Solving Optimal Power Flow Problem Using Improved Differential Evolution Algorithm

Abstract

The purpose of this article is to present a new improvement of the differential evolution algorithm for solving the Optimal Power Flow (OPF) problem with multiple and competing objective functions. The objective functions are fuel cost minimization of generating units, minimization of emission, reduction of real power losses in the transmission lines, voltage profile improvement, and voltage stability enhancement. These improvements include the random selection mechanism for a crossover, the trial operation modification, and finely introducing the mutation process calculations into the selection stage. To demonstrate the effectiveness of the proposed technique, the Improved Differential Evolution (IDE) has been performed on the IEEE 30-bus standard system. The optimization results reveal that the proposed approach has a high convergence speed with good variety. Lastly, the numerical results of the proposed approach are compared with other recent optimization methods. These comparisons demonstrate the effectiveness of the IDE technique for solving different OPF problems.