Multiobjective Economic Load Dispatch Using Particle Swarm Optimization

Abstract

A major objective for the Thermal power generation is to minimize fuel consumption by allocating optimal power generation to each unit (Economic Dispatch) and to maintain emissions within the environmental license limit (Emission Dispatch) subject to equality and inequality constraints. Due to conflicting nature of emission and economy objectives, problem becomes multiobjective in nature. In this research work weighting method is applied to convert multiobjective optimization problem in to scalar optimization. The weighting method assigns different weights to each objective function based on its importance. The Particle Swarm Optimization (PSO) technique is applied to find the best comprised solution. The thermal unit is selected as decision variable and it is searched within defined search area. The equality constraint is handled by exterior penalty method. Fuzzy cardinal approach is used to achieve the one best solution. In order to show the effectiveness of this technique, the proposed approach is applied to three test systems. Numerical results obtained from this approach are compared with different techniques (differential evolution(DE), classical evolutionary programming(CEP), fast evolutionary programming(FEP), mean(FEP) and improved (FEP),multi objective differential evolution (MODE) , pareto differential evolution (PDE), non dominated sorting genetic algorithm-II (NSGA-II) and strength pareto evolutionary algorithm 2 (SPEA 2) and are found satisfactory.