DocumentCode
3049529
Title
Improvement of short-term forecast for wind speed
Author
Bai, Xinxin ; Han, Shaocong ; Wang, Haifeng ; Yin, Wenjun ; Sun, Rongfu ; Zhang, Tao ; Liu, Jun ; Lei, Weimin
Author_Institution
IBM Res. - China, Beijing, China
fYear
2012
fDate
8-10 July 2012
Firstpage
451
Lastpage
455
Abstract
This paper presents a new type of linear regression model called sparse linear regression (SLR) model for short-term wind speed forecasting. Modifications are applied to the SLR model and some other variant models are proposed. Experiments are carried out on real wind farm history recording data. Results show SLR model and its variants can improve the accuracy of the short-term forecasting result compared with linear regression model.
Keywords
power system simulation; regression analysis; wind power; wind power plants; real wind farm history recording data; short-term forecast; sparse linear regression model; wind speed; Area measurement; Support vector machines; Vectors; Wind speed;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Operations and Logistics, and Informatics (SOLI), 2012 IEEE International Conference on
Conference_Location
Suzhou
Print_ISBN
978-1-4673-2400-7
Type
conf
DOI
10.1109/SOLI.2012.6273579
Filename
6273579
Link To Document