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Arc Modeling and Kurtosis Detection of Fault with Arc in Power Distribution Networksopen access

Authors
Hyun, Seung-YoonHong, Ji-SongYun, Sang-YunKim, Chang-HwanLee, Youngwoo
Issue Date
Mar-2022
Publisher
MDPI
Keywords
Arc modeling; Electric arc; Fault; Kurtosis detection
Citation
Applied Sciences-basel, v.12, no.6, pp 1 - 17
Pages
17
Indexed
SCIE
SCOPUS
Journal Title
Applied Sciences-basel
Volume
12
Number
6
Start Page
1
End Page
17
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115271
DOI
10.3390/app12062777
ISSN
2076-3417
Abstract
In power distribution networks, there are many practical fault cases such as high impedance faults, faults and so on. Especially when the faults with electric arc persist, it is dangerous for human beings and circumstances. Nevertheless, it is difficult to classify faults due to various customer load conditions or the presence of distributed energy resources. In this paper, we propose a new mathematical arc model based on experimental event data. For implementing the arc phenomenon, wet gravel was used as a contact conductor after the fault. The experimental results validate the arc transient model. Then, the simulations were performed to verify the success of arc modeling using Kizilcay’s arc model as a comparison method. Finally, we developed a fault detector using the kurtosis detection method, and power system simulations were conducted to evaluate fault detection performance using Matlab/Simulink. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles

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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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