Satellite based nowcasting of PV energy over peninsular Spain

Abstract

In this work we will study the use of satellite-measured irradiances as well as clear sky radiance estimates as features for the nowcasting of photovoltaic energy productions over Peninsular Spain. We will work with three Machine Learning models (Lasso and linear and Gaussian Support Vector Regression-SVR) plus a simple persistence model. We consider prediction horizons of up to three hours, for which Gaussian SVR is the clear winner, with a quite good performance and whose errors increase slowly with time. Possible ways to further improve these results are also proposed.