• DocumentCode
    2859650
  • Title

    Short-term wind speed forecast of wind farm based on V-system and LSSVM

  • Author

    Xiao-lan, Wang ; Qian-cheng, Chen

  • Author_Institution
    School of Electrical and Information Engineering, Lanzhou University of Technology, Gansu, 730050, China
  • Volume
    3
  • fYear
    2012
  • fDate
    2-5 June 2012
  • Firstpage
    2113
  • Lastpage
    2117
  • Abstract
    V-system of degree k is a new class of complete orthogonal function system in L2[0,1]. A wind speed forecasting method based on V-system and least square support vector machine (LSSVM) is proposed in this paper. Grouping the wind speed time series, and then using linear discrete V-system to decompose each group of data. The decomposition coefficient vectors of each group of data in frequency domain are obtained. The different LSSVM models to forecast decomposition coefficients in the same frequency band are established. The forecasting decomposition coefficient vectors are reconstructed by the inverse V-system transform to get forecasting wind speed. The simulation experiment shows the prediction accuracy is improved considerably.
  • Keywords
    Forecasting; Kernel; Predictive models; Support vector machines; Vectors; Wind forecasting; Wind speed; V-system; decomposition coefficient vector; least square support vector machine (LSSVM); wind farm; wind speed time series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Motion Control Conference (IPEMC), 2012 7th International
  • Conference_Location
    Harbin, China
  • Print_ISBN
    978-1-4577-2085-7
  • Type

    conf

  • DOI
    10.1109/IPEMC.2012.6259171
  • Filename
    6259171