Optimizing Power Resilience Performance of Intelligent Solar Photovoltaic System for Smart Energy Management Considering Reliability and Cost

Due to being nonpolluting and renewable, intelligent solar photovoltaic (PV) technology is widely used to provide electricity and becomes a cornerstone to sustainable energy and smart energy management. Different from existing studies that improve the PV efficiency by changing cell materials, this article proposes a novel system reliability and cost model of enhancing the PV power resilience performance from the perspective of optimizing the number of PV panels. Specifically, a multiobjective planning model is proposed, which determines the optimum number of spare parts for PV panels maximizing the output power resilience while maximizing the system reliability and minimizing the cost. The reliability measures the probability of stable operation of a PV panel considering the no-power output state. The cost factor encompasses negative cost of environmental benefits, resource cost, operation and maintenance cost, and penalty cost. Experiments are performed on fifty sets of Pareto optimal solutions in summer and winter cases to illustrate effectiveness of the proposed method by using a ground-mounted PV project in Zhongwei City, China.