Multiobjective optimal power flow using strength Pareto evolutionary algorithm

Abstract

In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. The OPF problem is formulated as a nonlinear constrained multiobjective optimization problem where the fuel cost and the voltage stability index are to be minimized simultaneously. A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. A hierarchical clustering algorithm is imposed to provide the decision maker with a representative and manageable Pareto-optimal set. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal nondominated solutions in one single run. The results also show the superiority of the proposed approach and confirm its potential to solve the multiobjective OPF problem.