Power Generation Forecasting of Solar Photovoltaic System Using Radial Basis Function Neural Network

Abstract

An accurate forecasting method for power generation of the solar photovoltaic (PV) system can help the power systems operator to reduce the risk of unreliability of electricity supply. This paper proposed a radial basis function (RBF) neural network method to forecast the power generation of PV system. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of power generation of a PV system. The good agreements between the realistic values and forecasting values are obtained; the numerical results show that the proposed forecasting method is accurate and reliable.