Twenty-four Hours Ahead Solar Irradiance Forecast Based on Artificial Neural Network, ARIMA and SARIMA

Over the past years, the Brazilian electricity matrix has shown a tendency to increase the diversification with the insertion of renewable energy as solar and wind. However, the change in the electric power scenario leads to greater complexity in the planning and operation of the system due to its intermittency and the impossibility of storing both natural resources. In order to mitigate this problem, predictive systems have been sought to accurately forecast short-term irradiance and wind speed. The purpose of this paper was to predict irradiance 24 hours ahead from a method based on artificial intelligence, neural network and applying a data pre-processing stage which consisted of obtaining the stochastic components of the daytime data. In addition, statistical methods, such as integrated auto-regressive of moving average and integrated auto-regressive of seasonal moving average, were used in order to compare the results achieved, and the artificial neural network presented better results.