• DocumentCode
    737043
  • Title

    The Online Forecasting Research of Short-Term Wind Speed and Power Generation at Wind Farm Based on Phase Space Reconstruction

  • Author

    Yajun, Han ; Jing, Liu

  • fYear
    2015
  • fDate
    13-14 June 2015
  • Firstpage
    1234
  • Lastpage
    1237
  • Abstract
    It is difficult to be accurately predicted for wind power generation´s random, intermittent and volatility. According to the strong chaotic characteristics of wind speed, the optimal time delay and embedding dimensions of wind speed are determined by using a short-term prediction of phase space reconstruction theory. After the sample space is reconstructed, the short-term wind speed is carried out by BP neural network. The experimental results show that the higher forecasting accuracy of short-term power generation can be obtained.
  • Keywords
    Biological neural networks; Delays; Forecasting; Power generation; Time series analysis; Wind speed; BP neural network; Phase space reconstruction; complex self-correlation method; false zero method; wind speed forecast;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2015 Seventh International Conference on
  • Conference_Location
    Nanchang, China
  • Print_ISBN
    978-1-4673-7142-1
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2015.300
  • Filename
    7263796