Short-term wind power prediction with radial basis networks

Title:

Short-term wind power prediction with radial basis networks

Creator:

ter Borg, Rutger W. and Rothkrantz , León J. M.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:8f7184c9-097c-4ad3-9b6d-06c16257e94e
uuid:8f7184c9-097c-4ad3-9b6d-06c16257e94e

Subject:

Wind power prediction, radial basis functions, and kernel machines

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

In this paper, we propose a method to predict wind power production with radial basis function networks. In this case, the power production is the aggregated production of all wind farms of one electricity company. The method uses wind speed predictions supplied by a meteorological agency, and predicts up to several days ahead. The coarse resolution of one meter per second is overcome by combining the weather data from several meteorological stations. The wind direction is mapped on a circle, so it is more compatible with a radial basis. These ingredients have been combined with a kernel machine, which has been implemented and tested. Test results are presented in the paper.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2006 Volume:16 | Number:2

Harvested from:

CDK

Metadata only:

false