Multiobjective optimal power flow using Improved Strength Pareto Evolutionary Algorithm (SPEA2)

Abstract

In this paper Improved Strength Pareto Evolutionary Algorithm (SPEA2) is presented and developed for Multiobjective Optimal Power Flow (OPF) problem. The generation OPF optimization problem is formulated as a nonlinear constrained multiobjective problem where the generation real power and the system voltage stability are optimized concurrently. Truncation algorithms are used to manage the Pareto-Optimal set size. The best compromise solution is extracted using fuzzy set theory. The SPEA2 performance results were compared to Strength Pareto Evolutionary Algorithm (SPEA) performance results. The results exhibit the capabilities of the proposed approach in produce well-distributed Pareto-optimal solutions for the subject multiobjective OPF optimization problem.