Photovoltaic Power Prediction Considering the Influence of Smog on Solar Radiation

Abstract

As smog significantly weakens the intensity of solar radiation, the impact of smog on photovoltaic power generation cannot be ignored. This article aims to improve the prediction accuracy of photovoltaic power generation under smog weather. The impact of main atmospheric meteorological factors on atmospheric aerosols under smog weather is studied, and radial basis function neural network is adopted to predict the optical thickness of atmospheric aerosols; then, the inclined plane radiation model is established to predict the radiation intensity received by the photovoltaic panel; finally, considering fully the factors affecting the photovoltaic power generation under the smog weather, the RBF neural network is used to predict the photovoltaic power. Experimental verification proved that the presented photovoltaic power prediction model has high accuracy.