Please use this identifier to cite or link to this item:
|Title:||Time-adaptive kernel density forecast: a new method for wind power uncertainty modeling|
Ricardo Jorge Bessa
|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.|
|Appears in Collections:||CPES - Articles in International Conferences|
Files in This Item:
|186.17 kB||Adobe PDF||View/Open Request a copy|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.