iterations and let participants get a feel for how it would work. Because most
of the costs and benefits of implementing iterations would accrue to market
participants, it makes sense to survey them with regards to determining whether
iterations would bring a net benefit to the market. The Beta Testing provided
participants to get a hands-on feel for how the institution would work and help
them assess the costs and the benefits. It also helped the PX identify the costs
of implementing the bidding system.
1. COMMENTS ON RESULTS
A. THE REPORT'S DISCUSSION
The PX report gives only the briefest of interpretations of Beta Test results.
Nonetheless, the report does make some important observations that are worthy of
highlight. First, the electronic communications links between the PX and
participants are crucial to the successful operation of iterations. Further, it
also requires operating procedures and rules when communications fails during
the process.
Second, that it is questionable whether enough iterations could take place to
achieve convergence. With iterations taking thirty minutes initially only having
an hour for them. , this yields only two iterations are possible if each takes
30 minutes and there is only an hour for them. With a quickening of the pace to
15 minutes only yields 4 to 5 iterations. While this may be enough, it could
also prove problematic, as will be discussed in greater detail below. Altering
the timeline may also prove problematic.
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Third, further costs would have to be incurred by the PX to implement system.
Specifically, bugs need to be eliminated from software and it needs to be made
friendlier to users. Also, implementation would require conducting more testing
and training of market participants.
Although the report states that the test was not designed to support theoretical
hypotheses, the report's discussion of the results is the most cursory and will
be expanded below.
b. THE REPORT'S OMISSIONS
Perhaps the largest omission from the report was a complete description of the
participants who took part in the testing. The report states 14 participants
representing some 90 to 95 percent of the Day-Ahead market volume. However, it
does not report how many of the participants were supply-side bidders and how
many were demand-side. Nor does it report whether the 90 to 95 percent included
both sides of market volume or only the supply or demand side. The number and
size of bidders on each side of the market is important information to be able
to assess the results of the testing. An examination of the results shows there
were clearly both demand and supply participants in the Beta Test. This is
because on more than one day prices and quantities were increasing between
iterations. Under the revision rules described above, this can only take place
when demand is participating in the market.
Another deficiency in the report was that nothing was said about the closing
rule used to decide which iteration was the last. Bidding strategies would be
different if the number of iterations were announced before the first iteration.
Similarly, bidding strategies would change if the number of iterations were
announced during the auction. Thus, one cannot tell if the participants are
bidding in such a way to get their desired outcome in the last iteration. There
were a number of closing rules described above, it is clear that one of them was
not being used. That is the change in energy prices was not appreciable. This is
clear from the fourth iteration on 11-03-98 where there was almost no movement
in prices between the third and fourth iterations, but the auction lasted for
two more iterations.
Although it is understandable why such information was not reported, it would be
instructive to have examined how each bidder changed its bids between
iterations. This would perhaps reveal too much about individual's bidding
strategies. A less sensitive number would have been to report how much total
quantity was bid in at all levels of quantity. This would have provided
information about the overall prominence of fictitious bidding. Nonetheless,
only market-level data are reported and not individual bidder data. Thus, it is
difficult to assess what strategies individual bidders are following.
Nonetheless, the market-level data can also be revealing.
c. INTERPRETING THE REPORT'S RESULTS
The report does contain market level prices and quantities for each round of
each auction. These data are attached as Appendix A. In conjunction with the
bidding rules for both demand
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and supply in the market, examination of changes between iterations provides
some insights as to how bidders were acting in the Beta Test.
In combination with the revision rules described above, the changes in prices
and quantities between iterations indicate what is going on in the market.
Supply side bidders only have two options in making revisions. First, they can
adjust their bids to lower their selling price for each quantity they offer as
described above. Second, they can remove a portfolio entirely from the market.
Ceteris Paribus, supply bid adjustments lead to lower prices and higher
quantities. Similarly, supply bid withdrawals lead to higher prices and lower
quantities. This is illustrated in figure 10. In the initial iteration P(1) and
Q(1) prevail. In the second iteration, if as a whole, supply adjusts its bids,
then a lower price, P(2A), and higher quantity, Q(2A), result. However, if, as a
whole, supply withdraws portfolios, then a higher price, P(2B), and lower
quantity, Q(2B), ensue.
FIGURE 10: SUPPLY SIDE EFFECTS
[GRAPH]
Likewise on the demand side of the market, there are only two options to making
revisions in their bids, revisions and withdrawals. Again, ceteris paribus,
demand bid adjustments lead to higher prices and higher quantities. In like
fashion, demand bid withdrawals lead to lower prices and lower quantities. This
can be seen in Figure 11. In the initial iteration, P(1) and Q(1) are the
outcome. In the second iteration, if as a whole, demand adjusts its bids, then a
higher price,
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P(2A), and higher quantity, Q(2A), follow. However, if, as a whole, demand
withdraws load, then a lower price, P(2B), and lower quantity, Q(2B), arise.
FIGURE 11: DEMAND SIDE EFFECTS
[GRAPH]
While it is the case that these effects can take place simultaneously, examining
how the prices and quantities change between iterations can shed some light on
how both demand and supply bidders are reacting to the market. For example,
between the first and second iterations in the 11-04-98 auction, both prices and
quantities have increased. This indicates that, besides whatever else is going
on in the market, the predominant effect is that demand bidders are adjusting
their bids to increase the amount they are willing to pay for power. This is the
only type of changes to the market that can explain both an increasing price and
an increasing quantity. Given this method of interpretation, it is possible to
describe the iterations in greater detail. Each of the daily markets will be
described using these terms.
These results represent the first chance PX participants had to experience
bidding with iterations. There was learning going on over these five days. The
11-03-98 market was the first day of the test. There were six iterations in this
market. In the second iteration, prices were generally falling and quantities
increasing with the exception of hours 22 and 23. This indicates the supply
adjustments were the predominant activity in this iteration. In the late hours
of the day, prices went up and volumes went down. This indicates that the net
effect was
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the removal of supply portfolios from the market. Suppliers may have bidding
separate portfolios for separate hours and decided not to operate at those
prices, thus, removing the portfolios for those hours. The third iteration shows
generally increasing prices and quantities indicating demand decided to buy more
at those prices. There is little change with the fourth iteration and depending
on the stopping rule, the auction may have ended. However, in the fifth
iteration, a chunk of 20% of the quantity in the market was removed from the
supply side, leading to much higher prices and lower quantities. After such a
large removal, it took another iteration of supply adjustment before the market
ended.
The results for 11-04-98 show quite a different pattern of change. It too lasted
six iterations. However, between each iteration, the prices and quantities
increased. This indicates the major effect was demand side adjustments.
Specifically, demanders were increasing their willingness to pay at the relevant
levels of demands. However, the magnitude of the price changes diminished as the
auction went on. There was an average 4 percent increase in prices between the
first and second iteration, but only a .25 percent increase between iteration
four and five. There must have been little activity in the later rounds.
The results for 11-05-98 show a prominence of the supply side of the market.
Prices were generally falling and quantity increasing. This indicates suppliers
were lowering their willingness to bids throughout the auction. The auction
lasted nine rounds, but the activity was diminished under a 1 percent average
price change by the fifth iteration. The rounds 3 through 6 saw changes only in
hours 1 through 5, with supply adjustments lowering prices and increasing
volumes. The later rounds saw changes in hours 17 through 20. There was a
withdrawal of supply bids in iteration 6. In the remainder of the iterations,
supply adjusted and prices fell in those hours. Again it should be highlighted
that a couple of iterations may be needed when there is a supply withdrawal.
The results for 11-06-98 lasted six iterations and show a mix of results across
iterations and hours. In the second iteration, most hours in prices and
quantities increased. This indicates demand adjustments. However in morning
hours prices fell while quantity increased, indicating supply competition for
share. In the third iteration, there was supply competition as prices fell and
volumes increased. The rest of the hours show increases in demand purchases. The
fourth iteration showed a supply withdrawal as prices increased and quantities
decreased in almost all hours. The fifth iteration showed a mix of effects with
some supply withdrawal and demand adjustments. However, the last iteration
revealed another supply withdrawal that increased prices by an average of over 5
percent. Given the limited information in the report, it is impossible to tell
whether this result was caused by unprofitable portfolios exiting or removal of
fictitious bids. However, if it is the latter, this is wholly consistent with
the classic example of the supply gaming described above.
It should be highlighted that one way for demand to avoid paying the resulting
high prices would be to play the same game. Specifically, for the demand side of
the market to introduce fictitious bids of their own which they would remove in
the last iteration as well. This would protect them from the resulting higher
prices. This would inflate the quantity stated in the early
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rounds of the market. Alternatively, this strategy would be harder to follow if
there were uncertainty about when the auction would end. Such uncertainty would
not eliminate the strategy, but only make it more difficult to follow.
The results for 11-07-98 lasted four iterations and show exactly the same
pattern as the day before. Specifically, demand increased its willingness to buy
between the first and second rounds with an average 8.66 percent increase in
quantity and a 13.6 percent increase in prices. However, in the last iteration,
supply withdrew portfolios resulting in an average 9.4 percent increase in price
and a reduction in quantity. A stronger case can be made for supply manipulation
of prices in this case. Withdrawal of supply for economic reasons means the
portfolio would be losing money. However, with each iteration, all prices in all
hours were increasing between iterations. The portfolio that was withdrawn in
the fourth iteration had to have been losing money from the start of the market.
Even if this portfolio was marginal and setting the prices in the previous
rounds, it's initial bid had to have been below its costs. It is possible that
this portfolio may have been waiting to see if prices would increase over
iterations to make it profitable. However, the alternative hypothesis of a
fictitious bid is also possible. More information about the specific bids and
bidders would be needed to strengthen the argument either way. However, the
result is consistent with supply manipulation of prices.
[CHART]
The table summarizes the price and quantity movements for the changes between
iterations for the first six iterations of each round. There were 11 iterations
on 11-05-98, but only first five are shown here because there was little
movement in prices and quantities in the later rounds. As can be seen in the
table, for all days, a supply or demand adjustment started in the early rounds
of the market. As expected, supply withdrawals came near the end of the
iterations. It should be highlighted that demand withdrawals were never a
predominant effect for any iteration on any day. This may indicate demand's
unwillingness to take advantage of the revision rules in the iterative process.
2. COMMENTS ON INTERVIEWS
The participant survey solicited views concerning the introduction of
iterations. The answers as specified in the report are attached as Appendix B.
The report did a good job of summarizing these comments. The survey dealt with
two different issues that will be discussed
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here. First, what was the participant's perceived benefits and costs of
iterations? Second, how did the participants view gaming in the market?
a. BENEFITS AND COSTS
The bulk of the questions in the survey had to do with the benefits and costs of
implementation. In large part, the answers were conditioned on the conclusion
the participants had come to. For instance, more than one participant stated
that it would not support increasing the time for iterations given it did not
see benefits and probably would not use them.
Three questions addressed the time available for iterations and garnered
generally negative responses. Namely, only one participant was willing to
increase the time for iterations. Thus, the benefits from iterations are great
enough to overcome the transition costs of changing the established process.
Two participants cited price discovery as a benefit of iterations. These were
probably demand side participants who were able to adjust consumption in the
early rounds of iterations. Only two participants cited better adoption of
feasible schedules as a benefit. Most found little benefits from iterations.
Many of the participants cited higher costs of dealing with iterations as a
significant negative impact of iterations.
b. CONCERNS ABOUT GAMING
One of the questions asked explicitly about concerns about gaming in the market.
Three participants cited particular games as a significant problem. Their
comments support some of the observations made above about the possibility and
likelihood.
One explicitly complained that the activity rules are not sufficient to prevent
the type of fictitious bidding that was described above. Specifically,
"Withdrawal Rule would allow a participant to submit a fake bid to drive price
down to force others to withdraw from the market until the fake bid is withdrawn
leaving the real bid at a higher price...." Further this participant stated it
would not agree to implementing iterations unless this flaw was fixed.
Another participant stated it believed that there would be gaming, but it would
not diminish the end results relative to a single-round auction. However, they
also stated, "The basic game in iterative bidding involves the submission of
bids that are not physically based for the sole purpose of withdrawing them to
drive prices up." They correctly note that it would be difficult to guard
against this behavior because it is similar to legitimate withdrawals.
It should also be highlighted that there were countervailing views of the
results. One participant cited a higher MCP as a benefit from iterations. As
discussed above, these higher prices may have been resulting from gaming of the
market, particularly in the last two auctions. Another participant cited higher
prices from gaming as a significant negative impact of the introduction of
iterations.
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C. CONCLUSIONS FROM NOVEMBER RESEARCH
Given the responses of participants to the survey, the report does come to the
correct conclusion about implementation of iterations at this time. Namely, the
current iterative structure and timeline produce more costs for participants
than it does benefits. Nonetheless, there are two new conclusions to that follow
from the November research. First, there is a benefit to demand from
participating in iterations. Second, there is the real potential for gaming the
iterative process. Each of these conclusions will be discussed in turn.
Iterations provide significant benefits to the demand side of the market as well
as to supply, particularly during the transition period. Because PG&E, SCE and
SDG&E are required to purchase the power from the PX market, they currently have
few options for procurement. Particularly, they can only buy from the Day-Ahead
or On-the-Day markets. CTC recovery provides an incentive for them to reduce PX
prices as much as they can. Splitting purchases between these markets is one of
the only ways they have to reduce their power costs.
The basic problem they are solving is a quantity allocation problem between the
markets. By buying less in one market they will pay a lower price in that
market. However, they must then buy more in the other market, pushing up the
price in that market. To do this effectively, they must forecast relevant supply
elasticities for both markets. The tradeoff can be seen in Figure 12. Demanders
have a total Q(T) they must purchase between both markets. By moving down the
Day-Ahead supply curve, they move up the Hour-Ahead curve. The optimal
allocation is given when the extra they save in one market is exactly offset by
the extra they must pay in the other market.
Iterations in the market allows demanders to obtain better information about the
Day-Ahead price before committing to how they would like to split their load
between these markets. The iterations allow them better control over the
quantity they purchase in the Day-Ahead market. If prices are low, they can
adjust their demand bids to increase their purchases. If prices are high, they
can withdraw some bids to reduce their purchases. This is a significant benefit
from iterations.
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FIGURE 12: DEMAND PURCHASE DECISION
[GRAPH]
There is the possibility that there was manipulation of the market in the Beta
Test by supply-side bidders. The price and quantity patterns in the last two
days of the test are consistent with suppliers removing a `fictitious bid' in
the last round of the auction. It would be impossible to eliminate the
possibility of a fictitious bid without requiring all bidding to be done on a
unit basis. The elimination of portfolio bids would have other consequences on
the market and may not be the solution to this problem.
Further, the market results were not consistent with strategic behavior on the
demand side of the market. However, that does not mean that demand could not
behave exactly the same way supply does by bidding fictitious load that it too
would pull out of the market on the last iteration. This behavior would tend to
reduce price and quantities. Because the seller's objective is diametrically
opposed to the buyer's, it is not clear how the net result would turn out if
both sides of the market were undertaking strategic behavior simultaneously.
More investigation and data analysis would be needed to determine what the
likely result would be.
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VI. CONCLUSIONS
In its evaluation of the gains from implementing iterations in the market, the
PX correctly looks to its participants for assistance in determining whether
iterations should be adopted. Participants bear most of the costs and enjoy most
of the benefits from iterations.
Participants report that the costs imposed by iterations are large in comparison
to the benefits they provide under the present set of revision rules and market
timeline. The costs imposed by iterations include increased staff and computer
resources to process the information. The benefits are minimal except perhaps on
the demand side of the market where price discovery allows a better allocation
of purchases between the day-ahead and other markets.
However, more testing of iterations would have provided more information about
the likely impacts of implementing these rules. For instance, there was not
enough study to be able to tell what the impacts would be of strategic behavior.
There may or may not be significant problems with bidders behaving strategically
through the iterative process. While the Beta Test revealed market price and
quantity results that are consistent with strategic behavior on the part of
supply, there did not appear to be much strategic behavior on the demand side of
the market. As just discussed, it would be possible for demanders to undertake
similar behavior. Before implementation or revision of rules to address the
problem of fictitious bids, more research should be done to identify the net
effect when both sides of the market are behaving strategically.
Elimination of opportunities for strategic behavior may be difficult to
implement since they would require the adoption of unit bidding. Unit bidding
would considerably lessen the costs on suppliers to perform analysis during the
iteration. However, it may require suppliers to forego the benefits of portfolio
bidding.
Given the evidence, the policy decision to forego implementation of iterations
at this time is a prudent one. Changes should be focused on addressing ways to
reduce costs to participants. Any change in the rules or market that reduce the
cost of transacting through iterations should make iterations more attractive.
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VII. SOURCES
London Economics, "PX Auction Testing: A Report for the California PX
Restructuring Trust" London Economics, Inc., March 3, 1997. (Also included as PX
Appendix 3, Attachment B, PX/ISO filing, March 31, 1997).
London Economics, "Response to Request for Additional Information," Questions 15
and 18, May 20, 1997.
London Economics, Inc., "PX Auction Testing: A Report for the California PX
Restructuring Trust." March 3, 1997. (Also included as PX Appendix 3, Attachment
B, PX/ISO filing, March 31, 1997.)
London Economics, Inc., "The Impact of PX Simplifications on PX Efficiency: A
Report for the California Trust on Power Industry Restructuring," September
1997.
Order Conditionally Authorizing Limited Operation of an Independent System
Operator and Power Exchange, Conditionally Authorizing Transfer of Control the
Facilities on an Interim Basis to an Independent System Operator, Granting
Reconsideration, Addressing Rehearing, Establishing Procedures an Providing
Guidance, FERC Order, October 30, 1997
Plott, Dr. Charles R., "Tests of the Power Exchange Mechanism," March 10, 1997.
(Also included as Attachment 2, August 15, 1997 FERC Filing.)
Power Exchange Bidding and Bid Evaluation Protocol, Revised to Incorporate
Iterative Bidding and Activity Rules, no date.
The FERC's 90 Questions, April 29, 1997
Wilson, Dr. Robert, "Bidding Activity Rules for the Power Exchange: Report to
the California Trust for Power Industry Restructuring" Market Design Inc.,
March 14, 1997. (Also included as PX Appendix 3, Attachment A, PX/ISO filing,
March 31, 1997).
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APPENDIX A: SURVEY RESULTS
Participant Do you think you would How much time should Are you willing to move Are you willing to
normally modify your bids be allowed per the deadline for bids reduce the time
during iterations? iteration? from 7:00 am to 6:00 am available for
if necessary to provide submitting IPS's
time for iteration? Adjustment Bids, and
A/S bids, if necessary
to provide for
iteration?
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
1
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
2 20 minutes 6:40 am 8:20 am
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
3 Probably not. 15 minutes appears No. No.
tight, but we cannot
accurately assess
until technical
difficulties are
resolved
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
4 If iterations become Based on the Beta No. Rather not.
mandatory, there is a good Test, 5 minutes is
chance that we will no longer sufficient time.
participate in the PX Market
because of the time
constraints and manpower
required to do iterations.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
5 Not often, maybe 10% of the 20-30 minutes is Yes. Yes.
time. more realistic than
15 minutes. PX
could open the
market with longer
time period, then
move to 15 minutes
after participants
gain experience.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
6 Currently would not normally Should be Would be acceptable if Based on other's
modify bids. Would modify re-evaluated after the participants that comments, would not be
bids if economies in market software bugs are would normally acceptable.
place made good business fixed. Right now, participate in
sense to make such 15 minutes is too iterations are willing
modifications. short. to move the timeline.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
7 Right now, given the number Cannot answer this No. As it is, we are No. This would be an
of resources we need to bid question until fixes pushing other entities extreme hardship, given
and/or schedule, iterative are made and tested. we work with to provide the additional work on
bidding is not necessarily an us appropriate data by 6 top of the current
option, since you need to am so that we can workload, to develop
modify each resource and prepare our bids. IPSs, Adj. Bids, and
modify the appropriate prices A/S bids.
that are active. At this
point, we would incorporate
reviewing the MCP from the
first iteration into our
bidding process. But, as a
rule, we would not
automatically modify our bids.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
8 Yes, but only to a limited For the Beta tested No. Iterative bidding Currently, the benefits
extent. However, if we saw process and is not worth sacrificing of iterative bidding
evidence of routine excessive software, absolutely time that is currently appear to be far less
gaming, such that only the no less than 15 used to make last minute than the benefits of
last iteration was minutes. improvements to initial having enough time to
meaningful, our involvement Realistically, 25-30 bids. At most, a few do a good job
in iterations would drop off minutes are needed minutes before 7:00 scheduling and offering
substantially. Activity may to make any but the might be sacrificed Adj. Bids and A/S
be limited to the selective simplest, (e.g., 6:45). The bids. Iteration should
withdrawal of bids due to the essentially proposed Say-of market not be allowed to
primary reason that pre-designed, at 6:00 am would make reduce the time for
withdrawal of bids is simple, changes when closing the initial these activities.
quick, and relatively less multiple portfolios Day-Ahead iteration Iterative bidding is
subject to human error. are involved. before 7:00 especially simply not worth
impractical. detracting from the far
more complex and
manually intensive
processes of scheduling
and bidding into the
adjustment and A/S
markets.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
9 Yes. 20 minutes maximum, Prefer not. Suggest up Would very reluctantly
preferably to four 20 minute agree to shortening the
30 minutes. iterations, first time to 1.5 hours.
closing at 7 am and the However, in view of
last closing at 8 am. previous comment, we
Feel that 3 to 4 don't think it is
iterations are necessary.
sufficient for operators
to be able to adjust
their schedules as
necessary to run
efficient production and
recover costs as
required. A fixed
number of iterations
provides greater
opportunity for gaming.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
10
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
11 Not likely. No less than 20 Would oppose, given not Definitely not. DS's,
minutes. likely to participate in Adj. Bids, and A/S bids
Participants must be bid modification. are extremely important
allowed sufficient and those with large
time to give proper number of schedules
consideration to bid already have a hard
modifications. If time finishing on
too little time, time. Self-provision
participants will be of A/S will also
incented to either consume additional time.
not modify bids, or
develop a programmed
bid adjustment
response to each
round's results.
Both of these
behaviors completely
defeat
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the purpose
of iterations.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
12 Not at this time. 30 minutes. No. Absolutely not. This
would be totally
unacceptable.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
13 Same as Participant 12. Same as Participant Same as Participant 12. Same as Participant 12.
12.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
14 Probably, but not very often. Minimum of 20 minutes. This is not acceptable. May be a possibility,
Wold conflict with but could be pressed
bilateral markets. for time.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
Participant Do you think you would normally How much time should be Are you willing to move Are you willing to reduce
modify your bids be during allowed per iteration? the deadline for bids from the time available for
iterations? 7:00 am to 6:00 am if submitting IPS's
necessary to provide Adjustment Bids, and
time for iteration? A/S bids, if necessary
to provide for
iteration?
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
1
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
2 Price discovery. Various software fixes
identified. Without
fixes, would not favor
iterations since
negative impacts would
outweigh the benefit of
price discovery. During
Beta Test, the resulting
price change after
2.5 hours of iterations
was $0.10. That alone make
iterative bidding look
impractical.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
3 Uncertain. Minimal, if any. Inadequate time to process Additional testing
bids. necessary after technical
difficulties resolved.
Various software fixes
identified.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
4 Yes. If production reacts A burden and at times
same as simulation, impossible for the
chance for more profit pre-schedulers and
from higher MCP. dispatchers to do the
process. Pre-schedulers
are overloaded as it is.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
5 No. Better price Additional time and Various software fixes
discovery. Perhaps personnel requirements identified.
some opportunity to with no definite
reduce costs. financial benefit.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
6 Difficult to evaluate, but None identified at Based on relatively small Various software fixed
would be concerned about this time, but would price movements during identified.
participants with larger not want to eliminate market simulation, not much
market share starting the the ability to have negative impact. However,
bidding with lower or higher this function in the gaming could cause prices
prices, knowing they could future when the to move out of the normal
re-price their energy or market becomes more market range.
withdraw from the market robust and competitive.
altogether. Some have contracts
based on PX index pricing,
whether the energy is being
bought through the PX or not.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
7 Yes. For now, minimal Timing of the IPS, A/S and
benefit. Our main Adj. Bids. These bids are
concern is congestion the "bread and butter" on
and this will not setting the market for the
necessarily address it. next day. Concerned about
other issues related to
billing and settlements,
appropriate treatment of
RMR generation, and
solutions to congestion.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
8 We are not concerned that Most of the potential High opportunity cost of Iterative bidding should
gaming will diminish the end benefits result from reducing the amount of not be implemented in the
results relative to a single better matching our time for IPSs, Adj. form that was tested during
round auction, but we do financial obligations Bids, and A/S bids. the Beta Test. The process
expect gaming and think that with our physical Costs involved in as tested is far too time
it will substantially eliminate supply capabilities developing new consuming. The theoretical
the theoretical benefits of the and costs, However, the analytical and data incremental benefits of
iterative process. The net magnitude of management software as iterative bidding should be
result is very little payback these speculative well as staffing issues viewed as doubtful in
for the time and effort consumed. benefits should not be if ours are extended too practice. If the Board
The likely basic game in viewed as that great. much earlier into the decides in favor of
iterative bidding involves Other risk/revenue morning. Finally, costs iterations, implementation
the submission of bids that management tools associated with human should occur only after the
are not physically based for (including but not errors and computer successful conclusion of
the sole purpose of withdrawing limited to participa- system or software another test, any software
them to drive prices up. Can ting in markets closer problems resulting from bugs are fixed, and parties
only be guarded against with to real time) exist to the more complex more familiar with
sophisticated market better match physical iterative process. settlements problems have
monitoring (a difficult task and financial positions. endorsed the concept. At
to distinguish between The benefits of an least one month lead time
legitimate withdrawals and iterative vs. a one should be provided after
gaming activities). Risk to time auction process final iterative process and
gamers of not knowing when are doubtful and really software are established to
the last iteration will occur can't be demonstrated in allow participants to
is very minimal since the any test we can think of. develop appropriate new
gaming strategy could include analytical and data
withdrawing enough capacity management tools. Iterative
during each iteration to bidding should not be seen
ensure the stopping criteria as a priority at this stage
is not met, with the of the maturing energy
exception of the hard time market. It appears unlikely
deadline. to play a significant role
in improving the ability of
parties to manage financial
risks. Attention
DRAFT -- DO NOT CITE
- 43 -
would be better
applied to working
with the ISO to make
the hourly market more
streamlined (closer to
real time) and user
friendly.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
9 See a potential for gaming, Virtually none (keep Significant in terms of Considering the various
mostly due to the fact that in mind we are a net time effort and related impacts of the iteration
while sellers can withdraw seller and have no staffing, as well as process on the market and
their bids, buyers cannot interest in reduced conflicting timeline our own operations, we are
enter a new bid in later prices) compared to with bilateral markets. against implementing
iterations. Seems to be negative impacts. Iteration represents the iterations. Answers to
somewhat contrary to the PX having a "free previous questions
effort to improve the prices. option" on our energy provided in the event
for an extra hour. By the PX fixes software
the time iterations are problems, provides
closed, most of our sufficient testing, and
bilateral transactions decides to implement
are completed. iterations.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
10
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
11 Yes. Activity rules are not Few, under the Higher prices due either Not in favor of
sufficient to prevent gaming. current structure of to gaming or programmed implementing iterations
Withdrawal Rule would allow a the proposed bidding response to iterative at this time. However,
participant to submit a fake rules. results. Greater do not want to
bid to drive price down to possibility of mistakes, foreclose on the idea
force others to withdraw from less time to create Adj. either. Postpone
the market until the fake bid is Ids and A/S bids. A iterations until there
finally withdrawn, leaving the process that potentially is a demonstrable
real bid at a higher price, makes self-provision benefit at a minimum risk.
resulting in a MCP that more difficult to Rather the PX pursue
exceeds the price at which implement correctly. development of additional
most withdrawn capacity would forward markets prior to
have been willing to generate. implementing iterations
This is at least one flaw that as we see a larger
needs to be fixed. Until then, potential benefit in
we will not agree to iterations. such development.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
12 Yes. We may be able to Any reduction of time Recommend shelve iterations.
revise bidding for for IPSs, Adj. Bids, and May be worth resurrecting
generation units for A/S bids would be at some later date, but do
implementing feasible unacceptable. Price spikes not want to set an
schedules. because of gaming, implementation date at
withdrawal of bids the time.
to raise prices, etc.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
13 Same as Participant 12. Same as Participant Same as Participant 12. Same as Participant 12.
12.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
14 Not a significant concern. May be an opportunity Negative impacts far May be a possibility,
to sell more. outweigh the benefits. but could be pressed
Costs include personnel for time.
changes due to the times
involved and less
activity with the PX due
to bilateral market
timing conflicts.
- ------------- ------------------------------- ---------------------- -------------------------- -------------------------
DRAFT -- DO NOT CITE
- 44 -
APPENDIX B: ITERATIONS RESULTS FOR BETA TEST
Simulation Results from 11-03-98 Test
ITERATION #1 ITERATION #2 ITERATION #3
Hour MCP Volume MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol
Chng Chng Chng
- -----------------------------------------------------------------------------------------------------------
1 25.5149 13,839.6 25.0684 13,851.8 -1.75 0.09 25.1028 13,875.9 0.14 0.17
2 25.0007 13,786.3 24.3026 13,829.3 -2.79 0.31 24.3700 13,852.3 0.28 0.17
3 21.4308 13,608.3 21.0086 13,620.0 -1.97 0.09 21.0040 13,645.1 -0.02 0.18
4 22.8479 13,660.1 21.3979 13,700.4 -6.35 0.30 21.3824 13,725.8 -0.07 0.19
5 25.4741 13,983.0 25.0107 13,995.3 -1.82 0.09 25.0416 14,019.9 0.12 0.18
6 33.9970 15,359.6 33.9970 15,359.6 0.00 0.00 33.9970 15,359.6 0.00 0.00
7 53.6885 16,792.0 53.6883 16,792.0 0.00 0.00 53.8957 16,793.5 0.39 0.01
8 57.3040 17,830.1 57.3038 17,830.2 0.00 0.00 57.4813 17,836.7 0.31 0.04
9 60.2912 18,139.7 60.2911 18,139.7 0.00 0.00 60.4514 18,147.0 0.27 0.04
10 55.2454 19,002.9 55.2453 19,002.9 0.00 0.00 55.4098 19,008.9 0.30 0.03
11 57.6999 19,086.8 57.6998 19,086.8 0.00 0.00 57.8577 19,093.0 0.27 0.03
12 58.3690 19,068.7 58.3688 19,068.7 0.00 0.00 58.5245 19,075.0 0.27 0.03
13 43.9953 17,938.5 43.1070 18,170.4 -2.02 1.29 43.1998 18,171.2 0.22 0.00
14 44.4718 17,745.7 43.7222 17,941.4 -1.69 1.10 43.7481 17,959.6 0.06 0.10
15 44.3616 17,678.1 43.6423 17,868.3 -1.62 1.08 43.6488 17,891.6 0.01 0.13
16 42.8081 17,753.2 42.2550 17,898.9 -1.29 0.82 42.2095 17,935.6 -0.11 0.21
17 44.7584 18,006.6 43.9977 18,256.2 -1.70 1.39 44.0497 18,266.7 0.12 0.06
18 45.4382 19,188.0 44.9992 19,347.0 -0.97 0.83 44.9998 19,373.6 0.00 0.14
19 45.8005 18,889.7 45.2621 19,081.3 -1.18 1.01 45.3348 19,082.0 0.16 0.00
20 44.9092 18,234.1 44.5556 18,356.2 -0.79 0.67 44.6263 18,357.1 0.16 0.00
21 42.8459 18,055.8 42.4925 18,172.7 -0.82 0.65 42.5547 18,177.3 0.15 0.03
22 39.7595 17,400.5 42.3760 16,619.6 6.58 -4.49 42.3764 16,619.6 0.00 0.00
23 36.6966 16,532.1 39.6236 15,752.1 7.98 -4.72 39.6243 15,752.1 0.00 0.00
24 20.9864 15,086.3 28.0213 14,935.9 33.52 -1.00 27.1650 14,944.5 -3.06 0.06
------------------- ------------------------------------ ----------------------------------
41.4040 406,665.7 41.5599 406,676.7 0.38 0.00 41.5856 406,963.6 0.06 0.07
ITERATION #4 ITERATION #5 ITERATION #6
Hour MCP Volume % MCP % Vol MCP Volume % MCP % Vol MCP Volume % MCP % Vol
Chng Chng Chng Chng Chng Chng
- ----------------------------------------------------------------------------------------------------------
1 25.1028 13,875.9 0.00 0.00 66.5545 11,233.5 165.13 -19.04 66.5545 11,233.5 0.00 0.00
2 24.3700 13,852.3 0.00 0.00 59.7646 11,488.1 145.24 -17.07 59.7646 11,488.1 0.00 0.00
3 21.0040 13,645.1 0.00 0.00 57.5443 11,413.5 173.97 -16.35 57.5443 11,413.5 0.00 0.00
4 21.3660 13,726.2 -0.08 0.00 58.5590 11,433.6 174.08 -16.70 58.5590 11,433.6 0.00 0.00
5 25.0416 14,019.9 0.00 0.00 63.9028 11,649.3 155.19 -16.91 63.9028 11,649.3 0.00 0.00
6 33.9970 15,359.6 0.00 0.00 76.6063 12,274.3 125.33 -20.09 76.6063 12,274.3 0.00 0.00
7 53.8957 16,793.5 0.00 0.00 93.0266 12,954.7 72.60 -22.86 92.8824 12,968.2 -0.16 0.10
8 57.4813 17,836.7 0.00 0.00 89.0012 14,440.4 54.84 -19.04 88.8290 14,459.9 -0.19 0.14
9 60.4514 18,147.0 0.00 0.00 92.0143 14,545.5 52.21 -19.85 91.8674 14,561.5 -0.16 0.11
10 55.4098 19,008.9 0.00 0.00 85.4252 15,458.4 54.17 -18.68 92.6781 14,590.1 8.49 -5.62
11 57.8577 19,093.0 0.00 0.00 87.3385 15,493.3 50.95 -18.85 87.1651 15,515.8 -0.20 0.15
12 58.5245 19,075.0 0.00 0.00 87.7634 15,482.6 49.96 -18.83 87.5943 15,504.8 -0.19 0.14
13 43.1998 18,171.2 0.00 0.00 79.0559 14,156.2 83.00 -22.10 78.7859 14,175.9 -0.34 0.14
14 43.7481 17,959.6 0.00 0.00 80.1324 14,008.7 83.17 -22.00 79.9935 14,018.8 -0.17 0.07
15 43.6488 17,891.6 0.00 0.00 80.0171 13,929.1 83.32 -22.15 79.9645 13,933.0 -0.07 0.03
16 42.1850 17,941.9 -0.06 0.04 77.4086 13,864.7 83.50 -22.72 77.1426 13,883.6 -0.34 0.14
17 44.0497 18,266.7 0.00 0.00 78.8250 14,144.4 78.95 -22.57 78.5635 14,162.9 -0.33 0.13
18 44.9998 19,373.6 0.00 0.00 83.4484 14,819.4 85.44 -23.51 83.1663 14,841.5 -0.34 0.15
19 45.3348 19,082.0 0.00 0.00 76.4652 15,248.0 68.67 -20.09 83.9946 14,654.7 9.85 -3.89
20 44.6263 18,357.1 0.00 0.00 78.0904 14,317.1 74.99 -22.01 78.0202 14,322.3 -0.09 0.04
21 42.5547 18,177.3 0.00 0.00 73.9360 13,926.2 73.74 -23.39 73.8005 13,935.8 -0.18 0.07
22 42.3764 16,619.6 0.00 0.00 67.2876 13,136.1 58.79 -20.96 66.8728 13,163.0 -0.62 0.20
23 39.6243 15,752.1 0.00 0.00 60.2846 12,315.3 52.14 -21.82 60.2846 12,315.3 0.00 0.00
24 27.1650 14,944.5 0.00 0.00 48.0100 11,734.9 76.73 -21.48 48.0100 11,734.9 0.00 0.00
------------------------------- ------------------------------- --------------------------------
41.5839 406,970.3 0.00 0.00 75.0192 323,467.3 80.40 -20.52 75.5228 322,234.3 0.67 -0.38
DRAFT -- DO NOT CITE
- 45 -
Simulation Results from 11-04-98 Test
ITERATION #1 ITERATION #2 ITERATION #3
Hour MCP Volume MCP Volume % MCP % Vol MCP Volume % MCP % Vol
Chng Chng Chng Chng
- ---------------------------------------------------------------------------------------------------
1 138.7488 7,948.2 152.1834 7,963.4 9.68 0.19 154.0089 7,965.5 1.20 0.03
2 80.0820 8,257.5 83.5213 8,317.5 4.29 0.73 85.0086 8,333.1 1.78 0.19
3 74.9955 8,013.0 76.0084 8,068.3 1.35 0.69 77.0058 8,111.6 1.31 0.54
4 78.0239 8,149.5 79.0085 8,209.5 1.26 0.74 80.0054 8,263.3 1.26 0.66
5 101.3070 8,441.7 109.2207 8,444.1 7.81 0.03 112.0087 8,445.0 2.55 0.01
6 201.0481 8,538.4 211.1587 8,541.5 5.03 0.04 215.9516 8,543.0 2.27 0.02
7 225.8105 9,192.9 228.8427 9,193.9 1.34 0.01 230.5389 9,194.4 0.74 0.01
8 187.7054 10,587.2 194.7793 10,589.4 3.77 0.02 200.0079 10,591.0 2.68 0.02
9 197.5304 10,685.3 206.9756 10,691.6 4.78 0.06 211.5941 10,694.0 2.23 0.02
10 206.8824 10,730.2 216.4953 10,736.6 4.65 0.06 220.5132 10,739.3 1.86 0.03
11 211.4975 10,748.2 220.1406 10,753.9 4.09 0.05 223.1588 10,756.0 1.37 0.02
12 214.0332 10,641.3 221.7829 10,646.4 3.62 0.05 224.1089 10,648.0 1.05 0.02
13 222.1792 10,463.7 225.6048 10,466.0 1.54 0.02 228.0034 10,467.6 1.06 0.02
14 225.7341 10,190.1 235.1831 10,196.4 4.19 0.06 241.5478 10,200.6 2.71 0.04
15 225.7328 10,113.8 235.1582 10,120.1 4.18 0.06 241.5197 10,124.3 2.71 0.04
16 225.7507 10,081.2 235.1082 10,087.4 4.15 0.06 241.4570 10,091.7 2.70 0.04
17 226.1181 10,328.8 240.1522 10,338.2 6.21 0.09 247.0723 10,342.8 2.88 0.04
18 226.4257 10,944.8 240.5433 10,954.3 6.23 0.09 247.1360 10,958.7 2.74 0.04
19 226.3423 10,863.0 230.1066 10,867.2 1.66 0.04 233.1054 10,870.6 1.30 0.03
20 223.3216 10,833.9 228.5911 10,839.9 2.36 0.06 229.9367 10,841.4 0.59 0.01
21 204.4151 10,720.7 214.0269 10,731.6 4.70 0.10 218.3020 10,736.4 2.00 0.04
22 175.1481 10,428.7 177.0817 10,430.9 1.10 0.02 177.0817 10,430.9 0.00 0.00
23 141.8638 9,598.1 151.6702 9,609.3 6.91 0.12 151.7525 9,609.4 0.05 0.00
24 79.3292 9,282.8 79.9976 9,321.7 0.84 0.42 79.9976 9,321.7 0.00 0.00
------------------- -------------------------------- --------------------------------
180.0011 235,783.0 187.2226 236,119.1 4.01 0.14 190.4510 236,280.3 1.72 0.07
ITERATION #4 ITERATION #5 ITERATION #6
Hour MCP Volume % MCP % Vol MCP Volume % MCP % Vol MCP Volume % MCP % Vol
Chng Chng Chng Chng Chng Chng
- ------------------------------------------------------------------------------------------------------------
1 155.0081 7,966.6 0.65 0.01 156.0076 7,967.8 0.64 0.02 156.0076 7,967.8 0.00 0.00
2 87.0068 8,352.1 2.35 0.23 88.0062 8,355.0 1.15 0.03 88.0062 8,355.0 0.00 0.00
3 79.2806 8,209.4 2.95 1.21 79.2987 8,209.9 0.02 0.01 79.2987 8,209.9 0.00 0.00
4 80.0054 8,263.3 0.00 0.00 80.8139 8,281.6 1.01 0.22 80.8139 8,281.6 0.00 0.00
5 115.0072 8,445.9 2.68 0.01 116.0067 8,446.2 0.87 0.00 116.0067 8,446.2 0.00 0.00
6 220.0005 8,544.2 1.87 0.01 220.2271 8,544.3 0.10 0.00 220.2271 8,544.3 0.00 0.00
7 232.4418 9,195.0 0.83 0.01 234.5451 9,195.6 0.90 0.01 235.0967 9,195.8 0.24 0.00
8 205.0019 10,592.5 2.50 0.01 206.0008 10,592.8 0.49 0.00 206.0008 10,592.8 0.00 0.00
9 215.0037 10,696.9 1.61 0.03 216.0019 10,697.6 0.46 0.01 216.0019 10,697.6 0.00 0.00
10 220.5132 10,739.3 0.00 0.00 220.5132 10,739.3 0.00 0.00 220.5132 10,739.3 0.00 0.00
11 223.1588 10,756.0 0.00 0.00 223.1588 10,756.0 0.00 0.00 223.1588 10,756.0 0.00 0.00
12 224.1089 10,648.0 0.00 0.00 224.1089 10,648.0 0.00 0.00 224.1089 10,648.0 0.00 0.00
13 230.0070 10,468.9 0.88 0.01 232.8327 10,470.8 1.23 0.02 234.0060 10,471.6 0.50 0.01
14 245.5774 10,203.3 1.67 0.03 245.6651 10,203.4 0.04 0.00 245.6651 10,203.4 0.00 0.00
15 245.5527 10,127.0 1.67 0.03 245.6375 10,127.1 0.03 0.00 245.6375 10,127.1 0.00 0.00
16 245.5036 10,094.4 1.68 0.03 245.8242 10,094.6 0.13 0.00 245.8242 10,094.6 0.00 0.00
17 249.4611 10,344.4 0.97 0.02 249.5189 10,344.4 0.02 0.00 249.5189 10,344.4 0.00 0.00
18 249.4218 10,960.2 0.92 0.01 249.4814 10,960.2 0.02 0.00 249.4814 10,960.2 0.00 0.00
19 235.8417 10,873.7 1.17 0.03 235.8417 10,873.7 0.00 0.00 235.8417 10,873.7 0.00 0.00
20 229.9367 10,841.4 0.00 0.00 229.9367 10,841.4 0.00 0.00 229.9367 10,841.4 0.00 0.00
21 218.3020 10,736.4 0.00 0.00 218.3020 10,736.4 0.00 0.00 218.3020 10,736.4 0.00 0.00
22 177.0817 10,430.9 0.00 0.00 177.0817 10,430.9 0.00 0.00 177.0817 10,430.9 0.00 0.00
23 151.7525 9,609.4 0.00 0.00 151.7525 9,609.4 0.00 0.00 151.7525 9,609.4 0.00 0.00
24 79.9976 9,321.7 0.00 0.00 79.9976 9,321.7 0.00 0.00 79.9976 9,321.7 0.00 0.00
-------------------------------- -------------------------------- --------------------------------
192.2905 236,420.9 0.97 0.06 192.7734 236,448.1 0.25 0.01 192.8452 236,449.1 0.04 0.00
DRAFT -- DO NOT CITE
- 46 -
Simulation Results from 11-05-98 Test
ITERATION #1 ITERATION #2 ITERATION #3
Hour MCP Volume MCP Volume % MCP % Vol MCP Volume % MCP % Vol
Chng Chng Chng Chng
- ---------------------------------------------------------------------------------------------------
1 17.3078 15,390.4 14.4685 15,404.4 -16.40 0.09 12.8492 15,609.4 -11.19 1.33
2 13.9991 14,970.7 12.4184 15,163.9 -11.29 1.29 10.9207 15,319.4 -12.06 1.03
3 12.4703 14,732.1 10.9990 14,891.0 -11.80 1.08 9.8170 14,945.9 -10.75 0.37
4 12.5388 14,851.2 11.0081 14,929.3 -12.21 0.53 9.7430 15,065.3 -11.49 0.91
5 16.7483 15,337.0 14.9915 15,346.3 -10.49 0.06 12.4749 15,554.5 -16.79 1.36
6 24.5189 16,991.3 22.1606 17,004.3 -9.62 0.08 21.9969 17,257.8 -0.74 1.49
7 27.0070 18,938.3 27.0001 19,162.3 -0.03 1.18 27.0001 19,162.3 0.00 0.00
8 27.9966 20,034.3 27.4453 20,050.2 -1.97 0.08 27.3943 20,050.9 -0.19 0.00
9 29.9947 20,760.2 29.4329 20,800.1 -1.87 0.19 29.3229 20,801.1 -0.37 0.00
10 29.3145 21,338.9 28.9956 21,354.5 -1.09 0.07 28.8304 21,356.1 -0.57 0.01
11 30.3527 21,667.2 30.0079 21,693.8 -1.14 0.12 31.9866 21,635.3 6.59 -0.27
12 31.9899 21,723.8 31.9866 21,735.2 -0.01 0.05 33.9961 21,682.6 6.28 -0.24
13 34.9911 21,686.9 34.9917 21,701.3 0.00 0.07 34.9725 21,701.8 -0.05 0.00
14 35.9751 21,714.8 35.7730 21,739.6 -0.56 0.11 35.9715 21,755.0 0.55 0.07
15 36.0015 21,580.8 36.7892 21,556.5 2.19 -0.11 36.1826 21,586.5 -1.65 0.14
16 36.0021 21,324.3 37.5484 21,265.2 4.30 -0.28 36.9764 21,295.2 -1.52 0.14
17 36.0050 21,588.6 39.9924 21,402.5 11.07 -0.86 39.5062 21,441.7 -1.22 0.18
18 42.9643 22,625.4 41.9919 22,694.0 -2.26 0.30 42.4001 22,697.5 0.97 0.02
19 43.5176 22,396.9 42.9027 22,444.4 -1.41 0.21 43.2025 22,453.9 0.70 0.04
20 39.1212 21,954.2 38.5965 21,999.5 -1.34 0.21 38.4921 22,030.2 -0.27 0.14
21 34.9773 21,234.6 34.9783 21,249.0 0.00 0.07 34.9730 21,249.1 -0.02 0.00
22 27.9944 19,823.3 27.4769 19,839.0 -1.85 0.08 27.4811 19,840.2 0.02 0.01
23 24.9585 17,462.8 24.0005 17,472.3 -3.84 0.05 23.4731 17,476.1 -2.20 0.02
24 15.6528 16,055.7 13.1182 16,270.0 -16.19 1.33 11.8672 16,324.0 -9.54 0.33
----------------- ------------------------------- ---------------------------------
28.4333 466,183.7 27.8781 467,168.6 -1.95 0.21 27.5763 468,291.8 -1.08 0.24
ITERATION #4 ITERATION #5 ITERATION #6
Hour MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol Chng MCP Volume % MCP %
Chng Chng Chng Vol
Chng
- ----------------------------------------------------------------------------------------------------------
1 11.7593 15,812.7 -8.48 1.30 11.3274 15,814.0 -3.67 0.01 11.0067 15,898.0 -2.83 0.53
2 10.0000 15,472.8 -8.43 1.00 9.6949 15,523.8 -3.05 0.33 9.3690 15,538.7 -3.36 0.10
3 8.9705 15,099.4 -8.62 1.03 8.4862 15,101.4 -5.40 0.01 8.0945 15,150.3 -4.62 0.32
4 9.3275 15,217.1 -4.26 1.01 9.0082 15,218.4 -3.42 0.01 9.0083 15,229.5 0.00 0.07
5 12.5672 15,704.2 0.74 0.96 12.0488 15,705.9 -4.13 0.01 12.0688 15,805.8 0.17 0.64
6 21.9969 17,257.8 0.00 0.00 21.9969 17,257.8 0.00 0.00 21.9969 17,257.8 0.00 0.00
7 27.0001 19,162.3 0.00 0.00 27.0001 19,162.3 0.00 0.00 27.0001 19,162.3 0.00 0.00
8 27.3943 20,050.9 0.00 0.00 27.3943 20,050.9 0.00 0.00 27.3943 20,050.9 0.00 0.00
9 29.3229 20,801.1 0.00 0.00 29.3229 20,801.1 0.00 0.00 29.3229 20,801.1 0.00 0.00
10 28.8304 21,356.1 0.00 0.00 28.8304 21,356.1 0.00 0.00 28.8304 21,356.1 0.00 0.00
11 31.2923 21,683.2 -2.17 0.22 31.0315 21,690.7 -0.83 0.03 31.0315 21,690.7 0.00 0.00
12 33.0078 21,719.7 -2.91 0.17 33.0049 21,726.9 -0.01 0.03 33.0049 21,726.9 0.00 0.00
13 34.9385 21,727.8 -0.10 0.12 34.9385 21,727.8 0.00 0.00 34.9385 21,727.8 0.00 0.00
14 35.9715 21,755.0 0.00 0.00 35.9715 21,755.0 0.00 0.00 35.9715 21,755.0 0.00 0.00
15 35.9973 21,595.6 -0.51 0.04 35.9804 21,596.5 -0.05 0.00 36.4949 21,596.5 1.43 0.00
16 36.4947 21,318.7 -1.30 0.11 36.4947 21,318.7 0.00 0.00 36.7719 21,305.2 0.76 -0.06
17 39.5062 21,441.7 0.00 0.00 39.5062 21,441.7 0.00 0.00 39.9936 21,399.5 1.23 -0.20
18 42.4001 22,697.5 0.00 0.00 42.4001 22,697.5 0.00 0.00 43.9960 22,587.7 3.76 -0.48
19 43.2025 22,453.9 0.00 0.00 43.2025 22,453.9 0.00 0.00 44.5863 22,358.1 3.20 -0.43
20 38.4921 22,030.2 0.00 0.00 44.9906 21,639.5 16.88 -1.77 44.9938 21,689.4 0.01 0.23
21 34.9746 21,274.1 0.00 0.12 34.9746 21,274.1 0.00 0.00 34.9746 21,274.1 0.00 0.00
22 27.4811 19,840.2 0.00 0.00 27.4811 19,840.2 0.00 0.00 27.4811 19,840.2 0.00 0.00
23 23.3378 17,476.6 -0.58 0.00 23.1920 17,477.2 -0.62 0.00 23.1752 17,477.3 -0.07 0.00
24 11.9922 16,462.5 1.05 0.85 11.7817 16,474.3 -1.76 0.07 11.7817 16,474.3 0.00 0.00
------------------------------- -------------------------------- --------------------------------
27.3441 469,411.1 -0.84 0.24 27.5025 469,105.7 0.58 -0.07 27.6370 469,153.2 0.49 0.01
DRAFT -- DO NOT CITE
- 47 -
Simulation Results from 11-05-98 Test (continued)
ITERATION #7 ITERATION #8 ITERATION #9
Hour MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol
Chng Chng Chng Chng
- ---------------------------------------------------------------------------------------------------------
1 11.0067 15,898.0 0.00 0.00 11.0067 15,898.0 0.00 0.00 11.0067 15,898.0 0.00 0.00
2 9.3690 15,538.7 0.00 0.00 9.3690 15,538.7 0.00 0.00 9.3690 15,538.7 0.00 0.00
3 8.0948 15,153.0 0.00 0.02 7.7277 15,154.5 -4.54 0.01 7.3987 15,155.9 -4.26 0.01
4 9.0083 15,229.5 0.00 0.00 9.0083 15,229.5 0.00 0.00 9.0083 15,229.5 0.00 0.00
5 12.0688 15,805.8 0.00 0.00 12.0688 15,805.8 0.00 0.00 12.0688 15,805.8 0.00 0.00
6 21.9969 17,257.8 0.00 0.00 21.9969 17,257.8 0.00 0.00 21.9969 17,257.8 0.00 0.00
7 27.0001 19,162.3 0.00 0.00 27.0001 19,162.3 0.00 0.00 27.0001 19,162.3 0.00 0.00
8 27.3943 20,050.9 0.00 0.00 27.3943 20,050.9 0.00 0.00 27.3943 20,050.9 0.00 0.00
9 29.3229 20,801.1 0.00 0.00 29.3229 20,801.1 0.00 0.00 29.3229 20,801.1 0.00 0.00
10 28.8304 21,356.1 0.00 0.00 28.8304 21,356.1 0.00 0.00 28.8304 21,356.1 0.00 0.00
11 31.0315 21,690.7 0.00 0.00 31.0315 21,690.7 0.00 0.00 31.0315 21,690.7 0.00 0.00
12 33.0049 21,726.9 0.00 0.00 33.0049 21,726.9 0.00 0.00 33.0049 21,726.9 0.00 0.00
13 34.9385 21,727.8 0.00 0.00 34.9385 21,727.8 0.00 0.00 34.9385 21,727.8 0.00 0.00
14 35.9715 21,755.0 0.00 0.00 35.9715 21,755.0 0.00 0.00 35.9715 21,755.0 0.00 0.00
15 36.4949 21,596.5 0.00 0.00 36.4949 21,596.5 0.00 0.00 36.4949 21,596.5 0.00 0.00
16 36.7719 21,305.2 0.00 0.00 36.7719 21,305.2 0.00 0.00 36.7719 21,305.2 0.00 0.00
17 39.9936 21,399.5 0.00 0.00 39.9936 21,399.5 0.00 0.00 26.9196 19,770.5 -32.69 -7.61
18 43.7381 22,601.4 -0.59 0.06 43.5624 22,610.7 -0.40 0.04 43.5824 22,610.7 0.05 0.00
19 44.3227 22,371.1 -0.59 0.06 44.0074 22,393.3 -0.71 0.10 44.0022 22,406.5 -0.01 0.06
20 44.9930 21,689.4 0.00 0.00 44.9930 21,689.4 0.00 0.00 44.9930 21,689.4 0.00 0.00
21 34.9746 21,274.1 0.00 0.00 34.9746 21,274.1 0.00 0.00 34.9746 21,274.1 0.00 0.00
22 27.4811 19,840.2 0.00 0.00 27.4811 19,840.2 0.00 0.00 27.4811 19,840.2 0.00 0.00
23 23.2088 17,483.3 0.14 0.03 23.2088 17,483.3 0.00 0.00 23.2088 17,483.3 0.00 0.00
24 11.7817 16,474.3 0.00 0.00 11.7817 16,474.3 0.00 0.00 11.7817 16,474.3 0.00 0.00
------------------------------- -------------------------------- --------------------------------
27.6166 469,188.6 -0.07 0.01 27.5809 469,221.6 -0.13 0.01 27.0230 467,607.2 -2.02 -0.34
ITERATION #10 ITERATION #11
Hour MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol
Chng Chng Chng
- -----------------------------------------------------------------------
1 11.0067 15,898.0 0.00 0.00 11.0067 15,898.0 0.00 0.00
2 9.3690 15,538.7 0.00 0.00 9.3690 15,538.7 0.00 0.00
3 7.3987 15,155.9 0.00 0.00 7.3987 15,155.9 0.00 0.00
4 9.0083 15,229.5 0.00 0.00 9.0083 15,229.5 0.00 0.00
5 12.0688 15,805.8 0.00 0.00 12.0688 15,805.8 0.00 0.00
6 21.9969 17,257.8 0.00 0.00 21.9969 17,257.8 0.00 0.00
7 27.0001 19,162.3 0.00 0.00 27.0001 19,162.3 0.00 0.00
8 27.3943 20,050.9 0.00 0.00 27.3943 20,050.9 0.00 0.00
9 29.3229 20,801.1 0.00 0.00 29.3229 20,801.1 0.00 0.00
10 28.8304 21,356.1 0.00 0.00 28.8304 21,356.1 0.00 0.00
11 31.0315 21,690.7 0.00 0.00 31.0315 21,690.7 0.00 0.00
12 33.0049 21,726.9 0.00 0.00 33.0049 21,726.9 0.00 0.00
13 34.9385 21,727.8 0.00 0.00 34.9385 21,727.8 0.00 0.00
14 35.9715 21,755.0 0.00 0.00 35.9715 21,755.0 0.00 0.00
15 36.4949 21,596.5 0.00 0.00 36.4949 21,596.5 0.00 0.00
16 36.7719 21,305.2 0.00 0.00 36.7719 21,305.2 0.00 0.00
17 26.8840 19,770.7 -0.13 0.00 27.3848 20,018.3 1.86 1.25
18 43.5624 22,610.7 -0.05 0.00 43.5624 22,610.7 0.00 0.00
19 44.0022 22,406.5 0.00 0.00 44.0022 22,406.5 0.00 0.00
20 44.9930 21,689.4 0.00 0.00 44.9930 21,689.4 0.00 0.00
21 34.9746 21,274.1 0.00 0.00 34.9746 21,274.1 0.00 0.00
22 27.4811 19,840.2 0.00 0.00 27.4811 19,840.2 0.00 0.00
23 23.2088 17,483.3 0.00 0.00 23.2088 17,483.3 0.00 0.00
24 11.7817 16,474.3 0.00 0.00 11.7817 16,474.3 0.00 0.00
------------------------------- --------------------------------
27.0207 467,607.4 -0.01 0.00 7.0416 467,855.0 0.08 0.05
DRAFT -- DO NOT CITE
- 48 -
Simulation Results from 11-06-98 Test
ITERATION #1 ITERATION #2 ITERATION #3
Hour MCP Volume MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol
Chng Chng Chng
- ------------------------------------------------------------------------------------------------
1 26.2162 12,311.3 26.5538 12,423.3 1.29 0.91 26.4616 12,450.7 -0.35 0.22
2 25.7248 12,060.2 25.9908 12,193.2 1.03 1.10 25.8920 12,220.6 -0.38 0.22
3 25.0860 11,806.8 25.3588 11,938.2 1.09 1.11 25.2262 11,975.5 -0.52 0.31
4 25.2161 11,910.2 25.5539 12,025.6 1.34 0.97 25.3808 12,073.0 -0.68 0.39
5 25.9579 12,281.9 26.2319 12,408.9 1.06 1.03 26.1490 12,433.1 -0.32 0.20
6 31.0038 12,241.4 31.0108 12,245.8 0.02 0.04 31.0108 12,245.8 0.00 0.00
7 34.4429 12,754.9 34.3287 12,808.8 -0.33 0.42 39.6478 13,094.7 15.49 2.23
8 34.3445 13,648.2 34.2360 13,702.2 -0.32 0.40 39.5576 14,099.7 15.54 2.90
9 35.0502 13,927.8 34.9790 13,967.4 -0.20 0.28 39.6745 14,866.9 13.42 6.44
10 35.8670 14,005.1 35.0125 14,382.2 -2.38 2.69 39.8910 14,943.5 13.93 3.90
11 36.3252 14,136.2 35.0183 14,716.3 -3.60 4.10 40.0238 15,001.3 14.29 1.94
12 36.4531 14,177.9 37.7480 14,949.3 3.55 5.44 38.6936 14,990.3 2.51 0.27
13 35.9794 14,377.1 37.3897 15,227.0 3.92 5.91 37.9921 15,237.7 1.61 0.07
14 36.3902 14,228.4 37.7658 14,955.1 3.78 5.11 38.7239 14,999.4 2.54 0.30
15 36.6297 13,996.2 37.8272 14,765.9 3.27 5.50 38.8606 14,807.0 2.73 0.28
16 36.2164 13,929.9 37.5654 14,703.4 3.72 5.55 38.2704 14,744.2 1.88 0.28
17 35.9998 14,031.4 37.3128 14,887.4 3.65 6.10 37.8089 14,888.0 1.33 0.00
18 36.9472 14,484.0 38.1305 15,190.8 3.20 4.88 39.0371 15,191.8 2.38 0.01
19 36.8297 14,406.3 38.0382 15,114.1 3.28 4.91 38.9951 15,115.2 2.52 0.01
20 36.9401 13,981.2 38.0692 14,688.0 3.06 5.06 39.0097 14,689.0 2.47 0.01
21 36.0095 13,821.7 37.6394 14,451.5 4.53 4.56 38.4370 14,492.4 2.12 0.28
22 34.9741 13,320.4 34.9712 13,330.5 -0.01 0.08 38.1858 13,645.9 9.19 2.37
23 30.0084 13,516.5 30.0084 13,523.4 0.00 0.05 30.0084 13,523.4 0.00 0.00
24 27.2733 13,175.7 27.6873 13,254.5 1.52 0.60 27.6633 13,262.0 -0.09 0.06
----------------- -------------------------------- -------------------------------
32.9952 322,530.7 33.5178 331,852.8 1.58 2.89 35.0250 334,991.1 4.50 0.95
ITERATION #4 ITERATION #5 ITERATION #6
Hour MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol
Chng Chng Chng Chng
- -----------------------------------------------------------------------------------------------------------
1 26.4616 12,450.7 0.00 0.00 26.4616 12,450.7 0.00 0.00 29.0627 11,726.1 9.83 -5.82
2 25.8920 12,220.6 0.00 0.00 25.8920 12,220.6 0.00 0.00 27.7294 11,716.5 7.10 -4.13
3 25.2262 11,975.5 0.00 0.00 25.2262 11,975.5 0.00 0.00 26.6901 11,564.2 5.80 -3.43
4 25.3808 12,073.0 0.00 0.00 25.3808 12,073.0 0.00 0.00 26.9927 11,632.6 6.35 -3.65
5 26.1490 12,433.1 0.00 0.00 26.1490 12,433.1 0.00 0.00 27.9153 11,923.9 6.75 -4.10
6 31.0108 12,245.8 0.00 0.00 31.0108 12,245.8 0.00 0.00 33.9861 11,274.1 9.59 -7.93
7 42.5951 13,198.0 7.43 0.79 44.8593 13,355.4 5.32 1.19 46.9592 12,970.3 4.68 -2.88
8 42.5822 13,990.0 7.65 -0.78 44.9342 13,169.3 5.52 -5.87 46.9818 13,801.8 4.56 4.80
9 42.6079 14,680.2 7.39 -1.26 44.9368 13,838.5 5.47 -5.73 46.9856 14,342.9 4.56 3.64
10 42.9135 14,756.8 7.58 -1.25 44.9775 14,915.4 4.81 1.07 46.9966 14,369.3 4.49 -3.66
11 43.1266 14,764.8 7.75 -1.58 45.7784 15,329.1 6.15 3.82 47.9743 14,383.4 4.80 -6.17
12 38.9861 14,750.7 0.76 -1.60 38.9340 14,850.6 -0.13 0.68 39.4554 13,851.2 1.34 -6.73
13 38.5459 15,031.8 1.46 -1.35 38.2888 15,130.7 -0.67 0.66 39.3012 14,135.0 2.64 -6.58
14 38.9916 14,760.6 0.69 -1.59 39.3480 14,862.2 0.91 0.69 41.7694 13,923.1 6.15 -6.32
15 39.0198 14,567.2 0.41 -1.62 39.4967 14,667.7 1.22 0.69 41.9506 13,720.5 6.21 -6.46
16 38.9040 14,504.9 1.66 -1.62 38.8913 14,604.9 -0.03 0.69 41.3500 13,657.6 6.32 -6.49
17 38.3201 14,688.5 1.35 -1.34 38.0648 14,788.2 -0.67 0.68 39.2566 13,789.6 3.13 -6.75
18 39.1529 14,952.0 0.30 -1.58 39.5749 14,052.4 1.08 -6.02 41.3287 14,104.4 4.43 0.37
19 39.1136 14,875.3 0.30 -1.59 39.5498 13,975.8 1.12 -6.05 41.1963 14,027.6 4.16 0.37
20 39.1333 14,449.1 0.32 -1.63 39.0818 14,549.1 -0.13 0.69 39.5830 13,549.6 1.28 -6.87
21 38.9381 14,252.9 1.30 -1.65 39.0622 14,353.1 0.32 0.70 41.3941 13,455.7 5.97 -6.25
22 38.9032 13,413.1 1.88 -1.71 39.1560 13,515.6 0.65 0.76 41.3054 12,637.1 5.49 -6.50
23 30.5898 13,321.1 1.94 -1.50 30.5898 13,321.1 0.00 0.00 33.3942 12,348.7 9.17 -7.30
24 27.6633 13,262.0 0.00 0.00 27.6633 13,262.0 0.00 0.00 30.0092 12,350.8 8.48 -6.87
-------------------------------- ------------------------------- ------------------------------
35.8420 331,617.7 2.33 -1.01 36.3878 329,939.8 1.52 -0.51 38.3153 315,256.0 5.30 -4.45
DRAFT -- DO NOT CITE
- 49 -
Simulation Results from 11-07-98 Test
ITERATION #1 ITERATION #2 ITERATION #3
Hour MCP Volume MCP Volume % MCP % Vol Chng MCP Volume % MCP % Vol
Chng Chng Chng
- -------- ------------------ ---------------------------------------------------------------------------------
1 22.0006 13,737.4 22.0094 15,412.8 0.04 12.20 22.0094 15,412.8 0.00 0.00
2 21.3668 13,360.7 22.0024 15,253.2 2.97 14.16 22.0084 15,253.2 0.03 0.00
3 20.1368 12,919.4 20.8330 14,937.8 3.46 15.62 21.3871 15,042.5 2.66 0.70
4 20.2909 12,997.9 20.9663 15,023.7 3.33 15.59 21.5239 15,109.8 2.66 0.57
5 20.9614 13,472.6 21.9801 15,380.7 4.86 14.16 22.0045 15,384.1 0.11 0.02
6 22.6785 14,271.2 25.0021 15,903.6 10.25 11.44 25.3677 15,976.0 1.46 0.46
7 26.2906 15,634.5 26.7357 17,746.9 1.69 13.51 26.7357 17,746.9 0.00 0.00
8 26.1286 16,356.8 26.6362 18,474.0 1.94 12.94 27.0057 18,549.7 1.39 0.41
9 27.7447 17,028.0 28.3713 18,875.6 2.26 10.85 28.9722 18,893.2 2.12 0.09
10 27.9841 17,555.3 32.2385 18,876.7 15.20 7.53 32.9741 18,937.8 2.28 0.32
11 27.9874 17,893.5 34.5337 19,035.1 23.39 6.38 35.2658 19,085.4 2.12 0.26
12 27.9885 17,969.4 34.8165 18,975.7 24.40 5.60 35.5569 19,026.0 2.13 0.27
13 27.9861 17,868.9 31.5605 19,134.8 12.77 7.08 32.5469 19,138.1 3.13 0.02
14 27.9879 17,798.7 33.2617 18,947.4 18.84 6.45 33.9972 19,018.4 2.21 0.37
15 27.9867 17,592.6 32.9779 18,760.9 17.83 6.64 33.6803 18,891.9 2.13 0.70
16 27.9859 17,443.4 32.9722 18,612.0 17.82 6.70 33.6780 18,729.7 2.14 0.63
17 27.9884 17,892.7 34.6769 18,914.3 23.90 5.71 35.4189 18,964.5 2.14 0.27
18 33.1555 19,161.4 40.0076 19,791.4 20.67 3.29 40.6111 19,900.8 1.51 0.55
19 32.1264 19,051.0 40.0053 19,658.1 24.52 3.19 40.5881 19,824.1 1.46 0.84
20 32.3741 18,498.0 40.0028 19,121.8 23.56 3.37 40.5438 19,347.8 1.35 1.18
21 28.3022 17,904.1 36.7389 18,804.7 29.81 5.03 37.7707 18,809.4 2.81 0.02
22 27.9815 16,709.8 28.8557 18,324.6 3.12 9.66 29.5820 18,330.8 2.52 0.03
23 25.0003 15,147.9 26.8779 16,521.0 7.51 9.06 27.5519 16,599.7 2.51 0.48
24 22.1283 14,245.7 24.7335 16,000.1 11.77 12.32 25.0065 16,041.9 1.10 0.26
------------------ -------------------------------------- --------------------------------------
26.3568 392,510.9 29.9498 426,486.9 13.63 8.66 30.4911 428,014.5 1.81 0.36
ITERATION #4
Hour MCP Volume % MCP Chng % Vol
Chng
- --------------------------------------------
1 22.0094 15,412.8 0.00 0.00
2 22.0084 15,253.2 0.00 0.00
3 21.3871 15,042.5 0.00 0.00
4 21.5239 15,109.8 0.00 0.00
5 22.0082 15,384.6 0.02 0.00
6 25.3133 15,960.3 -0.21 -0.10
7 30.1917 17,030.7 12.93 -4.04
8 30.0070 17,790.1 11.11 -4.09
9 35.3969 18,131.6 22.18 -4.03
10 39.7867 18,159.1 20.66 -4.11
11 40.0090 18,433.2 13.45 -3.42
12 40.0062 18,405.9 12.51 -3.26
13 38.5634 18,490.7 18.49 -3.38
14 39.9955 18,250.5 17.64 -4.04
15 39.9948 18,050.3 18.75 -4.45
16 39.6743 17,964.0 17.80 -4.09
17 40.0056 18,333.2 12.95 -3.33
18 41.2175 18,915.3 1.49 -4.95
19 41.1927 18,838.6 1.49 -4.97
20 41.1604 18,362.3 1.52 -5.09
21 40.5645 18,152.5 7.40 -3.49
22 36.0073 17,697.8 21.72 -3.45
23 27.5519 16,599.7 0.00 0.00
24 25.0065 16,041.9 0.00 0.00
-------------------------------------
33.3576 415,810.6 9.40 -2.85