IDEAS home Printed from https://ideas.repec.org/a/hin/complx/3531209.html
   My bibliography  Save this article

Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks

Author

Listed:
  • Xiaoguang Wei
  • Shibin Gao
  • Tao Huang
  • Tao Wang
  • Wenli Fan

Abstract

This paper proposes a new framework to analyze two vulnerability features, impactability and susceptibility, in electrical networks under deliberate attacks based on complex network theory: these two features are overlooked but vital in vulnerability analyses. To analyze these features, metrics are proposed based on correlation graphs constructed via critical paths, which replace the original physical network. Moreover, we analyze the relationship between the proposed metrics according to degree from the perspective of load redistribution mechanisms by adjusting parameters associated with the metrics, which can change the load redistribution rules. Finally, IEEE 118- and 300-bus systems and a realistic large-scale French grid are used to validate the effectiveness of the proposed metrics.

Suggested Citation

  • Xiaoguang Wei & Shibin Gao & Tao Huang & Tao Wang & Wenli Fan, 2019. "Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks," Complexity, Hindawi, vol. 2019, pages 1-14, January.
    • Handle: RePEc:hin:complx:3531209
    DOI: 10.1155/2019/3531209
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2019/3531209.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2019/3531209.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2019/3531209?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
    ---><---

    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. Ying Wang & Xiangmei Li & Jiangfeng Li & Zhengdong Huang & Renbin Xiao, 2018. "Impact of Rapid Urbanization on Vulnerability of Land System from Complex Networks View: A Methodological Approach," Complexity, Hindawi, vol. 2018, pages 1-18, May.
    3. Long Guo & Xu Cai, 2008. "Degree And Weighted Properties Of The Directed China Railway Network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 19(12), pages 1909-1918.
    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. Tianlei Zang & Zian Wang & Xiaoguang Wei & Yi Zhou & Jiale Wu & Buxiang Zhou, 2023. "Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory," Energies, MDPI, vol. 16(18), pages 1-38, September.
    2. Upama Nakarmi & Mahshid Rahnamay Naeini & Md Jakir Hossain & Md Abul Hasnat, 2020. "Interaction Graphs for Cascading Failure Analysis in Power Grids: A Survey," Energies, MDPI, vol. 13(9), pages 1-25, May.
    3. Tao Wang & Xiaoguang Wei & Tao Huang & Jun Wang & Luis Valencia-Cabrera & Zhennan Fan & Mario J. Pérez-Jiménez, 2019. "Cascading Failures Analysis Considering Extreme Virus Propagation of Cyber-Physical Systems in Smart Grids," Complexity, Hindawi, vol. 2019, pages 1-15, March.

    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. Dávid Csercsik & László Á. Kóczy, 2017. "Efficiency and Stability in Electrical Power Transmission Networks: a Partition Function Form Approach," Networks and Spatial Economics, Springer, vol. 17(4), pages 1161-1184, December.
    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. Zhaoming Yang & Qi Xiang & Yuxuan He & Shiliang Peng & Michael Havbro Faber & Enrico Zio & Lili Zuo & Huai Su & Jinjun Zhang, 2023. "Resilience of Natural Gas Pipeline System: A Review and Outlook," Energies, MDPI, vol. 16(17), pages 1-19, August.
    4. Zhou, Yaoming & Wang, Junwei, 2018. "Efficiency of complex networks under failures and attacks: A percolation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 658-664.
    5. Arinushkin, P.A. & Vadivasova, T.E., 2021. "Nonlinear damping effects in a simplified power grid model based on coupled Kuramoto-like oscillators with inertia," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    6. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2011. "Maximal network reliability for a stochastic power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1332-1339.
    7. Claudio M. Rocco & Kash Barker & Jose Moronta, 2022. "Determining the best algorithm to detect community structures in networks: application to power systems," Environment Systems and Decisions, Springer, vol. 42(2), pages 251-264, June.
    8. Wen, Xiangxi & Tu, Congliang & Wu, Minggong, 2018. "Node importance evaluation in aviation network based on “No Return” node deletion method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 546-559.
    9. Xiao, Guanping & Zheng, Zheng & Wang, Haoqin, 2017. "Evolution of Linux operating system network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 249-258.
    10. 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.
    11. Hang Thi-Thuy Le & Eleonora Riva Sanseverino & Ninh Quang Nguyen & Maria Luisa Di Silvestre & Salvatore Favuzza & Binh Doan Van & Rossano Musca, 2023. "Critical Assessments of the Potential for Integrating Renewable Energy into Isolated Grids on Vietnamese Islands: The Case of the An-Binh Grid," Energies, MDPI, vol. 16(5), pages 1-23, March.
    12. 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.
    13. D E Salazar A & C M Rocco S & E Zio, 2008. "Optimal protection of complex networks exposed to a terrorist hazard: A multi-objective evolutionary approach," Journal of Risk and Reliability, , vol. 222(3), pages 327-335, September.
    14. Zio, E. & Golea, L.R., 2012. "Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 67-74.
    15. Tianlei Zang & Zian Wang & Xiaoguang Wei & Yi Zhou & Jiale Wu & Buxiang Zhou, 2023. "Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory," Energies, MDPI, vol. 16(18), pages 1-38, September.
    16. Nahmmacher, Paul & Schmid, Eva & Pahle, Michael & Knopf, Brigitte, 2016. "Strategies against shocks in power systems – An analysis for the case of Europe," Energy Economics, Elsevier, vol. 59(C), pages 455-465.
    17. Dingrao Feng & Wenkai Bao & Meichen Fu & Min Zhang & Yiyu Sun, 2021. "Current and Future Land Use Characters of a National Central City in Eco-Fragile Region—A Case Study in Xi’an City Based on FLUS Model," Land, MDPI, vol. 10(3), pages 1-25, March.
    18. Zongyao Sha & Dai Qiu & Husheng Fang & Yichun Xie & Jiangguang Tu & Xicheng Tan & Xiaolei Li & Jiangping Chen, 2022. "Assessing the Potential of Vegetation Carbon Uptake from Optimal Land Management in the Greater Guangzhou Area," Land, MDPI, vol. 11(11), pages 1-18, October.
    19. Ferrario, E. & Poulos, A. & Castro, S. & de la Llera, J.C. & Lorca, A., 2022. "Predictive capacity of topological measures in evaluating seismic risk and resilience of electric power networks," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    20. Johan Rose Santos & Nur Diana Safitri & Maya Safira & Varun Varghese & Makoto Chikaraishi, 2021. "Road network vulnerability and city-level characteristics: A nationwide comparative analysis of Japanese cities," Environment and Planning B, , vol. 48(5), pages 1091-1107, June.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:3531209. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.