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An improved framework for power grid vulnerability analysis considering critical system features

Author

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  • Dai, YuanYu
  • Chen, Guo
  • Dong, ZhaoYang
  • Xue, YuSheng
  • Hill, David J.
  • Zhao, Yuan

Abstract

In recent years the rapid development of complex network theory has provided a new angle on the vulnerability analysis of a power grid. However, current analysis models are usually general ones that may ignore some specific features of power systems. In order to address the issue, this paper proposes an improved framework for the vulnerability analysis of power grids. Firstly, the traditional topology based graph model is improved by depicting a power grid as a weighted graph based on the reactance matrix. Secondly, the concept of load is redefined by using power angle information. Thirdly, the power flow constraints are adopted instead of the shortest path based flow scheme. Based on the proposed framework, an improved dynamic analysis model is developed. In addition, numerical simulations for both a general traditional model and the proposed model are investigated based on the IEEE 118-bus system respectively. The comparison demonstrates that the improved model is more effective and efficient for the vulnerability analysis of a power grid.

Suggested Citation

  • Dai, YuanYu & Chen, Guo & Dong, ZhaoYang & Xue, YuSheng & Hill, David J. & Zhao, Yuan, 2014. "An improved framework for power grid vulnerability analysis considering critical system features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 405-415.
    • Handle: RePEc:eee:phsmap:v:395:y:2014:i:c:p:405-415
    DOI: 10.1016/j.physa.2013.10.029
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. Fauzan Hanif Jufri & Jun-Sung Kim & Jaesung Jung, 2017. "Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event," Energies, MDPI, vol. 10(11), pages 1-17, November.
    4. Guo, Wenzhang & Wang, Hao & Wu, Zhengping, 2018. "Robustness analysis of complex networks with power decentralization strategy via flow-sensitive centrality against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 186-199.
    5. Augutis, Juozas & Jokšas, Benas & Krikštolaitis, Ričardas & Urbonas, Rolandas, 2016. "The assessment technology of energy critical infrastructure," Applied Energy, Elsevier, vol. 162(C), pages 1494-1504.
    6. Guo, Hengdao & Zheng, Ciyan & Iu, Herbert Ho-Ching & Fernando, Tyrone, 2017. "A critical review of cascading failure analysis and modeling of power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 9-22.
    7. Carlo Bianca, 2022. "On the Modeling of Energy-Multisource Networks by the Thermostatted Kinetic Theory Approach: A Review with Research Perspectives," Energies, MDPI, vol. 15(21), pages 1-22, October.
    8. Xue, Fei & Bompard, Ettore & Huang, Tao & Jiang, Lin & Lu, Shaofeng & Zhu, Huaiying, 2017. "Interrelation of structure and operational states in cascading failure of overloading lines in power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 728-740.
    9. Wang, Xingyuan & Cao, Jianye & Li, Rui & Zhao, Tianfang, 2017. "A preferential attachment strategy for connectivity link addition strategy in improving the robustness of interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 412-422.
    10. Ji, Xingpei & Wang, Bo & Liu, Dichen & Chen, Guo & Tang, Fei & Wei, Daqian & Tu, Lian, 2016. "Improving interdependent networks robustness by adding connectivity links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 9-19.
    11. Fan, Wenli & Huang, Shaowei & Mei, Shengwei, 2016. "Invulnerability of power grids based on maximum flow theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 977-985.

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