A Study on Risk Propagation in Power Transmission Networks Based on the SEIR Model

As the scale and complexity of modern power systems continue to grow, the risks faced by transmission networks have increasingly become a critical concern. This paper introduces the SEIR model, commonly used in epidemiology, to simulate and analyze the behavior of risk propagation within power transmission networks. By studying the risk propagation paths and infection mechanisms, this research reveals the dynamic relationships among susceptibility, exposure, infection, and recovery of nodes within the transmission network. Simulation results indicate that the propagation of risk within the transmission network is significantly influenced by the network's topology, and identifying and protecting key nodes are effective measures to control risk. Finally, several strategies for controlling risk propagation are proposed, and potential directions for future research are discussed.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/eiecs63941.2024.10800380
Primary Topic
Technology and Security Systems
Type
article
Field-Weighted Citation Impact
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article

A Study on Risk Propagation in Power Transmission Networks Based on the SEIR Model

Xiaqing Meng, Jingjing Gong, Qi Ni
Technology and Security Systems
article

A Study on Risk Propagation in Power Transmission Networks Based on the SEIR Model

Xiaqing Meng, Jingjing Gong, Qi Ni
article en

Abstract

As the scale and complexity of modern power systems continue to grow, the risks faced by transmission networks have increasingly become a critical concern. This paper introduces the SEIR model, commonly used in epidemiology, to simulate and analyze the behavior of risk propagation within power transmission networks. By studying the risk propagation paths and infection mechanisms, this research reveals the dynamic relationships among susceptibility, exposure, infection, and recovery of nodes within the transmission network. Simulation results indicate that the propagation of risk within the transmission network is significantly influenced by the network's topology, and identifying and protecting key nodes are effective measures to control risk. Finally, several strategies for controlling risk propagation are proposed, and potential directions for future research are discussed.

Affordable and clean energy
Openalex Percentile: Top 62%
Technology and Security Systems
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