• DocumentCode
    115682
  • Title

    A distributed algorithm for NMPC-based wind farm control

  • Author

    Gros, Sebastien

  • Author_Institution
    Dept. of Signals & Syst., Chalmers Univ. of Technol., Göteborg, Sweden
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    4844
  • Lastpage
    4849
  • Abstract
    Nonlinear Model Predictive Control (NMPC) has been identified as a highly promising control technique for wind turbine generators, and has been shown to be realtime feasible for the control of individual wind turbines. The potential benefit of performing control at the wind farm level is well understood, and has been recently investigated in the literature. Likewise, the extension of NMPC from wind turbine to wind farm control is highly desirable, but very challenging since it requires solving large non-convex optimal control problems in real time. It has not been considered so far in the literature. This paper proposes a first contribution in that direction, using a distributed optimisation approach based on the Lagrange relaxation. The proposed algorithm requires a very limited amount of additional computations when compared to controlling the wind turbines individually via NMPC. The problem of smoothing the wind farm power output is considered here.
  • Keywords
    control engineering computing; convex programming; distributed algorithms; nonlinear control systems; optimal control; power engineering computing; power generation control; predictive control; real-time systems; wind power plants; Lagrange relaxation; NMPC; distributed algorithm; distributed optimisation approach; nonconvex optimal control problems; nonlinear model predictive control; real time systems; wind farm control; wind turbine generators; Aerodynamics; Computational modeling; Generators; Lagrangian functions; Real-time systems; Wind farms; Wind turbines; Lagrange relaxation; Real-Time Iteration; distributed NMPC; wind farm control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7040145
  • Filename
    7040145