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Model of Output Power of Photovoltaic Station Based on Grey Theory and Neural Network

With the emergence of energy crisis and environmental pollution, the large scale photovoltaic power systems have been widely applied. However, the output power of photovoltaic power system has the property of uncertainties. Insolation is not constant and the output of photovoltaic (PV) system is influenced by weather conditions. In order to predict the power output for PV system as accurate as possible, it requires method of insolation estimation. In this paper, a technique consider the insolation of each month, and confirm the validity of using grey system theory and neural network to predict insolation by computer simulations. The method used in this paper only involved in the weather data instead of complicated calculation and mathematical model. The results show that the proposed prediction model not only efficiently and accurately predict the PV system output power, but the speed of prediction is also fast, which has potential value in engineering applications.