• DocumentCode
    3213539
  • Title

    An enhanced ANN wind power forecast model based on a fuzzy representation of wind direction

  • Author

    Gavrilas, Mihai ; Gavrila, Gilda

  • Author_Institution
    Power Syst. Dept., Tech. Univ. of Iasi, Iasi, Romania
  • fYear
    2010
  • fDate
    23-25 Sept. 2010
  • Firstpage
    31
  • Lastpage
    36
  • Abstract
    Due to high penetration of wind generation in modern power systems, the influence of wind power production over the efficient operation of the power system is increasingly complex. Hence, an increasing interest is shown by different actors in the wind energy market to develop and enhance existent forecasting methods for power generated by wind farms. This paper presents the experience with wind power prediction of a small size wind power producer in Romania. The model was designed using components from Artificial Neural Networks and Fuzzy System theory.
  • Keywords
    fuzzy set theory; neural nets; power engineering computing; wind power plants; ANN wind power forecast model; fuzzy representation; fuzzy system theory; wind direction; wind energy market; wind farms; wind generation system; wind power production; Artificial neural networks; Forecasting; Pragmatics; Wind forecasting; Wind power generation; Wind speed; Wind turbines; Artificial neural networks; Fuzzy systems; Wind power forecast; Wind power generator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Network Applications in Electrical Engineering (NEUREL), 2010 10th Symposium on
  • Conference_Location
    Belgrade
  • Print_ISBN
    978-1-4244-8821-6
  • Type

    conf

  • DOI
    10.1109/NEUREL.2010.5644050
  • Filename
    5644050