Evolving cooperative behavior in a power market

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 14bus transmission network are conducted and power buyer strategies are observed and analyzed. Categories and Subject Descriptors Learning Classifier Systems and Other Genetics-Based Machine Learning General Terms Economics, Human Factors. Keywords Cooperative behavior, power market, evolutionary algorithm.

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Dipti Srinivasan, Dakun Woo, Lily Rachmawati, Kong Wei Lye
• Keywords: Cooperative Strategies, Evolutionary Algorithm, GECCO 2006, Optimization, Power Buyer