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Structural Vulnerability of Power Grid Under Malicious Node-Based Attacks

  • Minzhen Zheng
  • Shudong LiEmail author
  • Danna Lu
  • Wei Wang
  • Xiaobo WuEmail author
  • Dawei Zhao
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1123)

Abstract

In recent years, the collapse of power grid in many countries not only has brought great inconvenience to national life, but also caused huge economic losses. Therefore, it is particularly important to analyze the vulnerability of network structure of power grid. In this paper, US power grid with 4941 nodes and 6594 edges is taken as examples. The network is attacked by deleting some percent nodes according to degree, k-shell value, betweenness centrality, and clustering coefficient, apparently. The largest connected component G, efficiency E, and average distance L are analyzed for measuring vulnerability of US power grid. The simulation results show that, in view of the largest connected component G and efficiency E, Betweenness Centrality-based attack is most destructive to the network structure than other attacks, and the attack based on Aggregation coefficient is the least destructive.

Keywords

Complex networks US power grid Vulnerability Largest connected component Robustness 

Notes

Acknowledgement

This research was funded by NSFC (No. 61672020, U1803263, U1636215, 61702309), (No. 18-163-15-ZD-002-003-01), National Key Research and Development Program of China (No. 2019QY1406), Key R&D Program of Guangdong Province (No. 2019B010136003, 2019B010137004), Project of Shandong Province Higher Educational Science and Technology Program (No. J16LN61), and the National Key research and Development Plan (No. 2018YFB1800701, No. 2018YFB0803504, and No. 2018YEB1004003).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Economics and StatisticsGuangzhou UniversityGuangzhouChina
  2. 2.Cyberspace Institute of Advance TechnologyGuangzhou UniversityGuangzhouChina
  3. 3.School of Computer Science and Cyber EngineeringGuangzhou UniversityGuangzhouChina
  4. 4.Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences)JinanChina

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