Optimization of hybrid PV/wind energy system using Meta Particle Swarm Optimization (MPSO)
When the stand alone energy system having photovoltaic panels only or wind turbine only are compared with the hybrid PV/wind energy systems, the hybrid systems are more economical and reliable. Hybrid system can be able to adapt the effects due to climate changes. This paper presents a Artificial Intelligent method to design the hybrid PV/wind system. While meeting the basic requirements of the stand-alone energy system, the objective function for cost of hybrid system is constructed, this includes initial costs, yearly operating costs and maintenance costs. The hybrid system consists of photovoltaic panels, wind turbines and storage batteries. Due to the complexity of hybrid energy system with nonlinear integral planning, Meta Particle Swarm Optimization is used to solve the problem. By use of MPSO operation strategy, the global optimal searching ability of the proposed algorithm is improved. The improved PSO can avoid the possibility of local minimum trap. The method mentioned in this article is proved to be effective using an example of hybrid energy system. Finally, the optimal solution is received using proposed MPSO method.