• 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