Improvement of Solar and Wind forecasting in southern Italy through a multi-model approach: preliminary results

Abstract

The improvement of the Solar and Wind short-term forecasting represents a critical goal for the weather prediction community and is of great importance for a better estimation of power production from solar and wind farms. In this work we analyze the performance of two deterministic models operational at ISAC-CNR for the prediction of short-wave irradiance and wind speed, at two experimental sites in southern Italy. A post-processing technique, i.e the multi-model, is adopted to improve the performance of the two mesoscale models. The results show that the multi-model approach produces a significant error reduction with respect to the forecast of each model. The error is reduced up to 20 % of the model errors, depending on the parameter and forecasting time.