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2020 | OriginalPaper | Chapter

Design of Fault Location Scheme for Distribution Network Based on Edge Computing

Authors : Minyu Li, Shuhua He, Xiangwei Chen, Yifan Wang, Jiafang Huang

Published in: Proceedings of PURPLE MOUNTAIN FORUM 2019-International Forum on Smart Grid Protection and Control

Publisher: Springer Nature Singapore

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Abstract

With the implementation of the “three-type two-network, world-class” strategy, the requirements for building a ubiquitous power Internet are proposed. In order to further improve the accuracy of fault location in distribution network, this paper designed a fault location scheme for distribution network based on edge computing. Through the information technology and intelligent technology such as edge computing, artificial intelligence, mobile internet, etc., the power distribution terminal completed the fault diagnosis of the distribution network “on the spot”. The design scheme divided the distribution line into several responsibility segments. Each responsibility segment was composed of one distribution terminal or feeder terminal as the collection terminal. The remaining distribution terminals in the responsibility segment served as the collection terminal and accepted the management control of the collection device. After a short-circuit fault or single-phase ground fault occurred in the distribution network, the aggregation terminal issued a control command, requesting the collection terminal to feed back the short-circuit fault alarm signal or the fault current waveform data, and analyzed the waveform data through the artificial intelligence algorithm to achieve fault location. The feasibility of the fault diagnosis decision bit was verified by the field application of the oscillating fault indicator. The design scheme could reduce the resource occupation of distribution automation station fault processing and improve the fault location efficiency of distribution automation station.

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Metadata
Title
Design of Fault Location Scheme for Distribution Network Based on Edge Computing
Authors
Minyu Li
Shuhua He
Xiangwei Chen
Yifan Wang
Jiafang Huang
Copyright Year
2020
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-13-9779-0_63