Hybrid differential evolution particle swarm optimization (DE-PSO) algorithm for optimization of unified power flow controller parameters

Abstract

This work proposes hybrid DE-PSO algorithm to tune the parameters of UPFC based lead-lag controller. Both DE and PSO are two powerful meta-heuristic optimization techniques with different special features. These specialities are combined together in hybrid DE-PSO algorithm. The parameters of UPFC based lead-lag controller are optimized by this hybrid DE-PSO algorithm by taking integral time absolute error (ITAE) as the fitness function. A single machine infinite bus power system is considered by applying a small perturbance in prime mover input power and the effect of DE-PSO optimized controller is compared with PSO and DE optimized controllers. The convergence rate, settling time, over and under shoots are compared for all algorithms. Also the eigen values and damping modes of oscillations are observed with all the three optimization techniques and it has been observed that hybrid DE-PSO algorithm is much efficient in damping electromechanical oscillations and thereby enhancing small signal stability as compared to PSO and DE algorithms.