• DocumentCode
    253922
  • Title

    Distributed model predictive control for active power control of wind farm

  • Author

    Haoran Zhao ; Qiuwei Wu ; Rasmussen, Claus Nygaard ; Qinglai Guo ; Hongbin Sun

  • Author_Institution
    Dept. of Electr. Eng., Tech. Univ. of Denmark, Lyngby, Denmark
  • fYear
    2014
  • fDate
    12-15 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D-MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can be considered to achieve a trade-off between them. Additionally, D-MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large-scale wind farm control.
  • Keywords
    centralised control; distributed control; optimisation; power generation control; predictive control; wind power plants; wind turbines; D-MPC; active power control; centralized wind farm control; distributed model predictive controller; power reference tracking performance; wind turbine load; Force; Generators; Load modeling; Shafts; Torque; Wind farms; Wind turbines; Active power control; D-MPC; dual decomposition; multi-objective; wind farm control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2014 IEEE PES
  • Conference_Location
    Istanbul
  • Type

    conf

  • DOI
    10.1109/ISGTEurope.2014.7028925
  • Filename
    7028925