Multi-objective differential evolution for optimal power flow

This paper presents a multiobjective differential evolution (MODE) based approach to solve the optimal power flow (OPF) problem. OPF problem has been treated as a true multiobjective constrained optimization problem. Different objective functions and different operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. Also, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE-30 bus test system show the effectiveness of the proposed approach in solving true multi-objective OPF and also finding well distributed Pareto solutions.