Optimal sizing of a Stand-alone photovoltaic system using statistical approach

The intermittent nature of renewable resources remain one of the major impediments to the evolution of electricity production from renewable energies. This paper presents a methodology to optimally size a photovoltaic (PV) stand-alone system with battery storage. Its originality resides in taking into account the stochastic nature of the solar radiation in the sizing process by using statistical techniques. The optimal design is based on the inverse conception, which gives the optimum number of photovoltaic panels and the optimum number of batteries. The inputs of the optimization process are only the radiation data and the load demand. The radiation data of the location were synthesized by the statistical technique from which the average hourly PV power of the day of each month was determined. A photovoltaic panel that most fits the site was chosen among a list of four panels with different characteristics to be afterward deployed for sizing. The loss of power supply probability (LPSP), related to the system reliability was used to evaluate the efficiency of the sizing methodology. The number of PV panel and batteries obtained from the system simulation during 24h presented an acceptable rate of load satisfaction.