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

Wang, Minzhen, Li, Cheng, Wang, Xinheng ORCID: 0000-0001-8771-8901, Piao, Zheyong, Yang, Yongsheng, Dai, Wentao and Zhang, Qi (2023) Research on Comprehensive Evaluation and Early Warning of Transmission Lines' Operation Status Based on Dynamic Cloud Computing. SENSORS, 23 (3). 1469-.

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Official URL: http://dx.doi.org/10.3390/s23031469

Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	electricity transmission line, exponential scaling method, comprehensive analysis, correlation algorithm, status assessment, cloud computing
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	24 Apr 2023 14:31
Last Modified:	24 Apr 2023 14:32
DOI:	10.3390/s23031469
Open Access URL:	https://doi.org/10.3390/s23031469
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3169929