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Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing

The current methods for evaluating the operating condition of electricity transmission lines (ETLs) and providing early warning have several problems, such as the low correlation of data, ignoring the influence of seasonal factors, and strong subjectivity. This paper analyses the sensitive factors t...

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Autores principales: Wang, Minzhen, Li, Cheng, Wang, Xinheng, Piao, Zheyong, Yang, Yongsheng, Dai, Wentao, Zhang, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919575/
https://www.ncbi.nlm.nih.gov/pubmed/36772506
http://dx.doi.org/10.3390/s23031469
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author Wang, Minzhen
Li, Cheng
Wang, Xinheng
Piao, Zheyong
Yang, Yongsheng
Dai, Wentao
Zhang, Qi
author_facet Wang, Minzhen
Li, Cheng
Wang, Xinheng
Piao, Zheyong
Yang, Yongsheng
Dai, Wentao
Zhang, Qi
author_sort Wang, Minzhen
collection PubMed
description The current methods for evaluating the operating condition of electricity transmission lines (ETLs) and providing early warning have several problems, such as the low correlation of data, ignoring the influence of seasonal factors, and strong subjectivity. This paper analyses the sensitive factors that influence dynamic key evaluation indices such as grounding resistance, sag, and wire corrosion, establishes the evaluation criteria of the ETL operation state, and proposes five ETL status levels and seven principles for selecting evaluation indices. Nine grade I evaluation indices and twenty-nine grade II evaluation indices, including passageway and meteorological environments, are determined. The cloud model theory is embedded and used to propose a warning technology for the operation state of ETLs based on inspection defect parameters and the cloud model. Combined with the inspection defect parameters of a line in the Baicheng district of Jilin Province and the critical evaluation index data such as grounding resistance, sag, and wire corrosion, which are used to calculate the timeliness of the data, the solid line is evaluated. The research shows that the dynamic evaluation model is correct and that the ETL status evaluation and early warning method have reasonable practicability.
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spelling pubmed-99195752023-02-12 Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing Wang, Minzhen Li, Cheng Wang, Xinheng Piao, Zheyong Yang, Yongsheng Dai, Wentao Zhang, Qi Sensors (Basel) Article The current methods for evaluating the operating condition of electricity transmission lines (ETLs) and providing early warning have several problems, such as the low correlation of data, ignoring the influence of seasonal factors, and strong subjectivity. This paper analyses the sensitive factors that influence dynamic key evaluation indices such as grounding resistance, sag, and wire corrosion, establishes the evaluation criteria of the ETL operation state, and proposes five ETL status levels and seven principles for selecting evaluation indices. Nine grade I evaluation indices and twenty-nine grade II evaluation indices, including passageway and meteorological environments, are determined. The cloud model theory is embedded and used to propose a warning technology for the operation state of ETLs based on inspection defect parameters and the cloud model. Combined with the inspection defect parameters of a line in the Baicheng district of Jilin Province and the critical evaluation index data such as grounding resistance, sag, and wire corrosion, which are used to calculate the timeliness of the data, the solid line is evaluated. The research shows that the dynamic evaluation model is correct and that the ETL status evaluation and early warning method have reasonable practicability. MDPI 2023-01-28 /pmc/articles/PMC9919575/ /pubmed/36772506 http://dx.doi.org/10.3390/s23031469 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
Wang, Minzhen
Li, Cheng
Wang, Xinheng
Piao, Zheyong
Yang, Yongsheng
Dai, Wentao
Zhang, Qi
Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing
title Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing
title_full Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing
title_fullStr Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing
title_full_unstemmed Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing
title_short Research on Comprehensive Evaluation and Early Warning of Transmission Lines’ Operation Status Based on Dynamic Cloud Computing
title_sort research on comprehensive evaluation and early warning of transmission lines’ operation status based on dynamic cloud computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919575/
https://www.ncbi.nlm.nih.gov/pubmed/36772506
http://dx.doi.org/10.3390/s23031469
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