Dynamic reinforcement identification method for weak links in distribution network based on deep graph neural network

Aiming at the insufficient recognition accuracy of weak points in the distribution network, a dynamic enhancement recognition method for weak nodes in the distribution network based on a deep graph neural network is proposed. It integrates the complex topology of the distribution network, automatica...

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Bibliographic Details
Published in:Journal of physics. Conference series 2024-12, Vol.2914 (1), p.012025
Main Authors: Jin, Qiang, Zhang, Yu, Li, Hongjun, Shi, Jinyue, Zhao, Yuchen
Format: Article
Language:English
Subjects:
Graph neural networks
Identification methods
Systems stability
Topology
Weak nodes
Online Access:Get full text
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Summary:Aiming at the insufficient recognition accuracy of weak points in the distribution network, a dynamic enhancement recognition method for weak nodes in the distribution network based on a deep graph neural network is proposed. It integrates the complex topology of the distribution network, automatically extracts key features, and accurately locates and reinforces weak links in real time. The results show that the recognition accuracy and system stability are significantly improved.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2914/1/012025