Enhanced adaptive particle swarm optimisation algorithm for dynamic economic dispatch of units considering valve-point effects and ramp rates

Abstract

In power systems, dynamic economic dispatch (DED) is one of the most significant non-linear problems showing non-convex characteristic because of the valve-point effects. In this study, an enhanced adaptive particle swarm optimisation (EAPSO) algorithm is proposed to solve the DED problem where the valve-point effects, ramp-rate limits and transmission power losses are taken into account. In the proposed optimisation algorithm, a mutation technique is devised to prevent premature phenomena and lead the swarm search space much more effectively; also a novel non-linear approach is designed to adjust the inertia weight factor dynamically according to the optimisation process performance. Social and cognitive factors are self-adaptively tuned, so the swarm can search the space smartly for global optimum solution. The efficiency of the proposed method is validated on three popular test systems in the area including 5, 10 and 30 thermal units. The results are compared with most of the other works in the area. The superiority of the method is shown over earlier methods.