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Probabilistic Short-term Wind Power Forecasting for the Optimal Management of Wind Generation

Wind power forecasting tools have been developed for some time. The majority of such tools usually provides single-valued (spot) predictions. Such predictions limits the use of tools for decision-making under uncertainty. In this paper we propose a method for producing the complete predictive probability density function (PDF). The method is based on kernel density estimation techniques. The preliminary results show that this method levels with state of the art one while being fast and producing the complete PDF. The results were obtained through real data from three French wind farms.