• DocumentCode
    3444271
  • Title

    Model predictive control for the high-power grid-connecting PWM converters

  • Author

    Qing-qing Yuan ; Xiao-jie Wu ; Ting-ting Zhang ; Kang-an Wang

  • Author_Institution
    Dept. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2013
  • fDate
    26-29 Oct. 2013
  • Firstpage
    252
  • Lastpage
    256
  • Abstract
    Large-scale network of the renewable energy imposes increasing stringent requirements, especially with regard to harmonic distortion limits imposed by the grid code and the switching losses of the high-power PWM converter itself. This paper presents a new control strategy adopting the receding horizon policy, i. e., model predictive control (MPC), for a diode clamped three-level topology converter. With a simplification of the three-level SVPWM into a two-level SVPWM and taking the grid current tracking error, harmonic distortion limits, switching numbers per cycle and the deviation of the neutral point potential as components of the cost function, a relative good performance could be obtained with a high degree of robustness because of the utility of receding horizon policy.
  • Keywords
    PWM power convertors; harmonic distortion; power grids; predictive control; MPC; control strategy; cost function; diode clamped three-level topology converter; grid current tracking error; harmonic distortion; high-power grid-connecting PWM converters; large-scale network; model predictive control; neutral point potential deviation; receding horizon control policy; renewable energy; switching losses; three-level SVPWM; two-level SVPWM; Harmonic analysis; MATLAB; Mathematical model; Space vector pulse width modulation; Switches; Vectors; PWM converter; high-power; model predictive control; receding horizon policy; three-level;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems (ICEMS), 2013 International Conference on
  • Conference_Location
    Busan
  • Print_ISBN
    978-1-4799-1446-3
  • Type

    conf

  • DOI
    10.1109/ICEMS.2013.6754453
  • Filename
    6754453