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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Service Operations and Logistics, and Informatics (SOLI), 2012 IEEE International Conference on
         
        
            Conference_Location : 
Suzhou
         
        
            Print_ISBN : 
978-1-4673-2400-7
         
        
        
            DOI : 
10.1109/SOLI.2012.6273579