Research on Remote Monitoring and Fault Diagnosis System of Substation

Remote fault warning and diagnosis for substations are important means to ensure safe operation of substations and facilitate transition towards smart grids. Currently, some substations are located in remote areas and operate unmanned which leads to untimely automatic analysis of the monitoring system and an imperfect fault warning and diagnosis system. This paper, based on the characteristics of a pilot substation, designs a remote monitoring system for substations, which can achieve remote fault warning and diagnosis. The system adopts a wide-angle, uninterrupted sampling strategy and information synchronization to ensure collaborative sharing of monitoring data; state trend analysis, indicator evaluation and intelligent inspection are used to achieve remote fault warning, and related operating conditions are utilized to extract fault features for remote fault diagnosis.

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Publication Details

Published
2025-04-15
DOI
https://doi.org/10.1109/acpee64358.2025.11040456
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
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Research on Remote Monitoring and Fault Diagnosis System of Substation

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Research on Remote Monitoring and Fault Diagnosis System of Substation

Hui Nan Guo, Yu Tai, Jie Jiang, Leyao Cong, Sijia Li, Benke Hao
article en

Abstract

Remote fault warning and diagnosis for substations are important means to ensure safe operation of substations and facilitate transition towards smart grids. Currently, some substations are located in remote areas and operate unmanned which leads to untimely automatic analysis of the monitoring system and an imperfect fault warning and diagnosis system. This paper, based on the characteristics of a pilot substation, designs a remote monitoring system for substations, which can achieve remote fault warning and diagnosis. The system adopts a wide-angle, uninterrupted sampling strategy and information synchronization to ensure collaborative sharing of monitoring data; state trend analysis, indicator evaluation and intelligent inspection are used to achieve remote fault warning, and related operating conditions are utilized to extract fault features for remote fault diagnosis.

Wuxi Wind Power Design and Research Institute (CN)
Climate action
Openalex Percentile: Top 87%
Smart Grid and Power Systems
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