Article

Evolving cooperative behavior in a power market

Authors:

Dipti Srinivasan,

Dakun Woo,

Lily Rachmawati,

Kong Wei LyeAuthors Info & Claims

GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation

Pages 1599 - 1600

https://doi.org/10.1145/1143997.1144260

Published: 08 July 2006 Publication History

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Abstract

This paper presents an evolutionary algorithm to develop cooperative strategies for power buyers in a deregulated electrical power market. Cooperative strategies are evolved through the collaboration of the buyer with other buyers defined by the different group memberships. The paper explores how buyers can lower their costs by using the algorithm that evolves their group sizes and memberships. The algorithm interfaces with PowerWorld Simulator to include in the technical aspect of a power system network, particularly the effects of the network constraints on the power flow. Simulation tests on an IEEE 14-bus transmission network are conducted and power buyer strategies are observed and analyzed.

References

[1]

J. M. Zolezzi, and H. Rudnick, "Transmission Cost Allocation by Cooperative Games and Coalition Formation," IEEE Trans. Power Systems, vol. 17, no. 4, pp. 1008--1005, November 2002.

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[2]

M. Shahidehpour, H. Yamin, and Z. Li, Market operations in electric power systems: forecasting, scheduling, and risk management. New York: IEEE, Wiley-Interscience, 2002, ch. 10.

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[3]

M. Srinivas, and L. M. Patnaik, "Adaptive Probabilities of Crossover Mutation in Genetic Algorithm," IEEE Trans. Systems, Man and Cybernetics, vol. 24, no. 4, pp. 656--667, April 1994.

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Brodsky ALevy R(2022)A Three-Stage Cooperative Market Mechanism for Resilient Power SystemsSN Computer Science10.1007/s42979-022-01126-93:3Online publication date: 26-Apr-2022
https://dl.acm.org/doi/10.1007/s42979-022-01126-9
Argotte LMejia-Lavalle MSosa R(2009)Business Intelligence and Energy Markets: A Survey2009 15th International Conference on Intelligent System Applications to Power Systems10.1109/ISAP.2009.5352918(1-6)Online publication date: Nov-2009
https://doi.org/10.1109/ISAP.2009.5352918
Mejía-Lavalle MSosa R. RGonzález M. NArgotte R. L(2009)Survey of Business Intelligence for Energy MarketsProceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems10.1007/978-3-642-02319-4_28(235-243)Online publication date: 22-Jun-2009
https://dl.acm.org/doi/10.1007/978-3-642-02319-4_28

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Published In

GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation

July 2006

2004 pages

ISBN:1595931864

DOI:10.1145/1143997

General Chair:
Mike Cattolico
Tiger Mountain Scientific, Inc., USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 08 July 2006

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GECCO06: Genetic and Evolutionary Computation Conference

July 8 - 12, 2006

Washington, Seattle, USA

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GECCO '06 Paper Acceptance Rate 205 of 446 submissions, 46%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Brodsky ALevy R(2022)A Three-Stage Cooperative Market Mechanism for Resilient Power SystemsSN Computer Science10.1007/s42979-022-01126-93:3Online publication date: 26-Apr-2022
https://dl.acm.org/doi/10.1007/s42979-022-01126-9
Argotte LMejia-Lavalle MSosa R(2009)Business Intelligence and Energy Markets: A Survey2009 15th International Conference on Intelligent System Applications to Power Systems10.1109/ISAP.2009.5352918(1-6)Online publication date: Nov-2009
https://doi.org/10.1109/ISAP.2009.5352918
Mejía-Lavalle MSosa R. RGonzález M. NArgotte R. L(2009)Survey of Business Intelligence for Energy MarketsProceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems10.1007/978-3-642-02319-4_28(235-243)Online publication date: 22-Jun-2009
https://dl.acm.org/doi/10.1007/978-3-642-02319-4_28

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Dynamic bidding analysis in power market based on the supply function

Evolving cooperative bidding strategies in a power market

Formation mechanism of on-grid power tariff using game model of complete information

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Dynamic bidding analysis in power market based on the supply function

Evolving cooperative bidding strategies in a power market

Formation mechanism of on-grid power tariff using game model of complete information

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