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

机译:基于深度学习的太阳能电池输出特性仿真模型设计与研究

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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.
机译:随着越来越突出的能源和环境问题,太阳能是一种新的能源形式,世界上最大的发展潜力。作为一种新型的绿色可再生能源,太阳能是一种理想的可再生能源,因为其利用率高,与其他新能源相比。太阳能光伏发电是一种直接形式的发电,使用光伏面板将阳光的辐射能量转换为电能。在实际情况下,光强度不稳定,太阳能光伏电池(SPVC)容易受到外部温度和其他因素的影响,因此需要模拟光伏阵列的特性并实现光伏发电系统的动态仿真。本文介绍了太阳能光伏电池的原理,基于深度学习设计了太阳能电池的仿真模型,并分析了太阳能电池的输出特性。越来越多的太阳辐射,降低电池温度,串联电阻和二极管反向饱和电流都可以提高光伏电池的输出性能,增加开路电压和短路电流有助于提高其输出功率和效率。

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