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Title

Fault detection for DFIG based on sliding mode observer of new reaching law

Journal title

Bulletin of the Polish Academy of Sciences Technical Sciences

Yearbook

2021

Volume

69

Issue

3

Affiliation

Li, RuiQi : School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Li, RuiQi : Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Yu, Wenxin : School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Yu, Wenxin : Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Wang, JunNian : School of Physics and Electronics, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Wang, JunNian : Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Lu, Yang : School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Lu, Yang : Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Jiang, Dan : School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Jiang, Dan : Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Zhong, GuoLiang : School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Zhong, GuoLiang : Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Zhou, ZuanBo : School of Information and Electrical Engineering, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China ; Zhou, ZuanBo : Key Laboratory of Knowledge Processing Networked Manufacturing, Hunan University of Science and Technology, Hunan Pro., Xiangtan,411201, China

Authors

Li, RuiQi ; Yu, Wenxin ; Wang, JunNian ; Lu, Yang ; Jiang, Dan ; Zhong, GuoLiang ; Zhou, ZuanBo

Keywords

fault detection ; doubly-fed induction generator ; sliding mode observer ; new reaching law

Divisions of PAS

Nauki Techniczne

Coverage

e137389

Bibliography

  1.  Z. Hameed, Y.S. Hong, Y.M. Cho, S.H. Ahn, and C.K. Song. “Condition monitoring and fault detection of wind turbines and related algorithms: A review”, Renew. Sust. Energ. Rev. 13(1), 1‒39 (2009).
  2.  A. Stefani, A. Yazidi, C. Rossi, F. Filippetti, D. Casadei, and G.A. Capolino, “Doubly fed induction machines diagnosis based on signature analysis of rotor modulating signals”, IEEE Trans. Ind. Appl. 44(6), 1711‒1721(2008).
  3.  D. Shah, S. Nandi, and P. Neti, “Stator-interturn-fault detection of doubly fed induction generators using rotor-current and search-coil- voltage signature analysis”, IEEE Trans. Ind. Appl. 45(5), 1831‒1842 (2009).
  4.  G. Stojčić, K. Pašanbegović, and T.M. Wolbank, “Detecting faults in doubly fed induction generator by rotor side transient current measurement”, IEEE Trans. Ind. App. 50(5), 3494‒3502 (2014).
  5.  R. Roshanfekr and A. Jalilian, “Wavelet-based index to discriminate between minor inter-turn short-circuit and resistive asymmetrical faults in stator windings of doubly fed induction generators, a simulation study”, IET Gener. Transm. Distrib. 10(2), 374‒381 (2016).
  6.  M.B. Abadi et al., “Detection of stator and rotor faults in a DFIG based on the stator reactive power analysis”, in IECON 2014‒40th Annual Conference of the IEEE Industrial Electronics Society 2014 pp. 2037‒2043.
  7.  S. He, X. Shen, and Z. Jiang, “Detection and Location of Stator Winding Interturn Fault at Different Slots of DFIG”, IEEE Access 7, 89342‒89353 (2019).
  8.  I. Erlich, C. Feltes, and F. Shewarega, “Enhanced voltage drop control by VSC–HVDC systems for improving wind farm fault ridethrough capability”, IEEE Trans. Power Deliv. 29(1), 378‒385 (2013).
  9.  Ö. Göksu, R. Teodorescu, C.L. Bak, F. Iov, and P.C. Kjær, “Instability of wind turbine converters during current injection to low voltage grid faults and PLL frequency based stability solution”, IEEE Trans. Power Syst. 29(4), 1683‒1691 (2014).
  10.  Z. Fan, G. Song, X. Kang, J. Tang, and X. Wang, “Three-phase fault direction identification method for outgoing transmission line of DFIG-based wind farms”, J. Mod. Power Syst. 7(5), 1155‒1164 (2019).
  11.  L.G. Meegahapola, T. Littler, and D. Flynn, “Decoupled-DFIG fault ride-through strategy for enhanced stability performance during grid faults”, IEEE Trans. Sustain. Energy 1(3), 152‒162 (2010).
  12.  F. Aguilera, P.M. De la Barrera, C.H. De Angelo, and D.E. Trejo, “Current-sensor fault detection and isolation for induction-motor drives using a geometric approach”, Control Eng. Pract. 53, 35‒46 (2016).
  13.  S. Abdelmalek, S. Rezazi, and A.T. Azar, “Sensor faults detection and estimation for a DFIG equipped wind turbine”, Energy Procedia 139, 3‒9 (2017).
  14.  M. Liu and P. Shi, “Sensor fault estimation and tolerant control for Itô stochastic systems with a descriptor sliding mode approach”, Automatica 49(5), 1242‒1250 (2013).
  15.  Y.J. Kim, N. Jeon, and H. Lee, “Model based fault detection and isolation for driving motors of a ground vehicle”, Sens. Transducers 199(4), 67 (2016).
  16.  K. Xiahou, Y. Liu, L. Wang, M.S. Li, and Q.H. Wu, “Switching fault-tolerant control for DFIG-based wind turbines with rotor and stator current sensor faults”, IEEE Access 7, 103390‒103403 (2019).
  17.  K.S. Xiahou, Y. Liu, M.S. Li, and Q.H. Wu, “Sensor fault-tolerant control of DFIG based wind energy conversion systems”, Int. J. Electr. Power Energy Syst. 117, 105563 (2020).
  18.  Z.Y. Xue, K.S. Xiahou, M.S. Li, T.Y. Ji, and Q.H. Wu, “Diagnosis of multiple open-circuit switch faults based on long short-term memory network for DFIG-based wind turbine systems”, IEEE J. Emerg. Sel. Top. Power Electron. 8(3), 2600‒2610 (2019).
  19.  L. Jing, M. Zhao, P. Li, and X. Xu, “A convolutional neural network based feature learning and fault diagnosis method for the condition monitoring of gearbox”, Measurement 111, 1‒10 (2017).
  20.  W. Teng, H. Cheng, X. Ding, Y. Liu, Z. Ma, and H. Mu, “DNN-based approach for fault detection in a direct drive wind turbine”, IET Renew. Power Gener. 12(10), 1164‒1171 (2018).
  21.  M.N. Akram and S. Lotfifard, “Modeling and health monitoring of DC side of photovoltaic array”, IEEE Trans. Sustain. Energy 6(4), 1245‒1253 (2015).
  22.  W. Gao and J.C. Hung, “Variable structure control of nonlinear systems, A new approach”, IEEE Trans. Ind. Electron. 40(1), 45‒55 (1993).
  23.  C.J. Fallaha, M. Saad, H.Y. Kanaan, and K. Al-Haddad, “Sliding-mode robot control with exponential reaching law”, IEEE Trans. Ind. Electron. 58(2), 600‒610 (2010).
  24.  Y. Liu, Z. Wang, L. Xiong, J. Wang, X. Jiang, G. Bai, R. Li, S. Liu, “DFIG wind turbine sliding mode control with exponential reaching law under variable wind speed”, Int. J. Electr. Power Energy Syst. 96, 253‒260 (2018).
  25.  Z. Lan, L. Li, C. Deng, Y. Zhang, W. Yu, and P. Wong, “A novel stator current observer for fault tolerant control of stator current sensor in DFIG”, in 2018 IEEE Energy Conversion Congress and Exposition (ECCE), 2018, pp. 790‒797.

Date

26.05.2021

Type

Article

Identifier

DOI: 10.24425/bpasts.2021.137389

Source

Bulletin of the Polish Academy of Sciences: Technical Sciences; Early Access; e137389
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