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Title: Time-adaptive kernel density forecast: a new method for wind power uncertainty modeling
Authors: Emil Constantinescu
Ricardo Jorge Bessa
Jean Sumaili
Vladimiro Miranda
Audun Botterud
Jianhui Wang
Issue Date: 2011
Abstract: 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 case-studies and compared with linear and splines quantile regression.
metadata.dc.type: conferenceObject
Appears in Collections:CPES - Indexed Articles in Conferences

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