• DocumentCode
    2906781
  • Title

    Model predictive and adaptive wind farm power control

  • Author

    Yi Guo ; Wei Wang ; Choon Yik Tang ; Jiang, John ; Ramakumar, Rama G.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Univ. of Oklahoma, Norman, OK, USA
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    2890
  • Lastpage
    2897
  • Abstract
    This paper introduces a wind farm controller that enables the power output of a wind farm to accurately and smoothly track a desired reference from a power grid operator. Developed based on a model of wind turbine control systems we recently proposed, the wind farm controller consists of an outer control loop and an inner one. The outer loop contains a model predictive controller, which uses various forecasts and feedbacks to iteratively compute a set of desired power trajectories, so that the deterministic tracking accuracy of the wind farm power output on a receding horizon is optimized. In contrast, the inner loop contains an adaptive controller, which uses estimated wind speed characteristics to adaptively tune a set of proportional controller gains, so that the stochastic smoothness of the wind farm power output on a shorter timescale is optimized. The paper also provides a series of simulation studies that illustrate the salient features of the wind farm controller.
  • Keywords
    adaptive control; power control; predictive control; proportional control; stochastic systems; wind power plants; wind turbines; adaptive wind farm power control; deterministic tracking accuracy; inner control loop; model predictive wind farm power control; outer control loop; power grid operator; power trajectories; proportional controller gains; receding horizon; stochastic smoothness; wind turbine control systems; Adaptation models; Optimization; Predictive models; Wind farms; Wind forecasting; Wind speed; Wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6580273
  • Filename
    6580273