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Self-Organized Criticality Identification of Power System Based on SC-GCN Network
ID：97 View Protection：ATTENDEE Updated Time：2023-11-20 13:45:42 Hits：967 Oral Presentation

Start Time：2023-12-10 11:00（Asia/Shanghai）

Duration：15min

Session：S8 AI-driven technology » S8AI-driven technology

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Abstract
In order to solve the problem that the traditional power system self-organized criticality identification method is weak in dealing with graphical data and nonlinear coupling factors, this paper proposes a power system self-organized criticality identification method based on SC-GCN neural network. First, the self-organized criticality evolution process is simulated based on the OPA model. Secondly, the feature quantities of each day, including bus features, line features and global features, are obtained according to the self-organized criticality evolution process, and the data are processed and classified as graph data. Further, a SC-GCN neural network model is obtained by adding jump connections to the traditional graph convolutional neural network to solve the gradient vanishing problem and accelerate the model convergence. Finally, the dataset is input into the SC-GCN neural network model for training and testing, and the simulation results show that compared with the traditional power system self-organized criticality identification method, the power system self-organized criticality identification method proposed in this paper can be more perfect, simple and rapid to identify the power system self-organized criticality online.
Keywords
Graph Convolutional Neural Networks; Self-Organizing Criticality; OPA Model; Jump Connections;
Speaker
Liyang Liu
researcher State Grid Sichuan Economic Research Institute

Submission Author
Liyang Liu State Grid Sichuan Economic Research Institute
Yuqi Han State Grid Sichuan Economic Research Institute;
Shengyong Ye State Grid Sichuan Economic Research Institute
Chuan Long State Grid Sichuan Economic Research Institute;
Zixuan Liu Southwest Jiaotong University
Xuna Liu State Grid Sichuan Economic Research Institute;
Ting Li State Grid Sichuan Economic Research Institute;
Xinting Yang State Grid Sichuan Economic Research Institute;
Da Li State Grid Sichuan Economic Research Institute;
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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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