Application of GA and PSO in Optimal Design of a Hybrid PhotovoltaicFuel Cell Energy System

This paper introduces hybrid Photovoltaic-Fuel Cell generation system for a typical domestic load that is not located near the electric grid. In this configuration the combination of a battery، an electrolyser، and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. An energy based modeling has been developed using Matlab/Simulink to observe evolution of the system during a typical day، and the results are reported and discussed in the paper. Particle Swarm Optimization Algorithm and Genetic Algorithm are used to size the system components. This kind of optimization is a novel optimization procedure that uses system operation to size the system components in order to match the load of the site in the most cost effective way. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results show that a system composed with a photovoltaic generator، a fuel cell، an electrolyser and a battery can deliver energy in a stand-alone installation with an acceptable cost.