• DocumentCode
    2315689
  • Title

    Short-term wind speed forecasting combined time series method and arch model

  • Author

    Meng-Di Wang ; Qi-Rong Qiu ; Bing-Wei Cui

  • Author_Institution
    Fac. of Mech. & Electron. Inf., China Univ. of Geosci., Wuhan, China
  • Volume
    3
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    924
  • Lastpage
    927
  • Abstract
    In order to improve the accuracy of the wind speed forecasting in the wind farm, this paper presents an ARIMA-ARCH model, which considers the heteroscedastic effect between the fluctuation of wind speed and the characteristics of the change of wind speed, to forecast the wind speed. First of all, the ARIMA model for the wind speed time series is built by SPSS. After that, the high lag order ARCH effect is found in the residual of the ARIMA model by Lagrange multiplier (LM) test. At last, the GARCH model is built for simulating the residual series and thus to construct the ARIMA-ARCH model. Numerical experiments demonstrate the superiority of the proposed method when comparing with the traditional ARIMA model.
  • Keywords
    forecasting theory; time series; wind power; ARIMA-ARCH model; Lagrange multiplier; short-term wind speed forecasting; time series method; wind farm; Abstracts; Atmospheric measurements; Pollution measurement; Predictive models; Time series analysis; Wind forecasting; Wind speed; ARCH model; ARIMA model; Short-term wind speed forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4673-1484-8
  • Type

    conf

  • DOI
    10.1109/ICMLC.2012.6359477
  • Filename
    6359477