Environmental/economic power dispatch using multiobjective evolutionary algorithms: A comparative study

Abstract

A comparative study of newly developed Pareto-based Multi-Objective Evolutionary 
Algorithms (MOEA) applied to a nonlinear power system multiobjective optimization 
problem is presented in this paper. Specifically, Niched. Pareto Genetic Algorithm 
(NPGA), Nondominated Sorting Genetic Algorithm (NSGA), and Strength Pareto 
Evolutionary Algorithm (SPEA) have been developed and successfully applied to 
Environmental/Economic electric power Dispatch (EED) problem. These multiobjective 
evolutionary algorithms have been individually examined and applied to the standard 
IEEE 30-bus test system. A feasibility check procedure has been developed and 
superimposed on MOEA to restrict the search to the feasible region of the problem 
space. The results of MOEA have been compared to those reported in the literature. 
The comparison shows the superiority of MOEA to the traditional multiobjective 
optimization techniques and confirms their potential to handle power system 
multiobjective optimization problems.