Ant Colony Optimization Applied on Combinatorial Problem for Optimal Power Flow Solution

This paper presents an efficient and reliable evolutionary-based approach to solve the optimal power flow (OPF) combinatorial problem. The proposed approach employs Ant Colony Optimization (ACO) algorithm for optimal settings of OPF combinatorial problem control variables. Incorporation of ACO as a derivative-free optimization technique in solving OPF problem significantly relieves the assumptions imposed on the optimized objective functions. The proposed approach has been examined and tested on the standard IEEE 57-bus test System with different objectives that reflect fuel cost minimization, voltage profile improvement, and voltage stability enhancement. The proposed approach results have been compared to those that reported in the literature recently. The results are promising and show the effectiveness and robustness of the proposed approach.