This paper develops an integrated machine learning and enhanced statistical approach for wind power interval forecasting. A\ntime-series wind power forecasting model is formulated as the theoretical basis of our method. The proposed model takes into\naccount two important characteristics of wind speed: the nonlinearity and the time-changing distribution. Based on the proposed\nmodel, six machine learning regression algorithms are employed to forecast the prediction interval of the wind power output.............
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