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Wind power day-ahead prediction with cluster analysis of NWP.
- Source :
-
Renewable & Sustainable Energy Reviews . Jul2016, Vol. 60, p1206-1212. 7p. - Publication Year :
- 2016
-
Abstract
- The selection of training data for establishing a model directly affects the prediction precision. Wind power has the characteristic of daily similarity. The corresponding meteorological data also has the characteristic of daily similarity. This paper proposes a new model with cluster analysis of the numerical weather prediction information. The similar day with the predicted day is searched as training sample to a generalized regression neural network model. The numerical weather prediction data and actual wind power data from a wind farm are used in this study to test the model. The prediction results show that correct cluster analysis method is a useful tool in day-ahead wind power prediction. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13640321
- Volume :
- 60
- Database :
- Academic Search Index
- Journal :
- Renewable & Sustainable Energy Reviews
- Publication Type :
- Academic Journal
- Accession number :
- 114496776
- Full Text :
- https://doi.org/10.1016/j.rser.2016.01.106