Modeling daily profiles of solar global radiation using statistical and data mining techniques

Abstract

Solar radiation forecasting is important for multiple fields, including solar energy power plants connected to grid. To address the need for solar radiation hourly forecasts this paper proposes the use of statistical and data mining techniques that allow different solar radiation hourly profiles for different days to be found and established. A new method is proposed for forecasting solar radiation hourly profiles using daily clearness index. The proposed method was checked using data recorded in Malaga. The obtained results show that it is possible to forecast hourly solar global radiation for a day with an energy error around 10% which means a significant improvement on previously reported errors.