• DocumentCode
    2670734
  • Title

    An Artificial Neural Network Approach for Short-Term Wind Power Forecasting in Portugal

  • Author

    Catalao, J.P.S. ; Pousinho, H.M.I. ; Mendes, V.M.F.

  • Author_Institution
    Univ. of Beira Interior, Covilha, Portugal
  • fYear
    2009
  • fDate
    8-12 Nov. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated, reporting the numerical results from a real-world case study.
  • Keywords
    neural nets; power engineering computing; power generation planning; wind power plants; artificial neural network; electric grid; short term wind power forecasting; Artificial intelligence; Artificial neural networks; Fuzzy logic; Power measurement; Predictive models; Statistical analysis; Temperature; Wind energy; Wind farms; Wind forecasting; Artificial neural networks; forecasting; wind power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on
  • Conference_Location
    Curitiba
  • Print_ISBN
    978-1-4244-5097-8
  • Type

    conf

  • DOI
    10.1109/ISAP.2009.5352853
  • Filename
    5352853