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An improved model for structural vulnerability analysis of power networks

Author

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  • Chen, Guo
  • Dong, Zhao Yang
  • Hill, David J.
  • Zhang, Guo Hua

Abstract

Electric power networks have been studied as a typical example of real-world complex networks. Traditional models for structural vulnerability analysis appear to be all based on physical topological structure. In this paper, we depict a typical power network as a weighted graph based on electrical topology by introducing its bus admittance matrix, which embodies the important characteristics of power networks in a much more realistic structure. Furthermore, the numerical simulation for both the traditional dynamical model and the proposed electrical topological model are investigated based on the IEEE 300 bus system respectively. The comparison demonstrates that the improved model is more precise and highly efficient for the analysis of structural vulnerability of power networks.

Suggested Citation

  • Chen, Guo & Dong, Zhao Yang & Hill, David J. & Zhang, Guo Hua, 2009. "An improved model for structural vulnerability analysis of power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4259-4266.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:19:p:4259-4266
    DOI: 10.1016/j.physa.2009.06.041
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    Citations

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    Cited by:

    1. Zohre Alipour & Mohammad Ali Saniee Monfared & Enrico Zio, 2014. "Comparing topological and reliability-based vulnerability analysis of Iran power transmission network," Journal of Risk and Reliability, , vol. 228(2), pages 139-151, April.
    2. Youba Nait Belaid & Patrick Coudray & José Sanchez-Torres & Yi-Ping Fang & Zhiguo Zeng & Anne Barros, 2021. "Resilience Quantification of Smart Distribution Networks—A Bird’s Eye View Perspective," Energies, MDPI, vol. 14(10), pages 1-29, May.
    3. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2019. "Review of major approaches to analyze vulnerability in power system," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 153-172.
    4. Fei Xue & Yingyu Xu & Huaiying Zhu & Shaofeng Lu & Tao Huang & Jinling Zhang, 2017. "Structural Evaluation for Distribution Networks with Distributed Generation Based on Complex Network," Complexity, Hindawi, vol. 2017, pages 1-10, October.
    5. Beyza, Jesus & Ruiz-Paredes, Hector F. & Garcia-Paricio, Eduardo & Yusta, Jose M., 2020. "Assessing the criticality of interdependent power and gas systems using complex networks and load flow techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    6. Nasiruzzaman, A.B.M. & Pota, H.R. & Akter, Most. Nahida, 2014. "Vulnerability of the large-scale future smart electric power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 11-24.
    7. Wang, Kai & Zhang, Bu-han & Zhang, Zhe & Yin, Xiang-gen & Wang, Bo, 2011. "An electrical betweenness approach for vulnerability assessment of power grids considering the capacity of generators and load," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4692-4701.
    8. Wang, Zhuoyang & Chen, Guo & Hill, David J. & Dong, Zhao Yang, 2016. "A power flow based model for the analysis of vulnerability in power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 105-115.
    9. Jian-Yong Wang & Zhen Tian & Xu Zhu & Naif D. Alotaibi, 2017. "Finite-Time Consensus with a Time-Varying Reference State and Switching Topology," Complexity, Hindawi, vol. 2017, pages 1-9, June.
    10. Koç, Yakup & Warnier, Martijn & Mieghem, Piet Van & Kooij, Robert E. & Brazier, Frances M.T., 2014. "The impact of the topology on cascading failures in a power grid model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 169-179.
    11. Ma, Tian-Lin & Yao, Jian-Xi & Qi, Cheng & Zhu, Hong-Lu & Sun, Yu-Shu, 2013. "Non-monotonic increase of robustness with capacity tolerance in power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5516-5524.
    12. Ziqi Wang & Jinghan He & Alexandru Nechifor & Dahai Zhang & Peter Crossley, 2017. "Identification of Critical Transmission Lines in Complex Power Networks," Energies, MDPI, vol. 10(9), pages 1-19, August.
    13. Wang, Zhuoyang & Hill, David J. & Chen, Guo & Dong, Zhao Yang, 2017. "Power system cascading risk assessment based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 532-543.
    14. Ren, Hai-Peng & Song, Jihong & Yang, Rong & Baptista, Murilo S. & Grebogi, Celso, 2016. "Cascade failure analysis of power grid using new load distribution law and node removal rule," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 239-251.
    15. Mahmoud Saleh & Yusef Esa & Ahmed Mohamed, 2018. "Applications of Complex Network Analysis in Electric Power Systems," Energies, MDPI, vol. 11(6), pages 1-16, May.
    16. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    17. Ma, Xiangyu & Zhou, Huijie & Li, Zhiyi, 2021. "On the resilience of modern power systems: A complex network perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    18. Wang, Jing & Zuo, Wangda & Rhode-Barbarigos, Landolf & Lu, Xing & Wang, Jianhui & Lin, Yanling, 2019. "Literature review on modeling and simulation of energy infrastructures from a resilience perspective," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 360-373.

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