• DocumentCode
    2257718
  • Title

    Fuzzy feed forward system based on T-S model applied for constant power control in wind power system

  • Author

    Peng, Hai-liang ; Guo, Peng ; Jia, Jian-jun

  • Author_Institution
    Dept. of Autom. & Comput. Eng., North China Electr. Power Univ., Beijing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    26
  • Lastpage
    31
  • Abstract
    Constant power control technology is one of the key technologies in wind power control. PI control is the most widely used technology in constant power control system. Hysteresis of PI control will cause a large overshoot of the output power that will make interference to the power grid. Feedforward control system can reduce the system lag. The fuzzy controller based on T-S model can overcome the influence caused by non-linear and uncertain mathematical model of the system. The fuzzy controller makes the feedforward controller easy to realize. Introducing neural network training method into Fuzzy control will greatly simplify the design of fuzzy controller. Based on Neural Adaptive - Fuzzy technology, a feed forward system is proposed in this paper, which is able to timely adjust pitch angle according to changes of wind speed. At last, the control strategy is simulated by MATLAB. The simulation results show that the method greatly improves the performance of system dynamic response, thus ensuring a constant power output.
  • Keywords
    PI control; adaptive control; feedforward; fuzzy control; neurocontrollers; power grids; power system control; wind power; PI control; T-S model applied; constant power control system; fuzzy feedforward control system; neural adaptive fuzzy technology; neural network training method; power grid; uncertain mathematical model; wind power system; Feeds; Generators; Mathematical model; Neurons; Pi control; Wind power generation; Wind speed; Constant Power Control; Fuzzy-feed forward control; T-S Model; Variable pitch; Wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5581098
  • Filename
    5581098