Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)

Fast Identification of Short Circuit Fault Based on Average Curvature of Current Waveform

Authors
Shaogui Ai, Xiuming Hu, Yongning Huang, Hui Ni, Zhiguo Hao
Corresponding Author
Shaogui Ai
Available Online December 2017.
DOI
https://doi.org/10.2991/ecae-17.2018.5How to use a DOI?
Keywords
fault current limiter; fast identification; short circuit Current; average curvature
Abstract

Using fault current limiter (FCL) is an effective way to solve the problem that short circuit current exceeds the standard. How to quickly identify short circuit faults is one of the keys. Thus, this paper presented a fast identification method for short circuit fault based on the average curvature of current waveform. A simple fault current limiter system was built in PSCAD, and the method was studied. The results show that it is faster than using current instantaneous value or the current change rate as the criterion. In view of the situation that the average curvature may exceed when the load changes sharply. It was proposed that the average curvature and the current change rate could be used as the combination criterion, and the fault could be identified quickly and accurately too.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
Series
Advances in Engineering Research
Publication Date
December 2017
ISBN
978-94-6252-458-3
ISSN
2352-5401
DOI
https://doi.org/10.2991/ecae-17.2018.5How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Shaogui Ai
AU  - Xiuming Hu
AU  - Yongning Huang
AU  - Hui Ni
AU  - Zhiguo Hao
PY  - 2017/12
DA  - 2017/12
TI  - Fast Identification of Short Circuit Fault Based on Average Curvature of Current Waveform
BT  - Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
PB  - Atlantis Press
SP  - 23
EP  - 26
SN  - 2352-5401
UR  - https://doi.org/10.2991/ecae-17.2018.5
DO  - https://doi.org/10.2991/ecae-17.2018.5
ID  - Ai2017/12
ER  -