An evolving ant direction hybrid differential evolution for optimal power flow with non-smooth cost functions

摘要

This paper presents an evolving ant direction hybrid differential evolution (EADHDE) algorithm for solving the optimal power flow problem with non-smooth and non-convex cost characteristics. In this algorithm, ant colony search is used by the EADHDE to find a suitable mutation operator for the hybrid differential evolution and the ant colony parameters are evolved using a genetic algorithm approach. The Newton-Raphson method solves the power flow problem. The feasibility of the proposed approach is tested on IEEE 30- and 57-bus systems, and the results obtained are compared with other methods. The proposed algorithm is capable of handling discrete control variables and gives similar results when compared with continuous case.