Evolving fuzzy bidding strategies in competitive electricity markets

This paper suggests an evolutionary approach to generate bidding strategies for power auctions. Bidding strategies are represented by fuzzy rule-based systems due to its transparency and ability to naturally handle imprecision in input data, a key issue in bidding environments. Evolution of bidding strategies uncovers unknown and unexpected agent behaviors and allows a richer analysis of auction mechanisms and their role as a coordination protocol. Specific genetic operators have been developed in this paper. Simulation experiments show that the evolutionary, genetic-based design approach evolves strategies that enhance agents profitability when compared with the marginal cost-based approaches commonly adopted by agents in power markets.