Multi-Objective Differential Evolution for Optimal Power Flow

Abstract

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.