• DocumentCode
    3492251
  • Title

    ANN approach to WECS power forecast

  • Author

    Fonte, P.M. ; Quadrado, J.C.

  • Author_Institution
    Rua Conselheiro Emidio Navarro, Inst. Superior de Engenharia de Lisboa
  • Volume
    1
  • fYear
    2005
  • fDate
    19-22 Sept. 2005
  • Lastpage
    1072
  • Abstract
    In this work-in-progress the problem with the future integration of large quantity of wind generators in the Portuguese electric grid is presented. A method based in artificial neural networks (ANN) is used to predict the average hourly wind speed. The work starts by choosing the patterns set length, the ANN structure and the learning method. As well as the dimensions of the data sets, training, validation and test. The ANN is tested with several structures until it archives an acceptable ANN based model. The obtained model is used to predict the wind speed and to forecast the power produced. The results archived are discussed. The future work perspectives are present
  • Keywords
    load forecasting; neural nets; power grids; power system analysis computing; wind power plants; ANN approach; Portuguese electric grid; WECS power forecast; artificial neural network; learning method; wind generator; Artificial neural networks; Distributed power generation; Photovoltaic systems; Power generation; Testing; Uncertainty; Wind energy generation; Wind forecasting; Wind power generation; Wind speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies and Factory Automation, 2005. ETFA 2005. 10th IEEE Conference on
  • Conference_Location
    Catania
  • Print_ISBN
    0-7803-9401-1
  • Type

    conf

  • DOI
    10.1109/ETFA.2005.1612645
  • Filename
    1612645