IDEAS home Printed from https://ideas.repec.org/a/eee/ijocip/v12y2016icp29-45.html
   My bibliography  Save this article

New centrality measures for assessing smart grid vulnerabilities and predicting brownouts and blackouts

Author

Listed:
  • Chopade, Pravin
  • Bikdash, Marwan

Abstract

This paper proposes mathematical models based on the electrical properties of smart grids for conducting vulnerability analyses and predicting brownouts and blackouts. Definitions of pseudo-Laplacian, pseudo-adjacency and pseudo-degree matrices for smart grids are introduced to specify new centrality measures with electrical interpretations. The centrality measures are used to rank the relative importance of nodes (e.g., generating stations or substations) and edges (e.g., transmission lines or buses) of a graph corresponding to a power grid network and to assess the overall vulnerability of the network. The reliability of using the centrality measures to predict brownouts and blackouts is demonstrated in the face of random and targeted attacks. Monte-Carlo simulations are used to analyze attacks on smart grid networks and to assess the performance of the centrality measures. The simulations employ the IEEE 30-bus, IEEE 57-bus and IEEE 300-bus networks as well as the WSCC 4941-bus real power grid. Every scenario in the Monte-Carlo simulations involves the removal of a subset of buses and performing a complete nonlinear Newton–Raphson power flow analysis to compute the power traffic matrix and the corresponding centrality. The Monte-Carlo simulations conclusively demonstrate that electrical centrality measures based on the power traffic matrix are reliable indicators of the total unsatisfied load ratio (i.e., the load taken offline due to an attack divided by the total load demand). A key result is that, if the total centrality score of the removed buses exceeds a threshold estimated via Monte-Carlo simulation, then a sudden and dramatic jump to a blackout situation is ensured.

Suggested Citation

  • Chopade, Pravin & Bikdash, Marwan, 2016. "New centrality measures for assessing smart grid vulnerabilities and predicting brownouts and blackouts," International Journal of Critical Infrastructure Protection, Elsevier, vol. 12(C), pages 29-45.
    • Handle: RePEc:eee:ijocip:v:12:y:2016:i:c:p:29-45
    DOI: 10.1016/j.ijcip.2015.12.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1874548215000797
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijcip.2015.12.001?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. Zio, Enrico & Piccinelli, Roberta, 2010. "Randomized flow model and centrality measure for electrical power transmission network analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 379-385.
    2. Zio, Enrico & Podofillini, Luca & Zille, Valérie, 2006. "A combination of Monte Carlo simulation and cellular automata for computing the availability of complex network systems," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 181-190.
    3. Bompard, Ettore & Napoli, Roberto & Xue, Fei, 2009. "Analysis of structural vulnerabilities in power transmission grids," International Journal of Critical Infrastructure Protection, Elsevier, vol. 2(1), pages 5-12.
    4. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2003. "Efficiency of scale-free networks: error and attack tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 622-642.
    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. Faramondi, Luca & Oliva, Gabriele & Setola, Roberto, 2020. "Multi-criteria node criticality assessment framework for critical infrastructure networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
    2. 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.
    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. Zhao, Chen & Li, Nan & Fang, Dongping, 2018. "Criticality assessment of urban interdependent lifeline systems using a biased PageRank algorithm and a multilayer weighted directed network model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 100-112.

    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. 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.
    2. Li, Daqing & Zhang, Qiong & Zio, Enrico & Havlin, Shlomo & Kang, Rui, 2015. "Network reliability analysis based on percolation theory," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 556-562.
    3. 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.
    4. 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.
    5. Andrea Avena-Koenigsberger & Xiaoran Yan & Artemy Kolchinsky & Martijn P van den Heuvel & Patric Hagmann & Olaf Sporns, 2019. "A spectrum of routing strategies for brain networks," PLOS Computational Biology, Public Library of Science, vol. 15(3), pages 1-24, March.
    6. Gianluca Fulli & Marcelo Masera & Catalin Felix Covrig & Francesco Profumo & Ettore Bompard & Tao Huang, 2017. "The EU Electricity Security Decision-Analytic Framework: Status and Perspective Developments," Energies, MDPI, vol. 10(4), pages 1-20, March.
    7. 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.
    8. Trpevski, Daniel & Smilkov, Daniel & Mishkovski, Igor & Kocarev, Ljupco, 2010. "Vulnerability of labeled networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(23), pages 5538-5549.
    9. Azzolin, Alberto & Dueñas-Osorio, Leonardo & Cadini, Francesco & Zio, Enrico, 2018. "Electrical and topological drivers of the cascading failure dynamics in power transmission networks," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 196-206.
    10. 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.
    11. Zhao, Jianyu & Wei, Jiang & Yu, Lean & Xi, Xi, 2022. "Robustness of knowledge networks under targeted attacks: Electric vehicle field of China evidence," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 367-382.
    12. Fabio Della Rossa & Lorenzo Giannini & Pietro DeLellis, 2020. "Herding or wisdom of the crowd? Controlling efficiency in a partially rational financial market," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
    13. Viljoen, Nadia M. & Joubert, Johan W., 2016. "The vulnerability of the global container shipping network to targeted link disruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 396-409.
    14. Patterson, S.A. & Apostolakis, G.E., 2007. "Identification of critical locations across multiple infrastructures for terrorist actions," Reliability Engineering and System Safety, Elsevier, vol. 92(9), pages 1183-1203.
    15. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    16. Zio, E. & Golea, L.R. & Rocco S., C.M., 2012. "Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 172-177.
    17. Beccuti, Marco & Chiaradonna, Silvano & Di Giandomenico, Felicita & Donatelli, Susanna & Dondossola, Giovanna & Franceschinis, Giuliana, 2012. "Quantification of dependencies between electrical and information infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 5(1), pages 14-27.
    18. E Zio & M Librizzi & G Sansavini, 2008. "A combined Monte Carlo and cellular automata approach to the unreliability analysis of binary network systems," Journal of Risk and Reliability, , vol. 222(1), pages 31-38, March.
    19. Badami, Marco & Fonti, Antonio & Carpignano, Andrea & Grosso, Daniele, 2018. "Design of district heating networks through an integrated thermo-fluid dynamics and reliability modelling approach," Energy, Elsevier, vol. 144(C), pages 826-838.
    20. César Yajure & Darihelen Montilla & Jose Emmanuel Ramirez-Marquez & Claudio M Rocco S, 2013. "Network vulnerability assessment via bi-objective optimization with a fragmentation approach as proxy," Journal of Risk and Reliability, , vol. 227(6), pages 576-585, December.

    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:ijocip:v:12:y:2016:i:c:p:29-45. 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: https://www.journals.elsevier.com/international-journal-of-critical-infrastructure-protection .

    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.