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A power flow based model for the analysis of vulnerability in power networks

Author

Listed:
  • Wang, Zhuoyang
  • Chen, Guo
  • Hill, David J.
  • Dong, Zhao Yang

Abstract

An innovative model which considers power flow, one of the most important characteristics in a power system, is proposed for the analysis of power grid vulnerability. Moreover, based on the complex network theory and the Max-Flow theorem, a new vulnerability index is presented to identify the vulnerable lines in a power grid. In addition, comparative simulations between the power flow based model and existing models are investigated on the IEEE 118-bus system. The simulation results demonstrate that the proposed model and the index are more effective in power grid vulnerability analysis.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:460:y:2016:i:c:p:105-115
    DOI: 10.1016/j.physa.2016.05.001
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    References listed on IDEAS

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    5. 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.
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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. Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.
    3. 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.
    4. Chen, Chong & Zhou, Xuan & Li, Zhuo & He, Zhiheng & Li, Zhengtian & Lin, Xiangning, 2018. "Novel complex network model and its application in identifying critical components of power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 316-329.
    5. Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi, 2018. "A systematic framework of vulnerability analysis of a natural gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 79-91.
    6. Xinglong Wang & Shangfei Miao & Junqing Tang, 2020. "Vulnerability and Resilience Analysis of the Air Traffic Control Sector Network in China," Sustainability, MDPI, vol. 12(9), pages 1-18, May.
    7. Tianhua Li & Yanchao Du & Yongbo Yuan, 2019. "Use of Variable Fuzzy Clustering to Quantify the Vulnerability of a Power Grid to Earthquake Damage," Sustainability, MDPI, vol. 11(20), pages 1-17, October.
    8. Wang, Zhuoyang & Chen, Guo & Liu, Long & Hill, David J., 2020. "Cascading risk assessment in power-communication interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    9. Wang, WuChang & Zhang, Yi & Li, YuXing & Hu, Qihui & Liu, Chengsong & Liu, Cuiwei, 2022. "Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).

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