Title :
Grid Parameter Estimation Using Model Predictive Direct Power Control
Author :
Arif, Bilal ; Tarisciotti, Luca ; Zanchetta, Pericle ; Clare, Jon C. ; Degano, Marco
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Nottingham, Nottingham, UK
Abstract :
This paper presents a novel finite-control-set model predictive control (FS-MPC) approach for grid-connected converters. The control performance of such converters may get largely affected by variations in the supply impedance, especially for systems with low short-circuit ratio values. A novel idea for estimating the supply impedance variation, and hence the grid voltage, using an algorithm embedded in the MPC is presented in this paper. The estimation approach is based on the difference in grid voltage magnitudes at two consecutive sampling instants, calculated on the basis of supply currents and converter voltages directly within the MPC algorithm, achieving a fast estimation and integration between the controller and the impedance estimator. The proposed method has been verified, using simulation and experiments, on a three-phase two-level converter.
Keywords :
power control; power convertors; predictive control; voltage control; FS-MPC approach; consecutive sampling instants; converter voltages; finite-control-set model predictive control approach; grid parameter estimation; grid voltage magnitudes; grid-connected converters; impedance estimator; model predictive direct power control; short-circuit ratio values; supply currents; supply impedance variation; three-phase two-level converter; Estimation; Impedance; Inductance; Reactive power; Resistance; Switches; Voltage control; AC???DC power conversion; grid impedance estimation; model predictive control (MPC); power conversion; power system dynamic stability;
Journal_Title :
Industry Applications, IEEE Transactions on
DOI :
10.1109/TIA.2015.2453132