Time-adaptive Kernel Density Forecast: a New Method for Wind Power Uncertainty Modeling
نویسندگان
چکیده
This paper reports new contributions to the advancement of wind power uncertainty forecasting beyond the current state-of-the-art. A new kernel density forecast (KDF) method applied to the wind power problem is described. The method is based on the Nadaraya-Watson estimator, and a time-adaptive version of the algorithm is also proposed. Results are presented for different casestudies and compared with linear and splines quantile regression.
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