Competitive co-evolutionary approach to stochastic modeling in deregulated electricity market

the main purpose of the paper is to calculate supplier's optimal biding in a deregulated electricity market, by calculating the Nash equilibrium strategies. In this paper we present the use of competitive coevolutionary algorithm in order to find the optimal biding strategies. A computational Algorithm has been developed to find Nash equilibrium strategies where a stochastic programming model is proposed to maximize the expected profits taking into account the stochastic aspect of spot market parameters. The key feature of our approach is the combination of a powerful learning algorithm to find the optimal strategies, and a scenario formulation to model the market uncertainties through. Each market agents is modeled as an adaptive evolutionary agent learning from market interactions and take part in the forward and spot transactions to act strategically to maximize their profits.