Co-evolutionary bidding strategies for buyers in electricity power markets

The deregulation of the electrical power industries has opened many opportunities to power buyers, once price takers of a monopolistic economy, to look forward to a free market economy with market forces determining the market clearing prices and quantities. However, the strong influence of technical and physical constraints of the network may result in economic decisions that adversely affect the interests of the consumers. Compared to the monopolistic economy of yesteryears, power buyers may actually be able to influence the market by cooperating with other power buyers in the network. This paper presents a co-evolutionary algorithm for evolving individual and cooperative strategies of electricity buyers in a power market. The algorithm focuses on how the buyers choose their bidding strategies through learning to maximize the profits in different scenarios of playing individually or cooperatively. The results show that it is of great benefit to cooperate but the free rider problem may arise when an individual buyer gains more profit due to the cooperative effort of the others.