• DocumentCode
    1938033
  • Title

    Short and mid-term wind power plants forecasting with ANN

  • Author

    Mahmoudi, Javad ; Jamil, Majid ; Balaghi, Hossein

  • Author_Institution
    Electr. Eng., Sharif Univ., Tehran, Iran
  • fYear
    2012
  • fDate
    6-8 March 2012
  • Firstpage
    167
  • Lastpage
    171
  • Abstract
    In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24 hours) power forecasting are presented for a sample wind power plant by multilayer ANN. The needed inputs data are temperature and wind speed for forecasting the power. A case study has presented.
  • Keywords
    load forecasting; neural nets; power engineering computing; wind power plants; artificial neural networks; mid-term wind power plant forecasting; multilayer ANN; short-term power forecasting; time 1 hour; time 24 hour; wind energy; wind speed; Artificial neural networks; Forecasting; Power generation; Training; Wind forecasting; Wind speed; artificial neural network; power prediction; wind power forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Renewable Energy and Distributed Generation (ICREDG), 2012 Second Iranian Conference on
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4673-0663-8
  • Electronic_ISBN
    978-1-4673-0664-5
  • Type

    conf

  • DOI
    10.1109/ICREDG.2012.6190456
  • Filename
    6190456