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This paper reports the application of a new kernel density estimation model based on the Nadaraya-Watson estimator, for the problem of wind power uncertainty forecasting. The new model is described, including the use of kernels specific to the wind power problem. A novel time-adaptive approach is presented. The quality of the new model is benchmarked against a splines quantile regression model currently...
Wind power forecasting has great significance to the connection of wind farms to the electric power system. This paper analyzes individual forecast models, such as the time series forecasting, Elman network forecasting that based on the chaos theory, grey neural network forecasting, and generalized regression neural network forecasting, etc., then puts forward an entropy weight combination prediction...
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