A PSO-based Economic Optimal Strategy for PV-ESS Combination Power Systems

In recent years, the research for economic optimization in power systems is usually regarded as multi-constrained, nonlinear problems. The particle swarm optimization (PSO) algorithm has been widely applied to solving economic optimization issues due to its easy implementation, few algorithm parameters, fast convergence, and good optimization ability. Nevertheless, the traditional solutions for these optimization issues lack the consideration of algorithm performance, resulting in huge deviations between the actual and the optimal results. Therefore, an improved PSO-based economics optimal strategy for photovoltaic (PV) and energy storage system (ESS) combination power systems is proposed in this paper. Under the proposed scheme, the improved PSO algorithm's convergence and speed are given full discussions bound to the algorithm parameters, which help obtain optimal results and improve solution speed. The feasibility of the proposed strategy is verified by simulation in the standard IEEE 33 bus test system.