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A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection
Capacitive equipment refers to its insulation design using the principle of capacitance of electrical equipment, mainly by a variety of different capacitive components in series. Most of the equipment in the substation is capacitive equipment. Once an insulation failure occurs, it will lead to extre...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534316/ https://www.ncbi.nlm.nih.gov/pubmed/37765784 http://dx.doi.org/10.3390/s23187727 |
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author | Chen, Guojin Zhu, Yucheng Meng, Zihao Fang, Weixing Xie, Wei Xu, Ming Li, Wenxin |
author_facet | Chen, Guojin Zhu, Yucheng Meng, Zihao Fang, Weixing Xie, Wei Xu, Ming Li, Wenxin |
author_sort | Chen, Guojin |
collection | PubMed |
description | Capacitive equipment refers to its insulation design using the principle of capacitance of electrical equipment, mainly by a variety of different capacitive components in series. Most of the equipment in the substation is capacitive equipment. Once an insulation failure occurs, it will lead to extremely serious consequences. Monitoring grid overvoltage and insulation degradation of capacitive equipment is an effective means to ensure the stable operation of the power system. Therefore, in order to enhance the health management of capacitive equipment, including transformers, bushings, and current transformers, and to mitigate the risk of severe failures, it is imperative to conduct broad-spectrum frequency-domain online monitoring of overvoltages, dielectric losses, and partial discharge. However, the current monitoring work requires the utilization of multiple detection apparatuses. Aiming at the disadvantage that the existing inspection is not well integrated and requires a combination of multiple devices. This paper proposes a smart grid overvoltage identification system that utilizes partial discharge (PD) signals in correlation with dielectric loss detection. The system achieves synchronous detection of dielectric loss and high-frequency partial discharge by synchronously and in real-time acquiring four current signals from the power grid, enhancing the integration level of the hardware system. |
format | Online Article Text |
id | pubmed-10534316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105343162023-09-29 A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection Chen, Guojin Zhu, Yucheng Meng, Zihao Fang, Weixing Xie, Wei Xu, Ming Li, Wenxin Sensors (Basel) Article Capacitive equipment refers to its insulation design using the principle of capacitance of electrical equipment, mainly by a variety of different capacitive components in series. Most of the equipment in the substation is capacitive equipment. Once an insulation failure occurs, it will lead to extremely serious consequences. Monitoring grid overvoltage and insulation degradation of capacitive equipment is an effective means to ensure the stable operation of the power system. Therefore, in order to enhance the health management of capacitive equipment, including transformers, bushings, and current transformers, and to mitigate the risk of severe failures, it is imperative to conduct broad-spectrum frequency-domain online monitoring of overvoltages, dielectric losses, and partial discharge. However, the current monitoring work requires the utilization of multiple detection apparatuses. Aiming at the disadvantage that the existing inspection is not well integrated and requires a combination of multiple devices. This paper proposes a smart grid overvoltage identification system that utilizes partial discharge (PD) signals in correlation with dielectric loss detection. The system achieves synchronous detection of dielectric loss and high-frequency partial discharge by synchronously and in real-time acquiring four current signals from the power grid, enhancing the integration level of the hardware system. MDPI 2023-09-07 /pmc/articles/PMC10534316/ /pubmed/37765784 http://dx.doi.org/10.3390/s23187727 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Guojin Zhu, Yucheng Meng, Zihao Fang, Weixing Xie, Wei Xu, Ming Li, Wenxin A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection |
title | A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection |
title_full | A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection |
title_fullStr | A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection |
title_full_unstemmed | A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection |
title_short | A Smart Grid Overvoltage Identification System Associated with Partial Discharge Signal and Dielectric Loss Detection |
title_sort | smart grid overvoltage identification system associated with partial discharge signal and dielectric loss detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534316/ https://www.ncbi.nlm.nih.gov/pubmed/37765784 http://dx.doi.org/10.3390/s23187727 |
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