  Photovoltaic (PV) power production increased drastically in Europe throughout
the last years. About the 6% of electricity in Italy comes from PV and for an
efficient management of the power grid an accurate and reliable forecasting of
production would be needed. Starting from a dataset of electricity production
of 65 Italian solar plants for the years 2011-2012 we investigate the
possibility to forecast daily production from one to ten days of lead time
without using on site measurements. Our study is divided in two parts: an
assessment of the predictability of meteorological variables using weather
forecasts and an analysis on the application of data-driven modelling in
predicting solar power production. We calibrate a SVM model using available
observations and then we force the same model with the predicted variables from
weather forecasts with a lead time from one to ten days. As expected, solar
power production is strongly influenced by cloudiness and clear sky, in fact we
observe that while during summer we obtain a general error under the 10%
(slightly lower in south Italy), during winter the error is abundantly above
the 20%.
