Evolving cooperative behavior in a power market

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.
• 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.
• 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.

INDEX TERMS

General Terms:
Economics, Human Factors

Keywords:
cooperative behavior, evolutionary algorithm, power market