A novel MPPT method based on large variance GA-RBF-BP

Abstract

The photoelectric conversion efficiency of photovoltaic cells is mainly affected by two factors, two factors are the operating temperature of the photovoltaic cell and the irradiance of the sun. In order to improve the photoelectric conversion efficiency of photovoltaic cells, combining with the two factors that affect photoelectric conversion efficiency of photovoltaic cells and the merits and demerits of BP neural network and RBF neural network, a scheme of maximum power point tracking based on large variation GA-RBF-BP is proposed. In this paper, the algorithm of input about RBF-BP neural network is the temperature and irradiance, the output is the voltage of maximum power point. This paper simulates the system through Matlab, the simulation results show that the system has excellent performance. This photovoltaic system can track the maximum power point quickly and accurately, which can greatly improve the photoelectric conversion efficiency of photovoltaic cells.