Contingency constrained economic load dispatch using improved particle swarm optimization for security enhancement

Abstract

This paper presents a contingency constrained economic load dispatch (CCELD) using proposed improved particle swarm optimization (IPSO), conventional particle swarm optimization (PSO), evolutionary programming (EP) techniques such as classical EP (CEP), fast-EP (FEP) and mean of classical and fast EP (MFEP) to alleviate line overloading. Power system security enhancement deals with the task of taking remedial action against possible network overloads in the system following the occurrences of contingencies. Line overload can be removed by means of generation redispatching. In the proposed improved PSO, a new velocity strategy equation with scaling factor is proposed and the constriction factor approach (CFA) utilizes the eigen value analysis and controls the system behaviour. The CCELD problem is a twin objective function viz. minimization of fuel cost and minimization of severity index. This proposed IPSO-based CCELD approach generates higher quality solution in terms of optimal cost, minimum CPU time and minimum severity index than the other methods. Simulation results on IEEE-118 bus and IEEE-30 bus test systems are presented and compared with the results of other approaches.