• DocumentCode
    2770726
  • Title

    Design of Optimal PI Controllers for Doubly Fed Induction Generators Driven by Wind Turbines Using Particle Swarm Optimization

  • Author

    Qiao, Wei ; Venayagamoorthy, Ganesh K. ; Harley, Ronald G.

  • Author_Institution
    Georgia Inst. of Technol., Atlanta
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1982
  • Lastpage
    1987
  • Abstract
    When subjected to transient disturbances in the power grid, the variable frequency converter (VFC) is the most sensitive part in the variable-speed wind turbine generator system (WTGS) equipped with a doubly fed induction generator (DFIG). The VFC is normally controlled by a set of PI controllers. Tuning these PI controllers is a tedious work and it is difficult to tune the PI gains optimally due to the nonlinearity and the high complexity of the system. This paper presents an approach to use the particle swarm optimization algorithm to design the optimal PI controllers for the rotor-side converter of the DFIG. A new time-domain fitness function is defined to measure the performance of the controllers. Simulation results show that the proposed design approach is efficient to find the optimal parameters of the PI controllers and therefore improves the transient performance of the WTGS over a wide range of operating conditions.
  • Keywords
    PI control; asynchronous generators; machine control; optimal control; particle swarm optimisation; rotors; time-domain analysis; wind turbines; doubly fed induction generator; optimal PI control; particle swarm optimization; rotor-side converter; time-domain fitness function; variable frequency converter; wind turbine generator system; Frequency conversion; Induction generators; Mesh generation; Optimal control; Particle swarm optimization; Power generation; Power grids; Tuning; Wind energy generation; Wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246944
  • Filename
    1716354