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Research on vulnerability assessment method of electric power network based on graph neural
ID：72 View Protection：ATTENDEE Updated Time：2023-11-20 13:45:39 Hits：1000 Oral Presentation

Start Time：2023-12-09 15:30（Asia/Shanghai）

Duration：15min

Session：S7 Power system protection and control » S7Power system protection and control

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Abstract
This paper proposes a vulnerability assessment method for power network based on graph neural network using complex network theory and graph neural network model. First, the eigenvector centrality (EC) in complex network theory is chosen as the measure of power system vulnerability. Second, an unsupervised power network vulnerability assessment model based on graph neural networks is established based on power system topological parameters and operational data. Finally, the learning effect and computational time efficiency of the model are explored, and the key nodes in the power network are identified.
 
Keywords
Graph neural network; Complex network; Eigenvector Centrality;
Speaker
Zijian Wan
student Southwest Jiaotong University

Submission Author
Zijian Wan Southwest Jiaotong University
Xu Liu Southwest Jiaotong University
Yeqing Zhang Southwest Jiaotong University
Yan Wang Southwest Jiaotong University
Yida Zeng Southwest Jiaotong University
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Important Date

  • Conference Date

    Dec 08

    2023

    to

    Dec 10

    2023

  • Nov 01 2023

    Draft paper submission deadline

  • Dec 10 2023

    Registration deadline

Sponsored By
IEEE IAS
Organized By
Southwest Jiaotong University (SWJTU)
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