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Recent Advances in Electrical & Electronic Engineering

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ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

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Research Article

Single Phase to Ground Fault Location of Distribution Network Based on Combined-GAT

Author(s): Keyan Liu, Wanxing Sheng and Xiaoyu Yang*

Volume 15, Issue 6, 2022

Published on: 25 August, 2022

Page: [465 - 474] Pages: 10

DOI: 10.2174/2352096515666220624160925

Price: $65

Abstract

Background: At present, small current grounding systems are widely used in distribution network of China. Affected by the complex topology of the distribution network and other factors, single-phase grounding fault has become the most prone type of electrical short-circuit fault in China.

Objective: Considering that the traditional fault selection and location methods are difficult to mine the effective information of fault quantity, a new method is proposed in this paper to achieve accurate fault location on the basis of ensuring timeliness.

Methods: In this paper, the physical topology of the distribution network is regarded as a graph, the overhead lines and cables of the main equipment are regarded as the nodes in the graph, and the problem of fault node location is corresponding to the task of graph attention classification. Considering the average degree and homogeneity of the given network topology, an improved graph attention network is built to realize fault node location.

Results: This paper verifies the effectiveness of the proposed model for fault location through simulation in PSCADA. In addition, the applicability of the proposed model in the case of changes in the distribution network structure is verified. It verifies that the proposed method achieves high positioning accuracy.

Conclusion: The proposed model can locate the fault line quickly and accurately when a singlephase grounding fault occurs, which is of great significance to improve the stability of the power system and give full play to the advantages of a small current grounding system.

Keywords: Distribution Network, Single phase to ground, Fault location, Graph Learning, PMU, Smart Grid

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Graphical Abstract

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