Back to Search
Start Over
Piecewise Support Vector Machine Model for Short-Term Wind-power Prediction.
- Source :
- International Journal of Green Energy; Sep/Oct2009, Vol. 6 Issue 5, p479-489, 11p, 2 Charts, 4 Graphs
- Publication Year :
- 2009
-
Abstract
- Based on the characteristics of the power curves of wind turbine generator systems and the principles of the support vector machine (SVM), a piecewise support vector machine (PSVM) model is proposed in this article to improve the precision of short-term wind-power prediction systems. The operation data from a wind farm in north China are used to verify the proposed model, and the average mean error and root mean squared error of the PSVM model are 4.76% and 68.83 kW less than that of an SVM model respectively. Results of parameter optimization confirm the robustness of the PSVM model. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15435075
- Volume :
- 6
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- International Journal of Green Energy
- Publication Type :
- Academic Journal
- Accession number :
- 44500395
- Full Text :
- https://doi.org/10.1080/15435070903228050