• DocumentCode
    3253155
  • Title

    A wind speed estimation method using adaptive Kalman filtering for a variable speed stall regulated wind turbine

  • Author

    Bourlis, Dimitris ; Bleijs, J.A.M.

  • Author_Institution
    Dept. of Eng., Univ. of Leicester, Leicester, UK
  • fYear
    2010
  • fDate
    14-17 June 2010
  • Firstpage
    89
  • Lastpage
    94
  • Abstract
    This paper presents a method for the estimation of the effective wind speed acting on the rotor of a wind turbine in order to be used for the control of a variable speed stall regulated wind turbine. The estimation algorithm consists of a Kalman filter, estimating the aerodynamic torque acting on the rotor of the turbine, and a Newton-Raphson method, which derives the effective wind speed from the aerodynamic torque. The Kalman filter is enhanced with adaptive algorithms that estimate the unknown covariances of the measurement and process noise respectively, keeping the filter continuously tuned close to its optimal behavior. The presented algorithm and results are based on a full model of a wind turbine, which entails the presence of two flexible shafts and three moments of inertia. From software and hardware simulation results it can be seen that the method is quite promising.
  • Keywords
    Newton-Raphson method; adaptive Kalman filters; noise; rotors; torque; velocity measurement; wind turbines; Newton-Raphson method; adaptive Kalman filtering; aerodynamic torque estimation; flexible shafts; hardware simulation; moments of inertia; noise; rotor; software simulation; variable speed stall regulated wind turbine control; wind speed estimation method; Adaptive algorithm; Adaptive filters; Aerodynamics; Filtering; Kalman filters; Newton method; Noise measurement; Torque; Wind speed; Wind turbines; adaptive Kalman filter; control of wind turbines; stall regulated wind turbines; wind estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5720-5
  • Type

    conf

  • DOI
    10.1109/PMAPS.2010.5528980
  • Filename
    5528980