Strategic bidding of transmission-constrained GENCOs with incomplete information

Strategic bidding of transmission-constrained GENCOs with incomplete information

This work describes a method for analyzing the competition among transmission-constrained generating companies (GENCOs) with incomplete information. Each GENCO models its opponents' unknown information with specific types for transforming the incomplete game into a complete game with imperfect...

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Bibliographic Details
Published in:IEEE transactions on power systems 2005-02, Vol.20 (1), p.437-447
Main Authors: Tao Li, Shahidehpour, M.
Format: Article
Language:eng
Subjects:
Bayesian Nash equilibrium
Clearing
Competition
Costs
Drives
electricity market
Electricity supply industry
Game theory
Games
GENCOs
incomplete and complete games
Information analysis
ISO
Markets
Mathematical analysis
Mathematical models
Nash equilibrium
Operators
optimal bidding strategy
Optimization methods
Power system simulation
Strategy
transmission constraints
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Summary:This work describes a method for analyzing the competition among transmission-constrained generating companies (GENCOs) with incomplete information. Each GENCO models its opponents' unknown information with specific types for transforming the incomplete game into a complete game with imperfect information. The proposed methodology employs the supply function equilibrium for modeling a GENCO's bidding strategy. The competition is modeled as a bilevel problem with the upper subproblem representing individual GENCOs and the lower subproblem representing the independent system operator (ISO). The upper subproblem maximizes the individual GENCOs' payoffs and the lower subproblem solves the ISO's market clearing problem for minimizing consumers' payments. The bilevel problem is solved by developing sensitivity functions for a GENCO's payoff with respect to its bidding strategies. An eight-bus system is employed to illustrate the proposed method, and the numerical results show the impact of transfer capability on GENCOs' bidding strategies.
ISSN:0885-8950
1558-0679