A remote barrier localization method for intelligent substations using deep belief networks
Year: 2024
Type: article
Abstract: In the remote operation of intelligent substations， failures often occur due to device or network malfunctions， or inconsistencies in information， consequently hampering operation and maintenance efficiency. To address this， the paper proposes a remote barrier localization method for intelligent substations using deep belief networks （DBNs）. Firstly， the whole process of remote control in an intelligent substation is decomposed to categorize the failures into three main types. Then， DBN-Softmax classifiers are introduced to extract features and train the classification model respectively， building a remote barrier localization model. Finally， failure types and telemetry information are used to precisely locate the faults. Engineering examples have shown effective validation of the method， including its merits of short computation time and high localization accuracy.
Authors: JI Rongrong, SHENG Haihua, SHI Jianli, LI Hai, ZHANG Xiaorong
Institution: State Grid Zhejiang Electric Power Company (China)
Language: English
Topic: Smart Grid and Power Systems
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6888498533
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