Forecast Solar Energy Using Artificial Neural Networks

Abstract

Energy harvested from the natural resources such as solar energy is highly intermittent. However, its future values can be predicted with reasonable accuracy. In this paper, a solar energy forecasting model based on Artificial Neural Network is proposed. Intensity of solar radiations is predicted 24 h ahead based on pressure, dew point, temperature, relative humidity, wind speed, zenith angle and historical values of solar intensity. The dataset of 4 months is used from National Solar Radiation Database. Simulations were performed to analyse the impact of each input variable on results. Results indicate the efficiency of the model both in terms of accuracy and computational costs.