research-article

ETI-ECF: Edge Computing Framework for Distribution Network Electrical Topology Identification

Authors:

Jie XuAuthors Info & Claims

CSAE '20: Proceedings of the 4th International Conference on Computer Science and Application Engineering

Article No.: 66, Pages 1 - 6

https://doi.org/10.1145/3424978.3425044

Published: 20 October 2020 Publication History

Abstract

The rapid development of the Ubiquitous Power IoT has highlighted new requirements for the distribution network electrical topology identification technology. At present, with the widespread access of smart meters, the large number of terminals and data has brought huge pressure to the communication network and data processing of the main station, which has affected the work efficiency. In this paper, we propose an edge computing framework for distribution network electrical topology identification (ETI-ECF), by improving the computing capability on edge side, implement localized analysis and process of mining data. Especially, we move the topology identification process from the main station to edge devices, and reduce the computing pressure on the server cluster of the main station. This framework provides a reference for the further combination of the Ubiquitous Power Internet of Things and edge computing.

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Cited By

Lin GLiu SShi DWang XLiu S(2022)A Dual-Graph Attention-Based Approach for Identifying Distribution Network Topology2022 IEEE 10th International Conference on Computer Science and Network Technology (ICCSNT)10.1109/ICCSNT56096.2022.9972879(29-33)Online publication date: 22-Oct-2022
https://doi.org/10.1109/ICCSNT56096.2022.9972879

Index Terms

ETI-ECF: Edge Computing Framework for Distribution Network Electrical Topology Identification
1. Networks
  1. Network architectures

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cover image ACM Other conferences

CSAE '20: Proceedings of the 4th International Conference on Computer Science and Application Engineering

October 2020

1038 pages

ISBN:9781450377720

DOI:10.1145/3424978

Conference Chair:
Ali Emrouznejad,
Program Chair:
Jui-Sheng Rayson Chou

Copyright © 2020 ACM.

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Publication History

Published: 20 October 2020

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CSAE 2020

CSAE 2020: The 4th International Conference on Computer Science and Application Engineering

October 20 - 22, 2020

Sanya, China

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CSAE '20 Paper Acceptance Rate 179 of 387 submissions, 46%;

Overall Acceptance Rate 368 of 770 submissions, 48%

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Cited By

Lin GLiu SShi DWang XLiu S(2022)A Dual-Graph Attention-Based Approach for Identifying Distribution Network Topology2022 IEEE 10th International Conference on Computer Science and Network Technology (ICCSNT)10.1109/ICCSNT56096.2022.9972879(29-33)Online publication date: 22-Oct-2022
https://doi.org/10.1109/ICCSNT56096.2022.9972879

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