• DocumentCode
    2869792
  • Title

    The Estimation of Wind Turbine Pitch Angle Based on ANN

  • Author

    Liu, Yanping ; Liu, Shuhong ; Guo, Hongmei ; Wang, Huajun

  • Author_Institution
    Inst. of Inf. Eng., Hebei Univ. of Technol., Tianjin, China
  • fYear
    2009
  • fDate
    1-3 Nov. 2009
  • Firstpage
    581
  • Lastpage
    584
  • Abstract
    Variable-speed and constant-frequency (VSCF) pitch-controlled wind turbine is believed to be superior to other types of wind turbine due to its features such as high efficiency and ideal starting and braking performance, artificial neural networks (ANN) technology is adopted to predict pitch angle at real-time working condition, and to obtain more accurate pitch angle reference value. It enhances control precision of the entire pitch-controlled system. Pitch-controlled system, the very core of a large-scale wind turbine control system, is playing a very important role in the security, stability and efficient operation of the units.
  • Keywords
    neurocontrollers; power generation control; wind turbines; ANN; artificial neural networks; real-time working condition; starting-braking performance; variable-speed and constant-frequency pitch-controlled wind turbine; wind turbine pitch angle estimation; Artificial neural networks; Control systems; Mathematical model; Neural networks; Power generation; Rotors; Wind energy; Wind energy generation; Wind speed; Wind turbines; ANN; Pitch-controlled system; VSCF; pitch angle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-5557-7
  • Electronic_ISBN
    978-0-7695-3852-5
  • Type

    conf

  • DOI
    10.1109/ICINIS.2009.153
  • Filename
    5366565