• DocumentCode
    159213
  • Title

    Finite Set Model Predictive Control with a novel online grid inductance estimation technique

  • Author

    Arif, Bilal ; Tarisciotti, Luca ; Zanchetta, Pericle ; Clare, Jon

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Univ. of Nottingham, Nottingham, UK
  • fYear
    2014
  • fDate
    8-10 April 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a novel finite control set Model Predictive Control (MPC) approach, for grid connected converters. The advantage of using MPC for this application lies in the fact that it does not require cascaded control loops, PWM modulators or PLLs. However, the supply impedance is generally unknown causing remarkable errors in the MPC control action, in the case its value is not negligible compared to the converter inductance. This paper presents a novel idea for estimating the supply inductance, based on the difference between the grid voltage magnitudes at two consecutive sampling instants. The grid voltage magnitudes are calculated on the basis of the supply current and converter voltage directly within the MPC algorithm, in order to achieve a fast estimation and integration between the controller and estimator. The proposed method is verified via simulation tests on a three-phase two level active front-end.
  • Keywords
    electric impedance; inductance; power convertors; power grids; predictive control; MPC; consecutive sampling instants; finite control set; grid connected converter inductance; grid voltage magnitudes; model predictive control approach; online grid inductance estimation technique; supply impedance; three-phase two level active front-end; Inductance estimation; Predictive Control;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Power Electronics, Machines and Drives (PEMD 2014), 7th IET International Conference on
  • Conference_Location
    Manchester
  • Electronic_ISBN
    978-1-84919-815-8
  • Type

    conf

  • DOI
    10.1049/cp.2014.0299
  • Filename
    6836947