Stochastic Optimal Power Flow Based Improved Differential Evolution

This paper presents a improved differential evolution approach to solve the stochastic optimal power flow (OPF) problem. The stochastic OPF problem minimizes the total the expected cost of a base-case operating state considering the stochastic load and generator. The improved Optimal settings of stochastic OPF control variables produced by Monte Carlo method are designed by this improved differential evolution (DE) algorithm. The proposed methods are illustrated on the the standard IEEE 30-bus system and the result shows that its effectiveness and robustness.