Sizing optimization of a stand-alone photovoltaic system using genetic algorithm

The Stand-Alone Photovoltaic (SAPV) system's power reliability and the corresponding Life Cycle Cost (LCC) present the main designing objectives. Therefore, a compromise solution between optimization criterions is crucial. This paper presents the sizing optimization of a stand-alone photovoltaic system with battery storage using Genetic Algorithm (GA). The main objective is computing the optimum configuration of the PV panels and storage batteries to supply a residential household. The purpose is to achieve an acceptable Loss of Power Supply Probability (LPSP), which is related to system's reliability, and the minimum LCC. The system's performance evaluation for different configurations of PV panels and batteries for a two-day simulation with an hourly step time was done. It was based on energetic modeling of the studied SAPV system. Sizing optimization insured consumers supply, a minimum LCC and an acceptable batteries State Of Charge (SOC).