WIND POWER experiences a tremendous developmentof its installed capacities inEurope. Though, the intermittence of wind generation causes difficulties in the management of power sys- tems. Also, in the context of the deregulation of electricity markets, wind energy is penalized by its intermittent nature. It is recognized today that the forecasting of wind power for horizons up to 2/3-day ahead eases the integration ofwind generation. Wind power forecasts are traditionally pro- vided in the formof point predictions, which correspond to themost-likely power production for a givenhorizon. That sole information isnot sufficient fordeveloping optimalmanagement or trading strategies. Therefore, we investigate on possible ways for estimating the uncertainty of wind power forecasts. The characteristics of the prediction uncertainty are described by a thorough study of the performance of some of the state-of-the-art approaches, and by underlining the influence of some variables e.g. level of predicted power on distributions of prediction errors. Then, a generic method for the estimation of prediction intervals is introduced. This statistical method is non-parametric and utilizes fuzzy logic concepts for integrating expertise on the prediction uncertainty characteristics.
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