New bidding strategy formulation for day-ahead energy and reserve markets based on evolutionary programming

In this paper, a new bidding strategy for a day-ahead market is formulated. The proposed algorithm is developed from the viewpoint of a generation company wishing to maximize a profit as a participant in the deregulated power and reserve markets. Separate power and reserve markets are considered, both are operated by clearing price auction system. The optimal bidding parameters for both markets are determined by solving an optimization problem that takes unit commitment constraints such as generating limits and unit minimum up/down time constraints into account. This is a non-convex and non-differentiable which is difficult to solve by traditional optimization techniques. In this paper, evolutionary programming is used to solve the problem. The algorithm is applied to both single-sided and double-sided auctions, numerical simulations are carried out to demonstrate the performance of the proposed scheme compared with those obtained from a sequential quadratic programming.

[1]  L. Lai.  Power system restructuring and deregulation : trading, perfomance and information technology , 2001 .

[2]  Gerald B. Sheblé,et al.  A profit-based unit commitment GA for the competitive environment , 2000 .

[3]  G. Gross,et al.  Strategic bidding in electricity generation supply markets , 1999, IEEE Power Engineering Society. 1999 Winter Meeting (Cat. No.99CH36233).

[4]  W. Mielczarski,et al.  Bidding strategies in electricity markets , 1999, Proceedings of the 21st International Conference on Power Industry Computer Applications. Connecting Utilities. PICA 99. To the Millennium and Beyond (Cat. No.99CH36351).

[5]  P. Attaviriyanupap,et al.  A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function , 2002, IEEE Power Engineering Review.

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

[7]  Fushuan Wen,et al.  Coordination of bidding strategies in day-ahead energy and spinning reserve markets , 2002 .

[8]  Peter B. Luh,et al.  Optimization based bidding strategies in the deregulated market , 1999 .

[9]  Eiichi Tanaka,et al.  An Evolutionary Programming Solution to the Unit Commitment Problem , 1997 .

[10]  P. Luh,et al.  Optimal integrated generation bidding and scheduling with risk management under a deregulated daily power market , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

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

[12]  Kankar Bhattacharya.  Strategic bidding and generation scheduling in electricity spot-markets , 2000, DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382).

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

[14]  A. David.  Competitive bidding in electricity supply , 1993 .

[15]  David B. Fogel,et al.  An introduction to simulated evolutionary optimization , 1994, IEEE Trans. Neural Networks.

[16]  Fushuan Wen,et al.  Strategic bidding in reserve market , 2000 .

[17]  A. Papalexopoulos,et al.  Competitive procurement of ancillary services by an independent system operator , 1999 .

[18]  Jun Hasegawa,et al.  A new profit-based unit commitment considering power and reserve generating , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

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

[20]  G. Sheblé.  Computational Auction Mechanisms for Restructured Power Industry Operation , 1999 .

[21]  Shigeru Okuma,et al.  An Evolutionary Computation for Supplier Bidding Strategy in Electricity Auction Market , 2002 .

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

[23]  S. Hao.  A study of basic bidding strategy in clearing pricing auctions , 1999, Proceedings of the 21st International Conference on Power Industry Computer Applications. Connecting Utilities. PICA 99. To the Millennium and Beyond (Cat. No.99CH36351).