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Blade imbalance fault diagnosis of doubly fed wind turbine based on current coordinate transformation
Author(s) -
Yang Dong,
Tang Ju,
Zeng Fuping
Publication year - 2019
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22796
Subject(s) - stator , fault (geology) , doubly fed electric machine , coordinate system , induction generator , turbine , control theory (sociology) , blade (archaeology) , wind power , transformation (genetics) , current (fluid) , generator (circuit theory) , engineering , computer science , ac power , physics , structural engineering , power (physics) , electrical engineering , voltage , mechanical engineering , artificial intelligence , geology , biochemistry , chemistry , control (management) , quantum mechanics , seismology , gene
A stator current characteristic analysis method based on coordinate transformation is proposed to address the issue of the double‐fed induction generator (DFIG) blade imbalance. Based on the DFIG and the wind turbine transmission chain model, the stator current expression of DFIG under blade imbalance failure was derived in detail, and the corresponding fault characteristic frequency was analyzed, which shows that the blade imbalance fault causes the stator current of the DFIG to generate the fault feature component with frequency f m on the d ‐axis and q ‐axis components. Then, the stator current characteristic analysis method based on coordinate transformation was proposed. Finally, a simulation model of DFIG with blade imbalance was established, and the fault characteristics of the turbine under different wind speeds and imbalance coefficients are simulated and analyzed. The results show that the stator current characteristic analysis method based on coordinate transformation can extract the characteristics of imbalanced fault and can be effective in determining the severity of the fault by monitoring the changes in the amplitude of the characteristic frequency compared with direct spectrum analysis of stator current and blade speed. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.