PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR DYNAMIC ECONOMIC DISPATCH

Abstract

Economic Dispatch (ED) Problem is critical in power system operations as it gives the optimal schedule of the generators so that total operating cost of generation is minimum, while satisfying the generator constraints and the system constraints. The traditional ED doesn’t take into account the valve point loading on the cost curve, ramp up and ramp down capability of the thermal generating units. The above said issues can’t be over looked as they are a more realistic approach to the ED problem. The ED problem considering the Ramp limits and valve point effects is called Dynamic Economic Dispatch (DED). The present work aims to solve DED problem of a five generator system using Refined Genetic Algorithm (RGA) and Particle Swarm optimization (PSO) technique. The Solution obtained by PSO gives a better optimal solution compared to RGA, the results obtained are duly discussed.