Economic Power Dispatch using Hybrid Particle Swarm Optimization with Simplex Search Method

Abstract

This paper presents the solution of economic power dispatch (EPD) in thermal power plants using the hybridization of particle swarm optimization (PSO) and simplex search method (SSM). EPD is obtaining the best generating schedule to supply the power demand and covering the transmission losses with minimum overall fuel cost. Physical constraints like valve point loading effects, ramp rate limits and prohibited operating zones are also included with basic EPD problem to increase the practicability in the problem. As PSO performs well in finding the global best solution and SSM in finding the local best solution, thus their combination improves the overall minimum results obtained for the generation fuel cost objective function. The performance of the proposed methodology is tested on different test systems having categories of small-scale, medium-scale and large-scale power system problems. The results obtained are then compared with other reported methods to show the superiority of the proposed algorithm.

Hybrid krill herd optimizer for thermal power scheduling problem

“…A new 𝛼-constrained simplex method has been implemented on a multi-objective hydrothermal considering wind and solar power scheduling [28]. A hybridized technique of PSO and the simplex search method has been used to solve economic power dispatch of thermal generating units considering valve point loading, ramp-rate and POZ [29]. A hybrid evolutionary algorithm which is a combination of shuffle frog technique and PSO has been implemented to economic emission power dispatch problem considering physical and operational constraints [30].…”