Open AccessSimplified model predictive direct torque control method without weighting factors for permanent magnet synchronous generator‐based wind power system
Author(s) -
Guo Leilei,
Zhang Xing,
Yang Shuying,
Xie Zhen,
Wang Lingxiang,
Cao Renxian
Publication year - 2017
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/iet-epa.2015.0620
Subject(s) - control theory (sociology) , direct torque control , torque , permanent magnet synchronous generator , stator , weighting , damping torque , wind power , robustness (evolution) , stationary reference frame , reference frame , ac power , engineering , magnet , computer science , power (physics) , physics , frame (networking) , induction motor , control (management) , chemistry , voltage , artificial intelligence , acoustics , telecommunications , biochemistry , quantum mechanics , thermodynamics , mechanical engineering , electrical engineering , gene
Conventional model predictive direct torque control (MP‐DTC) of permanent magnet synchronous generator (PMSG) suffers from weighing factor tuning work and relatively large calculation amount. This study proposes a simplified MP‐DTC method without weighting factors for PMSG‐based wind power system. First, the torque and stator flux magnitude are predicted on the stationary reference frame instead of on the synchronous rotating reference frame, hence reducing the calculation amount. Second, a new cost function based on the torque and the reactive torque is developed in this study. As the torque and the reactive torque have the same order of magnitude, the weighting factor which is needed in the conventional MP‐DTC system is eliminated. Meanwhile, the stator current and stator flux magnitude can be controlled indirectly by controlling the torque and reactive torque simultaneously, which ensures the stability of the system. Besides, the robustness of the proposed strategy to unknown PMSG parameter variations is improved to a certain extent. The experimental results validate the effectiveness of the proposed method.