Bidding strategies for electricity producers in a competitive electricity marketplace

This paper presents a methodology for the development of bidding strategies for electricity producers in a competitive electricity marketplace. Initially, the problem is modeled as a two level optimization problem where, at the first level, a market participant tries to maximize his expected profit under the constraint that, at the second level, an independent system operator dispatches power solving an optimal power flow problem that minimizes total system cost. It is assumed that each supplier bids a linear supply function and chooses his bidding strategy based on probabilistic estimates of demand and rival behavior. Monte Carlo simulation is used to calculate the expected profit and Genetic Algorithms are employed to find the optimal strategy. Subsequently, the formulation is expanded to account for different market participants' risk profiles. It is shown that risk aversion may influence the optimal bidding strategy of an individual.

[1]  Howard Raiffa,et al.  Games And Decisions , 1958 .

[2]  M. Blume,et al.  The Demand for Risky Assets , 1975 .

[3]  T. Copeland,et al.  Financial Theory and Corporate Policy. , 1980 .

[4]  J. Hammersley.  SIMULATION AND THE MONTE CARLO METHOD , 1982 .

[5]  J. Ingersoll.  Theory of Financial Decision Making , 1987 .

[6]  J. W. Lamont,et al.  Strategic bidding in an energy brokerage , 1997 .

[7]  S. M. Shahidehpour,et al.  Application of games with incomplete information for pricing electricity in deregulated power pools , 1998 .

[8]  G. Sheblé,et al.  Genetic algorithm evolution of utility bidding strategies for the competitive marketplace , 1998 .

[9]  Chen-Ching Liu,et al.  Analysis of electricity market rules and their effects on strategic behavior in a noncongestive grid , 1998 .

[10]  Daniel Ashlock,et al.  Comprehensive bidding strategies with genetic programming/finite state automata , 1999 .

[11]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[12]  P. Luh,et al.  Optimization based bidding strategies in the deregulated market , 1999, Proceedings of the 21st International Conference on Power Industry Computer Applications. Connecting Utilities. PICA 99. To the Millennium and Beyond (Cat. No.99CH36351).

[13]  T. Overbye,et al.  A two-level optimization problem for analysis of market bidding strategies , 1999, 1999 IEEE Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.99CH36364).

[14]  A. J. Svoboda,et al.  Revenue adequate bidding strategies in competitive electricity markets , 1999 .

[15]  J. Weber.  Individual Welfare Maximization in Electricity Markets Including Consumer and Full Transmission System Modeling , 1999 .

[16]  T. Dillon,et al.  Electricity price short-term forecasting using artificial neural networks , 1999 .

[17]  Haili Song,et al.  Optimal electricity supply bidding by Markov decision process , 2000 .

[18]  Fushuan Wen,et al.  Coordination of bidding strategies in energy and spinning reserve markets for competitive suppliers using a genetic algorithm , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

[19]  Fushuan Wen,et al.  Optimal bidding strategies for competitive generators and large consumers , 2001 .

[20]  Fushuan Wen,et al.  Oligopoly electricity market production under incomplete information , 2001 .

[21]  M. Joung,et al.  A Continuous Strategy Game for Power Transactions Analysis in Competitive Electricity Markets , 2001, IEEE Power Engineering Review.

[22]  A. David,et al.  Optimal bidding strategies and modeling of imperfect information among competitive generators , 2001 .

[23]  Ali Keyhani,et al.  Stochastic price modeling of electricity in deregulated energy markets , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[24]  Y. Ho,et al.  An Ordinal Optimization-Based Bidding Strategy for Electric Power Suppliers in the Daily Energy Market , 2001, IEEE Power Engineering Review.

[25]  Mohammad Shahidehpour,et al.  Market operations in electric power systems , 2002 .

[26]  Haili Song,et al.  Nash Equilibrium Bidding Strategies in a Bilateral Electricity Market , 2002, IEEE Power Engineering Review.

[27]  J. Contreras,et al.  Forecasting Next-Day Electricity Prices by Time Series Models , 2002, IEEE Power Engineering Review.

[28]  Vassilios Petridis,et al.  Optimal power flow by enhanced genetic algorithm , 2002 .

[29]  Zuyi Li,et al.  Market Operations in Electric Power Systems : Forecasting, Scheduling, and Risk Management , 2002 .

[30]  A. Conejo,et al.  Optimal Response of a Power Generator to Energy, AGC, and Reserve Pool-Based Markets , 2002, IEEE Power Engineering Review.