A CONSTRICTION FACTOR BASED PARTICLE SWARM OPTIMIZATION FOR ECONOMIC DISPATCH

摘要

This paper presents an efficient method for solving the non-smooth economic dispatch (ED) problem with valve-point effects, by introducing a constriction factor into the original particle swarm optimization (PSO) algorithm. The proposed constriction factor based particle swarm optimization (CFBPSO) combines the original PSO algorithm with a constriction factor. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. To verify the feasibility and performance, the proposed method is applied to a test non-smooth ED problem with valve-point effects. The results of the CFBPSO are compared with the results of other methods; the genetic algorithm (GA); the evolutionary programming (EP); the modified PSO; and in particular the improved PSO (IPSO).