Reserve-constrained multiarea environmental/economic dispatch based on particle swarm optimization with local search
The objective of economic dispatch (ED) is to minimize the total operational cost while satisfying the operational constraints of power systems. Multiarea economic dispatch (MAED) deals with the optimal power dispatch of multiple areas. In this investigation, multiarea environmental/economic dispatch (MAEED) is proposed to address the environmental issue during the ED. Its target is to dispatch the power among different areas by simultaneously minimizing the operational costs and pollutant emissions. In this paper, the MAEED problem is first formulated and then an improved multiobjective particle swarm optimization (MOPSO) algorithm is developed to derive a set of Pareto-optimal solutions. In the proposed version of MOPSO, local search is used to increase its search efficiency. To ensure the system security, tie-line transfer limits between different areas are incorporated as a set of constraints in the optimization process. Moreover, the reserve-sharing scheme is applied to ensure that each area is able to fulfill its reserve requirement. Numerical studies based on a four-area test power generation system are carried out to demonstrate the validity of the proposed optimization method as well as the results from different problem formulations. Comparative results with respect to other optimization methods are also presented.
environmental/economic dispatch particle swarm optimization multiarea power dispatch reserve sharing stochastic search and optimization