Incremental cost based combined economic and emission dispatch using hybrid differential evolution

Abstract

Economic load dispatch (ELD) is one of the most important problems to be solved in the operation and planning of a power system. Nowadays due to increased environmental awareness, generating utilities should optimize their emission in addition to the fuel cost. Recently researchers are developing different soft computing techniques to solve the combined economic and emission dispatch (CEED) problem. In this paper, Hybrid differential evolution Algorithm (HDEA) is developed to solve CEED problem considering security constraints as the traditional Differential evolution (DE) is suffers from local optima or stagnation problem. To evaluate the accuracy, convergence speed and applicability of the proposed method, it is implemented on the standard IEEE-30 bus system having six generating units to solve CEED problem and the results of CEED problem are compared with traditional PSO and DE. The tested results indicate that the proposed method is more efficient than the others in terms of fuel costs, emission, total losses and computational times.