• DocumentCode
    1735232
  • Title

    Wind turbine pitch optimization

  • Author

    Biegel, Benjamin ; Juelsgaard, Morten ; Kraning, Matt ; Boyd, Stephen ; Stoustrup, Jakob

  • Author_Institution
    Dept. of Autom. & Control, Univ. of Aalborg, Aalborg, Denmark
  • fYear
    2011
  • Firstpage
    1327
  • Lastpage
    1334
  • Abstract
    We consider a static wind model for a three-bladed, horizontal-axis, pitch-controlled wind turbine. When placed in a wind field, the turbine experiences several mechanical loads, which generate power but also create structural fatigue. We address the problem of finding blade pitch profiles for maximizing power production while simultaneously minimizing fatigue loads. In this paper, we show how this problem can be approximately solved using convex optimization. When there is full knowledge of the wind field, numerical simulations show that force and torque RMS variation can be reduced by over 96% compared to any constant pitch profile while sacrificing at most 7% of the maximum attainable output power. Using iterative learning, we show that very similar performance can be achieved by using only load measurements, with no knowledge of the wind field or wind turbine model.
  • Keywords
    convex programming; power generation control; wind turbines; RMS variation; blade pitch profiles; convex optimization; iterative learning; power production; static wind model; structural fatigue; wind turbine pitch optimization; Blades; Fatigue; Force; Poles and towers; Rotors; Torque; Wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications (CCA), 2011 IEEE International Conference on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    978-1-4577-1062-9
  • Electronic_ISBN
    978-1-4577-1061-2
  • Type

    conf

  • DOI
    10.1109/CCA.2011.6044383
  • Filename
    6044383