Optimal sizing and energy management of a stand-alone photovoltaic/pumped storage hydropower/battery hybrid system using Genetic Algorithm for reducing cost and increasing reliability

In this paper, a genetic algorithm is applied to optimize the sizing of an autonomous renewable energy multi-source system for reliable and economical supply of energy. The multi-source system is composed of a photovoltaic generator, a pumped storage hydropower system and a battery. The system will power public lighting and operate a garden fountain in the Botanical Garden, located in the Alexandre Aibéo Park in Covilhã (Portugal). Solar irradiance is initially simulated for a reference photovoltaic capacity (25 kWp) over one year by the PVsyst software for the city of Covilhã. Two objective functions are used for sizing optimization: the loss of power supply probability (LPSP) and the levelized cost of energy (LCE). The LCE takes into account the capital cost, the replacement cost and the cost of operation and maintenance. The genetic algorithm is used to determine the best configuration of the different subsystems (photovoltaic generator capacity, upper water reservoir capacity and battery capacity). The originality of this work lies in the combination of two storage elements with different dynamics, the introduction of an adapted energy management strategy (EMS) allowing to manage energy flows between the different subsystems and to control the process of charging/ discharging storage elements, and multi-objective optimization (considering technical and economic criteria) of the sizing of the autonomous photovoltaic/pumped storage hydropower/ battery hybrid system using genetic algorithm.