CONICET | Buscador de Institutos y Recursos Humanos

This paper presents a method to predict a day-ahead solar irradiation curve, under extreme meteorological phenomena (Föhn, North and South winds), existing in the province of San Juan-Argentina. The proposed method is based on an Artificial Neuronal Network (ANN) which is trained with a data-set filtered by the environmental variables that characterize the mentioned phenomena. A previously calculated ideal solar irradiation curve is modified from the forecasts generated by the ANN. The proposed methodology merges statistical learning methods and Numerical Weather Predictions methods (NWP), typically used to improve upon the raw forecast of a NWP model. A reduction of the uncertainty in power production of photovoltaic plants in San Juan can be achieved with the results of the proposed forecasting method.