Combining msg cloud estimates and the wrf nwp model dynamic to enhance short-term solar radiation forecasting

Abstract

The development of accurate solar radiation forecasting methodologies is necessary for the management of the solar power plants and their integration in the power grid. The accuracy of the cloudiness representation and forecasting determines the accuracy of the solar radiation forecasting. Satellite-based methods are the reference approach for solar prediction in the forecasting horizons ranging from a few minutes up to about 6 hours (short-term forecasting). Satellite imagery gives an accurate view of the spatial distribution of clouds over wide regions. Numerical Weather Prediction (NWP) models have the unique ability to accurately represent the atmosphere dynamics by physics methods. However, their cloud representation, as here demonstrated, is still far from optimal. In this thesis, a method which improves short-term solar radiation forecasting by combining the accurate observations of the actual cloud field from satellite imagery and the accurate representation of atmospheric dynamics in NWP models, is presented and evaluated.