DocumentCode
2085897
Title
The Study of Wind Power Combination Prediction
Author
Han, Shuang ; Liu, Yongqian
Author_Institution
Renewable Energy Sch., North China Electr. Power Univ., Beijing, China
fYear
2010
fDate
28-31 March 2010
Firstpage
1
Lastpage
4
Abstract
According to the maximum entropy principle and the characteristic of wind farm power series, a combined wind power prediction model was proposed. The wind power series is non-gauss distribution, so high central moment were added to prediction model besides the second central moment. The prediction results showed that the proposed model can improve the prediction precision.
Keywords
maximum entropy methods; wind power plants; maximum entropy principle; non-gauss distribution; wind farm power series; wind power combination prediction; wind power series; Artificial neural networks; Information entropy; Information theory; Load modeling; Prediction methods; Predictive models; Renewable energy resources; Support vector machines; Wind energy; Wind farms;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location
Chengdu
Print_ISBN
978-1-4244-4812-8
Electronic_ISBN
978-1-4244-4813-5
Type
conf
DOI
10.1109/APPEEC.2010.5448145
Filename
5448145
Link To Document