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Author:

Wu, Hong (Wu, Hong.) | Wang, Yue (Wang, Yue.) | Liu, Yi (Liu, Yi.) | Li, Runtian (Li, Runtian.) | Li, Pengkun (Li, Pengkun.) | Xue, Yinglin (Xue, Yinglin.)

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Abstract:

The MMC topology is composed of large quantum series-connected submodules (SMs). The fault of any SM will affect the normal operation of MMC and may even lead to further cascading faults, thus reliability is one of its important issues. The empirical threshold in the existing literatures is difficult to generalize. To cope with this problem, this article proposes a threshold adaptive diagnosis strategy. The fault is detected and located by judging the generalized capacitor voltage unbalance degree of the SMs whether exceed the threshold. By analyzing the diagnostic threshold of MMC under different operating powers, the proposed strategy can accurately and quickly diagnose SMs open-circuit fault at different power points. Experimental results in a hardware-in-the-loop (HIL) platform verify the effectiveness of the proposed strategy. © 2022 IEEE.

Keyword:

Computer circuits Failure analysis Fault detection Power converters Timing circuits

Author Community:

  • [ 1 ] [Wu, Hong]Xi'an Jiaotong University, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an, China
  • [ 2 ] [Wang, Yue]Xi'an Jiaotong University, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an, China
  • [ 3 ] [Liu, Yi]Xi'an Jiaotong University, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an, China
  • [ 4 ] [Li, Runtian]Xi'an Jiaotong University, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an, China
  • [ 5 ] [Li, Pengkun]Xi'an Jiaotong University, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an, China
  • [ 6 ] [Xue, Yinglin]State Power Economic Research Institute, State Grid, Beijing, China

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Year: 2022

Page: 1206-1210

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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