Economic load dispatch using improved particle swarm optimization algorithms

Abstract

The main objective of Economic Load Dispatch (ELD) problem is to schedule the connected generating units of plant outputs so as to fulfill load demands at minimum operating cost while satisfying all operational constraints. Recently particle swarm optimization algorithms inspired by collective behavior of swarm has been applied successfully to solve ELD problem. It is a population based stochastic optimization process driven by the simulation of a social psychological metaphor. In this paper three improved PSO algorithms- IPSO-A, IPSO-B and IPSO-C have been developed and implemented to solve ELD for IEEE 5, 14 and 30 bus systems. Conventional PSO (CPSO) using inertia weight and constriction factor individually as well as simultaneously have been also implemented to solve ELD problem. PSO algorithms have been compared for twenty trial runs. The best, worst, average fitness and their standard deviation for all the algorithms have been determined. The results show that proposed improved PSO techniques gives the optimum operating cost with consistent results in terms of diversity of results.