INFLUENCE OF GLOBAL SOLAR RADIATION TYPICAL DAYS ON FORECASTING MODELS ERROR

In this work, we have led an analysis of different global solar radiation forecasting models errors according to the global solar radiation variability. Different predictions models were performed such as machine learning techniques (Neural Networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this study a simple linear autoregressive (AR) model as well as two naïve models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and tested with data from three Frenc