Literature DB >> 20887062

Do topological models provide good information about electricity infrastructure vulnerability?

Paul Hines1, Eduardo Cotilla-Sanchez, Seth Blumsack.   

Abstract

In order to identify the extent to which results from topological graph models are useful for modeling vulnerability in electricity infrastructure, we measure the susceptibility of power networks to random failures and directed attacks using three measures of vulnerability: characteristic path lengths, connectivity loss, and blackout sizes. The first two are purely topological metrics. The blackout size calculation results from a model of cascading failure in power networks. Testing the response of 40 areas within the Eastern U.S. power grid and a standard IEEE test case to a variety of attack/failure vectors indicates that directed attacks result in larger failures using all three vulnerability measures, but the attack-vectors that appear to cause the most damage depend on the measure chosen. While the topological metrics and the power grid model show some similar trends, the vulnerability metrics for individual simulations show only a mild correlation. We conclude that evaluating vulnerability in power networks using purely topological metrics can be misleading.

Year:  2010        PMID: 20887062     DOI: 10.1063/1.3489887

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  14 in total

1.  Suppressing cascades of load in interdependent networks.

Authors:  Charles D Brummitt; Raissa M D'Souza; E A Leicht
Journal:  Proc Natl Acad Sci U S A       Date:  2012-02-21       Impact factor: 11.205

2.  Transdisciplinary electric power grid science.

Authors:  Charles D Brummitt; Paul D H Hines; Ian Dobson; Cristopher Moore; Raissa M D'Souza
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-23       Impact factor: 11.205

3.  General methodology for inferring failure-spreading dynamics in networks.

Authors:  Xiangyang Guan; Cynthia Chen
Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-15       Impact factor: 11.205

4.  Ensembles of realistic power distribution networks.

Authors:  Rounak Meyur; Anil Vullikanti; Samarth Swarup; Henning S Mortveit; Virgilio Centeno; Arun Phadke; H Vincent Poor; Madhav V Marathe
Journal:  Proc Natl Acad Sci U S A       Date:  2022-10-10       Impact factor: 12.779

5.  Limits and trade-offs of topological network robustness.

Authors:  Christopher Priester; Sebastian Schmitt; Tiago P Peixoto
Journal:  PLoS One       Date:  2014-09-24       Impact factor: 3.240

6.  Islanding the power grid on the transmission level: less connections for more security.

Authors:  Mario Mureddu; Guido Caldarelli; Alfonso Damiano; Antonio Scala; Hildegard Meyer-Ortmanns
Journal:  Sci Rep       Date:  2016-10-07       Impact factor: 4.379

7.  Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence.

Authors:  Mert Korkali; Jason G Veneman; Brian F Tivnan; James P Bagrow; Paul D H Hines
Journal:  Sci Rep       Date:  2017-03-20       Impact factor: 4.379

8.  Topological vulnerability of power grids to disasters: Bounds, adversarial attacks and reinforcement.

Authors:  Deepjyoti Deka; Sriram Vishwanath; Ross Baldick
Journal:  PLoS One       Date:  2018-10-12       Impact factor: 3.240

9.  Coupled catastrophes: sudden shifts cascade and hop among interdependent systems.

Authors:  Charles D Brummitt; George Barnett; Raissa M D'Souza
Journal:  J R Soc Interface       Date:  2015-11-06       Impact factor: 4.118

10.  Dynamically induced cascading failures in power grids.

Authors:  Benjamin Schäfer; Dirk Witthaut; Marc Timme; Vito Latora
Journal:  Nat Commun       Date:  2018-05-17       Impact factor: 14.919

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