Solar PV Power Forecasting Using Extreme Learning Machine and Information Fusion

We provide a learning algorithm combining distributed Ex- treme Learning Machine and an information fusion rule based on the ag- gregation of experts advice, to build day ahead probabilistic solar PV power production forecasts. These forecasts use, apart from the current day solar PV power production, local meteorological inputs, the most valu- able of which is shown to be precipitation. Experiments are then run in one French region, Provence-Alpes-C^ d'Azur, to evaluate the algorithm performance.