Application of differential evolution algorithm in purchase cost optimization

TLDR: The simulation results show that differential evolution was successfully validated for eight distributed generators, which has significant advantages both in global convergence speed and convergence precision compared with improved GA.

Abstract: Under the deregulation of generation market, all distributed generators will participate in electric power bidding; therefore purchase cost problem has been getting more attention of power companies. However, under the competition principle, they can purchase energy from several of power generation companies, so there exist continuous and integral variables in purchase cost model. It is difficult to solve the problem using traditional optimization method. The differential evolution algorithm has been successfully applied to a wide range of applications, mainly in solving continuous nonlinear optimization problems. Therefore, this paper provides a new method based on differential evolution algorithm for purchase cost optimization, and has been successfully applied to solving the problem. The simulation results show that differential evolution was successfully validated for eight distributed generators, which has significant advantages both in global convergence speed and convergence precision compared with improved GA.