Scrutiny of multifarious particle swarm optimization for finding the optimal size of a PV/wind/battery hybrid system

In this paper, a network-independent pattern has been used to design a hybrid (PV/wind/Batt) system with high reliability and minimum production total costs over the life of the system. In such systems, optimum sizing is the main issue for having a cost-effective system. In this regard, studies the performance of different PSO (particle swarm optimization algorithm) variants to determine the optimum sizing of hybrid (PV/wind/Batt) system, namely, PSO, modified PSO (MPSO), PSO based on repulsion factor (PSO-RF), PSO with constriction factor (PSO-CF), and PSO with adaptive inertia weight (PSO-W). The system's components optimal size has been studied under various performance conditions using real-time information and meteorological data of one of three atypical regions located in Iran. Simulation results indicate that PSO-CF produces more promising results than the other variants, tabu search (TS), simulated annealing (SA) and harmony search (HS) algorithms in terms of mean (Mean), standard deviation (Std.), worst (Worst) and best (Best) the total annual cost (TAC).