• DocumentCode
    3524006
  • Title

    An economic NMPC formulation for wind turbine control

  • Author

    Gros, Sebastien

  • Author_Institution
    Signals & Syst.,, Chalmers Univ. of Technol., Goteborg, Sweden
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    1001
  • Lastpage
    1006
  • Abstract
    Model Predictive Control (MPC) is a strong candidate for the control of large Multi-MegaWatt Wind Turbine Generators. Several MPC and some Nonlinear MPC scheme have been proposed in the literature, based on reference-tracking objective functions. While the resulting schemes offer very promising results, the difficulty of tuning a reference-tracking NMPC scheme for performance is likely to be a hindrance to the industrial success of NMPC-based WTG control. Because they directly maximize the system performance, economic NMPC schemes are more straightforward to tune. Economic NMPC schemes present, however, some known difficulties that are a serious obstacle to their real-time deployment. This paper presents an economic NMPC formulation for maximizing the generated power of wind turbine generators, which does not suffer from such difficulties. The relationship between the proposed and more classical reference-tracking approaches is formally established.
  • Keywords
    nonlinear control systems; power generation control; predictive control; wind turbines; NMPC-based WTG control; economic NMPC formulation; model predictive control; multimegawatt wind turbine generator control; nonlinear MPC scheme; power generation maximization; reference-tracking NMPC scheme; reference-tracking objective functions; system performance maximization; wind turbine control; Generators; Linear programming; Optimization; Rotors; Steady-state; Torque; Wind turbines; Operational Constraints; Power Optimization; Wind Turbine Control; economic NMPC;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6760013
  • Filename
    6760013