In this Retaspimycin paper a mathematical model for cost analysis has been introduced for each system's components, and then the performance of different variants of particle swarm optimization algorithms on the sizing problem of PV/wind/battery systems has been evaluated. The optimal size of system components has been studied under various performance conditions using real-time information and meteorological data from each of Iran's southern, north–west, and north–east regions. These algorithms are particle swarm optimization (PSO), particle swarm optimization algorithm with adaptive inertia weight (PSO-W), particle swarm optimization based on repulsion factor (PSO-RF), particle swarm optimization algorithm with constriction factor (PSO-CF), and modified particle swarm optimization algorithm (MPSO). The results are also compared with the results obtained by simulated annealing (SA), tabu search (TS) and harmony search (HS) algorithms. The performance of the algorithms is periosteum compared in terms of accuracy and computational cost.