Design of Simulation Model and Research on Output Characteristics of Solar Cells Based on Deep Learning

With the increasingly prominent problems of energy and environment, solar energy is a new energy form with the greatest development potential in the world. As a new type of green renewable energy, solar energy is an ideal renewable energy because of its high utilization rate compared with other new energy sources. Solar photovoltaic power generation is a direct form of power generation that uses photovoltaic panels to convert the radiant energy of sunlight into electrical energy. In the actual situation, the light intensity is unstable, and the solar photovoltaic cells (SPVC) are easily affected by external temperature and other factors, so it is necessary to model the characteristics of photovoltaic array and realize the dynamic simulation of photovoltaic power generation system. This paper introduces the principle of solar photovoltaic cells, designs the simulation model of solar cells based on deep learning, and analyzes the output characteristics of solar cells. Increasing solar radiation, decreasing battery temperature, series resistance and diode reverse saturation current can all improve the output performance of photovoltaic cells, and increasing open circuit voltage and short circuit current is helpful to improve its output power and efficiency.