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.
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References
Xin, L., Dongmei, J., Guoquan, Y.: The method in researching the vulnerability of the internet and the problems existing in it. Software 1(1) (2012)
Nicholson, C.D., Barker, K., Ramirez, M.J.E.: Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning. Reliab. Eng. Syst. Saf. 145, 62–73 (2016)
Huan, P., Rong, G., Gangdun, H.: Analysis and assessment of a realistic power grid’s dynamic structure vulnerability. Smart Grid 7(5), 392–401 (2017)
Hong, L., Ouyang, M., Peeta, S., et al.: Vulnerability assessment and mitigation for the Chinese railway system under floods. Reliab. Eng. Syst. Saf. 137, 58–68 (2015)
Minghui, X.: The Vulnerability Analysis of Urban Complementary Teansit Network under Spatially Localized Failures, Huazhong University of Science (2018)
Skelton, R.P., Anderegg, L., Prahlad, P.: No local adaptation in leaf or stem xylem vulnerability to embolism, but consistent vulnerability segmentation in a North American oak. New Phytologist 223(3), 1296–1306 (2019)
Hwang, T.S., Park, S.Y.: A seamless control strategy of a distributed generation inverter for the critical load safety under strict grid disturbances. IEEE Trans. Power Electron. 28(10), 4780–4790 (2013)
Atanov, I.V., Khorol’Skii, V.Y., Ershov, A.B., et al.: Formalization of the process of directional composition of structures of autonomous power-supply systems during design. Russ. Electr. Eng. 88(8), 475–479 (2017)
Bahmani-Firouzi, B., Azizipanah-Abarghooee, R.: Optimal sizing of battery energy storage for micro-grid operation management using a new improved bat algorithm. Int. J. Electr. Power Energy Syst. 56(3), 42–54 (2014)
Gini, F., Luise, M., Reggiannini, R.: Cramer-Rao bounds in the parametric estimation of fading radiotransmission channels. IEEE Trans. Commun. 46(10), 1390–1398 (1998)
Umberger, A.: Distributed Generation: How Localized Energy Production Reduces Vulnerability to Outages and Environmental Damage in the Wake of Climate Change. Golden Gate U.envtl.l.j (2012)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393, 440–442 (1998)
Dan, L.: Overview of research on grid vulnerability based on complex network theory. Heilongjiang Sci. Technol. Inf. 36 (2016)
Lixiong, X., Junyong, L., Yang, L., Zhanxin, Y., Li, Z., Yang, W.: Structural Characteristics Investigation of Electric Power, Transmission Networks (S2) (2014)
Motter, A.E., Lai, Y.C.: Cascade-based attacks on complex networks. Phys. Rev. E 66(6), 065102 (2002)
Jing, G., Wang, D.R.: The vulnerability analysis on power communication networks based on complex network theory. Power Syst. Commun. 30(9), 6–10 (2009)
Li, S., Wu, X., Li, A., Zhou, B., Tian, Z., Zhao, D.: Structural vulnerability of complex networks under multiple edge-based attacks. In: 2018 IEEE 3rd International Conference on Data Science in Cyberspace (IEEE DSC 2018), pp. 405–409 (2018)
Crucitti, P., Latora, V., Marchiori, M.: A topological analysis of the Italian electric power grid. Physica A 338, 92–97 (2004)
Zhao, D., Li, L., Li, S., Huo, Y., Yang, Y.: Identifying influential spreaders in interconnected networks. Physica Scripta 89(1) (2014). 0031-8949
Li, S., Li, L., Jia, Y., Liu, X., Yang, Y.: Identifying vulnerable nodes of complex networks in cascading failures induced by node-based attacks. Math. Probl. Eng. (2013). 938398
Wei, Z., Liu, J., Zhu, G., et al.: A new integrative vulnerability evaluation model to power grid based on running state and structure. Autom. Electr. Power Syst. 33(8), 11–15 (2009)
Li, S., Li, L., Yang, Y., Luo, Q.: Revealing the process of edge-based-attack cascading failures. Nonlinear Dyn. 69(3), 837–845 (2012)
Tian, Z., Su, S., Shi, W., Du, X., Guizani, M., Yu, X.: A data-driven method for future internet route decision modeling. Future Gener. Comput. Syst. 95, 212–220 (2019)
Anji, M., Yu, J., Guo, Z.: Electric power grid structural vulnerability assessment. In: Power Engineering Society General Meeting. IEEE (2006)
Zhao, D., Li, L., Peng, H., Luo, Q., Yang, Y.: Multiple routes transmitted epidemics on multiplex networks. Phys. Lett. A 378, 770–776 (2014)
Coppo, M., Pelacchi, P., Pilo, F., et al.: The Italian smart grid pilot projects: selection and assessment of the test beds for the regulation of smart electricity distribution. Electr. Power Syst. Res. 120, 136–149 (2015)
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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Zheng, M., Li, S., Lu, D., Wang, W., Wu, X., Zhao, D. (2019). Structural Vulnerability of Power Grid Under Malicious Node-Based Attacks. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_36
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