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author:

Miao, Xiren (Miao, Xiren.) [1] (Scholars:缪希仁) | Wu, Xiaomei (Wu, Xiaomei.) [2]

Indexed by:

EI Scopus PKU CSCD

Abstract:

With development of selective protection technology, the range of selective protection should be extended from power supply side to terminal side. Considering the limitations of short-circuit selective protection in low-voltage system, a concept for a multi-level system with full range selective and coordinative protection technology is propound, both system architecture and key techniques to realize above concept are expound as well. Based on a practical low-voltage experimental system, a single-phase short-circuit fault model is established, which is applied to analyze short-circuit current waveforms for full phase angle range and their early short-circuit fault detection with wavelet transform(WT). With early short-circuit detection, the extreme learning machine(ELM) is brought into research peak prediction method. The practical system simulation and experimental results verify both early detection and current peak prediction to be effective for a low-voltage short-circuit fault, which lays a theoretical foundation for a new selective protection technology. ©, 2014, Chinese Machine Press. All right reserved.

Keyword:

Electric network analysis Fault detection Forecasting Knowledge acquisition Machine learning Surge protection Timing circuits Wavelet transforms

Community:

  • [ 1 ] [Miao, Xiren]Fuzhou University, Fuzhou ; 350116, China
  • [ 2 ] [Wu, Xiaomei]Fuzhou University, Fuzhou ; 350116, China

Reprint 's Address:

  • 缪希仁

    [miao, xiren]fuzhou university, fuzhou ; 350116, china

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Source :

Transactions of China Electrotechnical Society

ISSN: 1000-6753

CN: 11-2188/TM

Year: 2014

Issue: 11

Volume: 29

Page: 177-183

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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