IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v396y2014icp204-211.html
   My bibliography  Save this article

Correlation analysis of different vulnerability metrics on power grids

Author

Listed:
  • Ouyang, Min
  • Pan, Zhezhe
  • Hong, Liu
  • Zhao, Lijing

Abstract

Many scholars have used different metrics to quantify power grid vulnerability in the literature, but how correlated these metrics are is an interesting topic. This paper defines vulnerability as the performance drop of a power grid under a disruptive event, and selects six frequently used performance metrics, including efficiency (E), source–demand considered efficiency (SDE), largest component size (LCS), connectivity level (CL), clustering coefficient (CC), and power supply (PS), to respectively quantify power grid vulnerability V under different node or edge failure probabilities fp and then analyzes the correlation of these six vulnerability metrics. Taking the IEEE 300 power grid as an example, the results show that the flow-based metric VPS, which is equivalent to the important load shed metric in power engineering, has mild correlation with source–demand considered topology-based metrics VSDE and VCL, but weak correlation with other topology-based metrics VE, VLCS and VCC, which do not differentiate source–demand nodes. Similar results are also found in other types of failures, other system operation parameters and other power grids. Hence, one should be careful to use topology-based metrics to quantify the real vulnerability of power grids.

Suggested Citation

  • Ouyang, Min & Pan, Zhezhe & Hong, Liu & Zhao, Lijing, 2014. "Correlation analysis of different vulnerability metrics on power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 204-211.
  • Handle: RePEc:eee:phsmap:v:396:y:2014:i:c:p:204-211
    DOI: 10.1016/j.physa.2013.10.041
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437113010133
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2013.10.041?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo, 2004. "A topological analysis of the Italian electric power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 92-97.
    2. Chen, Guo & Dong, Zhao Yang & Hill, David J. & Zhang, Guo Hua & Hua, Ke Qian, 2010. "Attack structural vulnerability of power grids: A hybrid approach based on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 595-603.
    3. R. Kinney & P. Crucitti & R. Albert & V. Latora, 2005. "Modeling cascading failures in the North American power grid," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 46(1), pages 101-107, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Wu, Di & Ma, Feng & Javadi, Milad & Thulasiraman, Krishnaiya & Bompard, Ettore & Jiang, John N., 2017. "A study of the impacts of flow direction and electrical constraints on vulnerability assessment of power grid using electrical betweenness measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 295-309.
    3. Nicholson, Charles D. & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 62-73.
    4. Lucas Cuadra & Sancho Salcedo-Sanz & Javier Del Ser & Silvia Jiménez-Fernández & Zong Woo Geem, 2015. "A Critical Review of Robustness in Power Grids Using Complex Networks Concepts," Energies, MDPI, vol. 8(9), pages 1-55, August.
    5. Beyza, Jesus & Gil, Pablo & Masera, Marcelo & Yusta, Jose M., 2020. "Security assessment of cross-border electricity interconnections," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    6. Forsberg, Samuel & Thomas, Karin & Bergkvist, Mikael, 2023. "Power grid vulnerability analysis using complex network theory: A topological study of the Nordic transmission grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    7. Espejo, Rafael & Lumbreras, Sara & Ramos, Andres, 2018. "Analysis of transmission-power-grid topology and scalability, the European case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 383-395.
    8. Wang, Shuliang & Guo, Zhaoyang & Huang, Xiaodi & Zhang, Jianhua, 2024. "A three-stage model of quantifying and analyzing power network resilience based on network theory," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    9. Wang, Shuliang & Gu, Xifeng & Luan, Shengyang & Zhao, Mingwei, 2021. "Resilience analysis of interdependent critical infrastructure systems considering deep learning and network theory," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. Vaibhav Gaur & Om Prakash Yadav & Gunjan Soni & Ajay Pal Singh Rathore, 2021. "A literature review on network reliability analysis and its engineering applications," Journal of Risk and Reliability, , vol. 235(2), pages 167-181, April.
    4. 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.
    5. 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.
    6. H Jönsson & J Johansson & H Johansson, 2008. "Identifying critical components in technical infrastructure networks," Journal of Risk and Reliability, , vol. 222(2), pages 235-243, June.
    7. 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.
    8. 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.
    9. Koç, Yakup & Warnier, Martijn & Van Mieghem, Piet & Kooij, Robert E. & Brazier, Frances M.T., 2014. "A topological investigation of phase transitions of cascading failures in power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 273-284.
    10. Prehoda, Emily W. & Schelly, Chelsea & Pearce, Joshua M., 2017. "U.S. strategic solar photovoltaic-powered microgrid deployment for enhanced national security," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 167-175.
    11. Wu, Di & Ma, Feng & Javadi, Milad & Thulasiraman, Krishnaiya & Bompard, Ettore & Jiang, John N., 2017. "A study of the impacts of flow direction and electrical constraints on vulnerability assessment of power grid using electrical betweenness measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 295-309.
    12. Abeysinghe, Sathsara & Wu, Jianzhong & Sooriyabandara, Mahesh & Abeysekera, Muditha & Xu, Tao & Wang, Chengshan, 2018. "Topological properties of medium voltage electricity distribution networks," Applied Energy, Elsevier, vol. 210(C), pages 1101-1112.
    13. 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.
    14. 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.
    15. Pagani, Giuliano Andrea & Aiello, Marco, 2013. "The Power Grid as a complex network: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2688-2700.
    16. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    17. Sarah LaRocca & Jonas Johansson & Henrik Hassel & Seth Guikema, 2015. "Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 608-623, April.
    18. Nie, Yan & Zhang, Guoxing & Duan, Hongbo, 2020. "An interconnected panorama of future cross-regional power grid: A complex network approach," Resources Policy, Elsevier, vol. 67(C).
    19. 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.
    20. Ettore Bompard & Lingen Luo & Enrico Pons, 2015. "A perspective overview of topological approaches for vulnerability analysis of power transmission grids," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 11(1), pages 15-26.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:396:y:2014:i:c:p:204-211. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.