Short-term cloudiness forecasting for solar energy purposes in Greece, based on satellite-derived information

A novel method for the short-term (15–240 min) forecasting of cloudiness in Greece is presented by taking into account that this is the main atmospheric factor responsible for the spatial and temporal distribution of surface solar irradiance. Images from the Spinning Enhanced Visible and Infrared Imager onboard the Meteosat Second Generation satellite, for a 3-year time period and with high spatial and temporal resolution (0.05°, 15 min), were processed to retrieve the cloud clearness index (CCI) and used for the training and testing of an artificial neural network (ANN). The estimated and the measured values of CCI are in good agreement and emphasis is given to the spatial distribution of the seasonal errors. The ANN was trained according to pre-classified areas that present similar cloud characteristics and could provide estimations of surface solar irradiance in synergy with models that calculate surface irradiance under clear skies.