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Project Title: |
Market Interactions and Market Power |
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Research/Application Need: |
As the US moves towards competitive markets in electric power generation, considerable effort has been focused on issues of ancillary service markets, and potential system security consequences of differences between contracted services and the physical supply of power services. Such service requirements introduce uncertainties that must be included in the security of delivery. These issues relate primarily to the contingent state behavior of the system, on time scales of minutes to hours. The impact of changes and uncertainties in system operation on contingent contracts has also, to date, been largely overlooked. The decoupling of responsibility for maintaining system security from the ownership of facilities provides a source of new problems. The natural question arises as to what contract terms and incentives will exist for all agents to invest engineering time into the careful design, operation, and maintenance of the overall system. This question becomes more pressing if the added operational uncertainties in a restructured environment make generation scheduling, demand scheduling, and operation more difficult. Note that most decisions have significant impact on the scheduling of the system, and therefore significant impact on the economic "bottom line." |
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Research Stem |
1. |
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Academic Team Members: |
Gerald B. Sheblé lead (ISU); D. Berleant (ISU); R. Thomas (Cornell) |
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Industry Team Members: |
Dale Stevens (MidAmerican) |
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Research/Application Area: |
Markets |
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Start and End Dates: |
Start – September 2000. End – September 2001 |
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Budget |
$### |
Project Description:
This project is
intended to achieve two goals. First
will be the characterization of market interaction between primary energy
exchange and reserve margin requirements as driven by market actions given
market forecast uncertainty. Second
will be proposals of market power philosophies, and specific market designs,
that offer quantitative schemes for ensuring system enhancement under a wide
range of operating condition uncertainties.
The theoretical underpinnings of such an approach are known in the economic
and market literature. It is primarily
proposed to evaluate the effect of uncertainties in the price bidding and
matching of such systems for such an array of contracts. Some the recent tools of probability and
statistics theory, such as interval analysis, and parametric programming will
be brought to bear on these problems.
Potential Benefits:
Standardized market interaction and base line strategies to facilitate secure addition of competitive resources from all agents units, including widespread distribution level equipment. The benefits of properly assessing uncertainties, even when such uncertainties can be measured, enable the proper pricing of the primary product, energy, and all supportive, ancillary services.
Deliverables:
Biannual project reports on progress. Prototype designs for market models for primary energy delivery and for contingent services (spinning reserves, regulation, load balance, ready reserves, and credit reserve) for competitive agents. Test-bed system indicating system benefits of these uncertainties evaluation tools when interacting with competitively driven bidding of energy dispatch and ancillary service provisions.
Technical Approach:
The objective in previous studies was to guarantee that market risk was not dominated by any single contract. Clearly, contract behavior and control challenges arise as large numbers of independent, for profit companies trade for risk management based on the latest information of the equipment and the capability of system operation. The proposed project would consolidate and extend these preliminary results, considering their application to more widespread supportive markets such as spinning reserves, ready reserves, load balance and regulation markets. This project would tailor auction and bidding designs to a competitive power system environment, as well as examine results in trajectory sensitive markets as contracts change based on new information.
The
technique we will use, IBDO, discretizes input distributions by using a list of
numerical intervals that span the range of the distribution and associating
with each interval the probability that a sample drawn from the distribution
would fall within it. A relatively
straightforward convolution process does a sum, product, or other operation on
two inputs that are known to be independent.
In the case of unknown dependency, an optimization process is used to
calculate strategic points on the envelopes describing the outputs. This process (Berleant and Goodman-Strauss
1998) is both simpler and more flexible than a technique addressing the problem
described by Williamson and Downs (1990).
Work Plan:
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Task |
Description and Completion Date |
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1 |
6 months: Extend ISU contract models with existing contingent strategies for risk management. |
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2 |
9 months: Augment model system to examine significant uncertainties at transmission and distribution levels as well as generation and demand levels. |
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3 |
12 months: Examine interaction of generator company and energy service company contracts with transaction-based unit commitment and dispatch algorithms. First proposal for active bidding designs for generation companies in competitive generation units. |
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4 |
18 months: Prototype "cooperative" contract strategies for generation companies, integrating ISO operational decisions with local decisions of unit owner. |
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5 |
24 months: Prototype "cooperative" contract strategies for energy service companies: integrating enhanced configuration estimation for market analysis, incorporate ancillary services of demand responsive to supportive services. |
Related Work:
Various PSERC teams have and are investigating the impact of market designs and of market interaction with the network. Such work includes the following projects:
· Costing and Pricing of Ancillary Services
· Market Mechanisms for Competitive Electricity.
·
An
Internet Platform For Simulating Competitive Bidding For Unit Commitment and
Schedule
·
Assessment
of Transmission Constraint Costs: Northeast U.S. Case Study
·
Fast
Determination of Simultaneous Available Transfer Capability (ATC)
·
Optimal
Power Flow Formulation in Market of Retail Wheeling
·
Designing
Cost Effective Demand Management Contracts using Game Theory
·
Markets
for Electric Power: Experimental Results for Alternative Auction Institutions
·
The
Design of Optimal Demand Management Programs
·
Market
Power: A Dynamic Definition
·
Alternative
Auction Institutions for Purchasing Electric Power: An Experimental Examination
·
The
Efficiency of Multi-Unit Electricity Auctions
·
Exotic
Electricity Options and the Valuation of Electricity Generation and
Transmission Assets
·
Multi-unit
Auctions With Complementarities: Issues of Efficiency in Electricity Auctions
·
Capturing
Non-Convexities in Multi-Unit Electricity Auctions
·
Priority
Network Access Pricing for Electric Power
·
Price-Based
Adaptive Spinning Reserve Requirements in Power System Scheduling
·
Energy
Auctions and Market Power: An Experimental Examination
·
Market
Power and Price Volatility in Restructured Markets for Electricity
·
Managing
Transmission Risk: The Theory of Spatial Hedging and Arbitrage
·
Stochastic
Models of Energy Commodity Prices and Their Applications: Mean-reversion with Jumps
and Spikes
·
Designing
Cost Effective Demand Management Contracts using Game Theory
·
Estimating
the Volatility of Spot Prices in Restructured Electricity Markets and the
Implications for Option Values
Such projects are related to this
project but do not include uncertainty on a contract or market basis while
considering multiple market efficiency.
Risk management requires efficient contract trading through efficient,
liquid markets.
How This Work Differs
From Related Work:
Many useful
calculations are simple when we know precisely what the values of the variables
are. However, when we apply such
calculations to real world problems, precise values are frequently not
justified by the knowledge available, and indeed may not be practically
obtainable at all. Too often, the
approach taken in such cases is to use precise values despite there being only
approximations of unknown actual values. While this allows easy calculation of
numerical outputs, those outputs generally deviate to a greater or lesser
degree from the true values. When the
implications of an inaccurate output are significant, as when significant
amounts of financial or other resources are involved, such approximations can
be costly; on the other hand, techniques that account for uncertainty in the
inputs can lead to significant savings.
Diverse
techniques have been described for calculating with variables that are
uncertain. Ideally, a technique should
avoid approximating distributions used to describe uncertain inputs, because
avoidance of approximation is the reason for applying such a technique in the
first place. A technique should also be
robustly applicable, and not require that uncertainty be expressed using
Gaussian or other predefined distribution types. Finally, a technique should avoid assuming that input
distributions are independent of one another or have any other predefined
dependency relationship, a non-trivial requirement. These factors lead us to propose using the technique of
interval-based distribution operations (IBDO).
This technique discretizes input distribution curves and hence can
handle arbitrary distributions.
Further, this technique avoids approximations by using discretizations
that provide an envelope around the input curve being discretized, thereby
using a strategy of bounding instead of approximating. Outputs are also bounding envelopes. In this technique, inputs for which the
dependency relationship is unknown lead to widened output envelopes that
incorporate the additional uncertainty this poses while retaining the
philosophy of bounding instead of approximating.
Status
Started October 15, 2000