Multi objective design of stand-alone PV/wind energy system by using hybrid GA and PSO

In recent years, hybrid renewable energy systems have been considered much more for stand-alone applications. In this paper, a new method has been introduced to obtain optimal size of hybrid energy system, including wind turbine (WT), photovoltaic (PV) panels and storage battery (SB). Optimization has considered two objective functions; total net present worth (TNPW) as cost function and energy index of reliability (EIR) as technical criteria. Because of complexity of problem and possibility of local minimum, a hybrid genetic algorithm (GA) and particle swarm optimization (PSO) is employed. First of all, by using GA, the possibility of local minimum reduces and after specified iterations, PSO is used to improve optimization's speed and local tuning ability.