Effects of photovoltaic panel type on optimum sizing of an electrical energy storage system using a stochastic optimization approach

Abstract

This article proposes a stochastic optimization approach for an off-grid solar-wind with an electrical energy storage structure. The proposed optimization approach is a probabilistic algorithm based on simulated annealing for approximating the global optimum of the objective function. The optimal size of the electrical energy storage system for the solar-wind energy system as the final aim is calculated considering the reliability and annualized cost of the system. The objective function of this study is to reduce the unavailability and cost of the system with different types of solar panels (monocrystalline, polycrystalline, and thin film). The optimization process of the system size is accomplished using a stochastic optimization approach by considering the battery capacity, photovoltaic (PV) panel, and wind turbine area as decision variables. The harmony search algorithm is used to confirm the optimality of the system. The effects of photovoltaic panel type on the optimum sizing of electrical energy storage system are calculated in a case study over a year. So, a sensitivity study is performed to analyze the effect of the initial costs of components and the efficiency of photovoltaic panels on the annualized cost of the system. The results show that polycrystalline-PV solar/battery systems are more suitable for the proposed location than other systems, due to economic, technical, and environmental conditions. Also, the stochastic optimization approach is effective for the sizing process and can achieve the goals of the system. In three solar cell types, there is a slight increase (about 3.6 %) in TCOS (total cost of the system) value by increasing PV panel unit cost; and, there is a significant decrease in TCOS value (about 82 %) by decreasing battery unit cost; also, there is a significant decrease in TCOS value (about 28 %) by increasing PV efficiency.