Hybrid coevolutionary programming for Nash equilibrium search in electricity markets

In this paper, a hybrid coevolutionary programming method is used for revenue maximization of six generating firms (in a modified IEEE 30-bus power system) who compete to serve the system demand. The system is a typical model of a market with numerous supply and demand agents. This single sided electricity market can be modeled as a game in which each supplier is a player. Each player searches for an optimal bidding strategy in this competitive market. In this paper, piece-wise affine supply functions with three parts are considered for each supplier, and the Nash equilibrium solution for price values (bidding strategies) is found by hybrid coevolutionary programming. In each generation, all players improve their strategies by interacting with the survived individuals of other players. During this interaction (coevolutionary phase) the strategy of each player is improved.