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Research on a comprehensive detection method for arc high resistance grounding faults in distribution networks

Published: 31 July 2024 Publication History

Abstract

In order to detect high resistance grounding faults, an effective zero crossing phase detection algorithm is proposed based on the nonlinear arc zero crossing distortion phenomenon during arc high resistance grounding faults, which can effectively deal with complex working conditions such as high harmonic content of fault zero sequence components and sudden changes in amplitude and phase frequency. The algorithm is applied to identify the arc characteristics of high resistance grounding faults. In addition, to ensure the effectiveness and sensitivity of fault protection startup, the traditional zero sequence voltage fault startup method was improved, and a fault startup method based on mutation energy was proposed and verified. These two methods are combined to form a comprehensive detection method for high resistance grounding faults, which shortens the starting time of high resistance fault criteria and improves the accuracy of line selection.

References

[1]
IEEE Guide for the Application of Neutral Grounding in Electrical Utility System, Part IV-Distribution, IEEE Std. C62. 92.4-1991, 1992.
[2]
Tengdin J, Westfall R, Stephan K. High impedance fault detection technology[R]. Report of PSRC Working Group D15, 1996.
[3]
Ghaderi A, Mohammadpour H A, Ginn H L, High-impedance fault detection in the distribution network using the time-frequency-based algorithm[J]. IEEE Transactions on Power Delivery, 2015, 30(3): 1260-1268.
[4]
Chen J, Phung T, Blackburn T, Detection of high impedance faults using current transformers for sensing and identification based on features extracted using wavelet transform[J]. IET Generation, Transmission & Distribution, 2016, 10(12): 2990-2998.
[5]
Sedighi A R, Haghifam M, Malik O, High impedance fault detection based on wavelet transform and statistical pattern recognition [J]. IEEE Transactions on Power Delivery, 2005, 20(4): 2414-2421.
[6]
Lazkano A, Ruiz J, Aramendi E, Evaluation of a new proposal for arcing fault detection method based on wavelet packet analysis [C]. IEEE Power Engineering Society Summer Meeting, 2001, 3: 1328-1333.
[7]
Soheili A, Sadeh J. Evidential reasoning based approach to high impedance fault detection in power distribution systems [J]. IET Generation, Transmission & Distribution, 2017, 11(5): 1325-1336.
[8]
Sarlak M, Shahrtash S M. High-impedance faulted branch identification using magnetic-field signature analysis[J]. IEEE Transactions on Power Delivery, 2013, 28(1): 67-74.
[9]
Costa F B, Souza B A, Brito N S D, Real-time detection of transients induced by high-impedance faults based on the boundary wavelet transform [J]. IEEE Transactions on Power Delivery, 2015, 51(6): 5312-5323.
[10]
Santos W C, Lopes F V, Brito N S D, High-impedance fault identification on distribution networks [J]. IEEE Transactions on Power Delivery, 2017, 32(1): 23-32.
[11]
Xue Y D, Chen X R, Song H M, Resonance analysis and faulty feeder identification of high-impedance faults in a resonant grounding system [J]. IEEE Transactions on Power Delivery, 2017, 32(3): 1545-1555.
[12]
Elkalashy NI, Lehtonen M, Darwish HA. Modeling and experimental verification of high impedance arcing fault in medium voltage networks [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2007, 14(2): 375-383.

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    PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
    January 2024
    969 pages
    ISBN:9798400716638
    DOI:10.1145/3674225
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 31 July 2024

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