Cable degradation discharge point location method based on transient zero sequence alarm and acoustic environmental data

By optimizing the automation configuration of medium-voltage distribution lines, capturing the initial signals of cable insulation hidden danger, combining the real case data of 6 years of distribution network insulation faults and hidden danger in a city of Zhejiang, summarizing the waveform law and progressive signal characteristics in the process of insulation hidden danger deterioration, a set of real-time monitoring method based on the analysis of big data of the medium-voltage distribution line cable insulation deterioration of the corona hidden danger has been developed. The method is based on the master station to realize localization, instead of periodic on-site equipment charged detection, has been verified on-site and found discharge traces cable head in advance. This method utilizes distribution automation and dispatch automation configurations to capture the instantaneous zero-sequence overcurrent signals corresponding to insulation degradation discharges, waveform characteristics, acoustic mutations, and environmental information as input. A quantitative risk algorithm consisting of eight analysis dimensions such as zero-sequence spike characteristics, number of spikes, and synchronization of acoustic ripple and spike timing is used. Three optional computational media, including master station, enhanced DTU, and DTU external component, are used to give hidden risk localization. The two methods, local discharge detection robot and manual detection, are used to confirm the site and then carry out out outage maintenance to prevent the further expansion of hidden dangers. The method relies on the distribution automation of existing protection devices and master station configuration to assist a small number of sensors and edge computing devices to realize, through the protection device uninterrupted monitoring instead of manual periodic local discharge detection. It solves the problems of high cost of periodic testing, unavoidable accidents caused by continuous insulation degradation in the interval of testing cycle, hidden location of some cables and blind area of testing, and effectively improves the reliability of power supply.

Authors

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-15
DOI
https://doi.org/10.61091/jcmcc127a-067
Primary Topic
High voltage insulation and dielectric phenomena
Type
article
Field-Weighted Citation Impact
0.00
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article

Cable degradation discharge point location method based on transient zero sequence alarm and acoustic environmental data

Kaifeng Lin, Di Huang, Bo Zhang, Qing Zheng et al.
Journal of Combinatorial Mathematics and Combinatorial Computing
High voltage insulation and dielectric phenomena
article

Cable degradation discharge point location method based on transient zero sequence alarm and acoustic environmental data

Kaifeng Lin, Di Huang, Bo Zhang, Qing Zheng, Weiyan Zheng, Yan He
article en

Abstract

By optimizing the automation configuration of medium-voltage distribution lines, capturing the initial signals of cable insulation hidden danger, combining the real case data of 6 years of distribution network insulation faults and hidden danger in a city of Zhejiang, summarizing the waveform law and progressive signal characteristics in the process of insulation hidden danger deterioration, a set of real-time monitoring method based on the analysis of big data of the medium-voltage distribution line cable insulation deterioration of the corona hidden danger has been developed. The method is based on the master station to realize localization, instead of periodic on-site equipment charged detection, has been verified on-site and found discharge traces cable head in advance. This method utilizes distribution automation and dispatch automation configurations to capture the instantaneous zero-sequence overcurrent signals corresponding to insulation degradation discharges, waveform characteristics, acoustic mutations, and environmental information as input. A quantitative risk algorithm consisting of eight analysis dimensions such as zero-sequence spike characteristics, number of spikes, and synchronization of acoustic ripple and spike timing is used. Three optional computational media, including master station, enhanced DTU, and DTU external component, are used to give hidden risk localization. The two methods, local discharge detection robot and manual detection, are used to confirm the site and then carry out out outage maintenance to prevent the further expansion of hidden dangers. The method relies on the distribution automation of existing protection devices and master station configuration to assist a small number of sensors and edge computing devices to realize, through the protection device uninterrupted monitoring instead of manual periodic local discharge detection. It solves the problems of high cost of periodic testing, unavoidable accidents caused by continuous insulation degradation in the interval of testing cycle, hidden location of some cables and blind area of testing, and effectively improves the reliability of power supply.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Openalex Percentile: Top 95%
High voltage insulation and dielectric phenomena
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