• DocumentCode
    619951
  • Title

    Studies on wind farms ultra-short term NWP wind speed correction methods

  • Author

    Lei Dong ; Liang Ren ; Shuang Gao ; Yang Gao ; Xiaozhong Liao

  • Author_Institution
    Sch. of Autom., Beijing Inst. of Technol., Beijing, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    1576
  • Lastpage
    1579
  • Abstract
    Ultra-short term wind speed forecast for wind farm is of great significance to the real-time scheduling of wind power system. In this paper, NWP (Numerical Weather Prediction) wind speed time series and measured wind speed time series were decomposed into different bands by wavelet multi-resolution analysis. Pearson product-moment correlation coefficient was used to verify the correction premise. Then the linear correction method was used to correct the low frequency stationary NWP wind speed. To test the approach, the data from Yilan wind farm of Heilongjiang province were used. The results show that when a strong correlation exists in the system deviation of training periods and testing periods, the prediction accuracy of ultra-short term wind speed will be significantly improved.
  • Keywords
    correlation methods; load forecasting; power generation scheduling; power system measurement; time series; wavelet transforms; weather forecasting; wind power plants; Heilongjiang province; Pearson product-moment correlation coefficient; Yilan wind farm; linear correction method; low frequency stationary NWP wind speed; numerical weather prediction; real-time scheduling; ultrashort term wind speed forecasting; wavelet multiresolution analysis; wind power system; wind speed correction method; wind speed time series measurement; Correlation coefficient; Forecasting; Predictive models; Time series analysis; Wind farms; Wind forecasting; Wind speed; NWP; Ultra-short Term Prediction; Wavelet theory; Wind Farm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561180
  • Filename
    6561180