Open AccessTorque ripple reduction of DFIG by a new and robust predictive torque control method
Author(s) -
Mokhtari Vayeghan Mohsen,
Davari S. Alireza
Publication year - 2017
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2016.0695
Subject(s) - control theory (sociology) , torque ripple , direct torque control , torque , model predictive control , robustness (evolution) , damping torque , stall torque , doubly fed electric machine , ripple , computer science , engineering , voltage , ac power , control (management) , induction motor , physics , artificial intelligence , electrical engineering , thermodynamics , biochemistry , chemistry , gene
A torque ripple minimising and robust predictive torque control of a doubly fed induction generator (DFIG) is proposed. The proposed method is based on a novel cost function and a robust predictive model. The aim of the proposed cost function is torque ripple reduction beside the torque and flux control. This method predicts the torque and the flux those will be resulted by the feasible voltage vectors for the next step. The best option is chosen and applied based on the proposed cost function. Two expressions are added to the conventional cost function for the torque ripple reduction. These terms minimise the effective value of the torque ripple and the variation of the torque while the main control is not affected. Furthermore, a novel closed‐loop prediction model for DFIG is proposed in order to improve the robustness of the method. Simulation results for the conventional finite control set‐model predictive control and the proposed methods are presented and compared in order to confirm the effectiveness of this method.