Non-dominated sorting differential evolution algorithm for multi-objective optimal integrated generation bidding and scheduling

According to the relationship of coordinated interaction between unit output and electricity price, an economic/risk/environmental generation optimal model for maximizing total profits in the dealing day and minimizing both risk and emissions was formulated in this paper. A new multi-objective differential evolution optimization algorithm, which integrated Pareto non-dominant sorting and differential evolution algorithm and improved individual crowding distance mechanism and mutation strategy to avoid premature and unevenly search, was designed to achieve Pareto optimal set of this model. Moreover, fuzzy set theory was employed to extract the best compromise non-dominated solution. The simulation analysis of an example demonstrated the superiority of the proposed algorithm such as integrality of Pareto front, well-distributed Pareto-optimal solutions, high search speed and so on. The proposed approach can effectively solve the multi-objective decision-making optimization problem of generation bidding.