Generalised resilience models for power systems and dependent infrastructure during extreme events

This study presents a generalised critical infrastructures resilience model for extreme events with a focus on power grids. Infrastructures are modelled as three domains – physical, cyber, and human. Each domain is described with respect to the services it provides. Each domain is represented by geo...

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Main Authors: Vaidyanathan Krishnamurthy, Bing Huang, Alexis Kwasinski, Evan Pierce, Ross Baldick
Format: Article
Language:English
Published: Wiley 2019-12-01
Series:IET Smart Grid
Subjects:
Online Access:https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0170
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spelling doaj-354eeb112b9c475a88e1c2096829d07b2021-04-02T12:26:27ZengWileyIET Smart Grid2515-29472019-12-0110.1049/iet-stg.2019.0170IET-STG.2019.0170Generalised resilience models for power systems and dependent infrastructure during extreme eventsVaidyanathan Krishnamurthy0Bing Huang1Bing Huang2Alexis Kwasinski3Evan Pierce4Ross Baldick5Department of Electrical and Computer Engineering, University of PittsburghElectrical and Computer Engineering, The University of Texas at AustinElectrical and Computer Engineering, The University of Texas at AustinDepartment of Electrical and Computer Engineering, University of PittsburghMcCombs School of Business, The University of Texas at AustinElectrical and Computer Engineering, The University of Texas at AustinThis study presents a generalised critical infrastructures resilience model for extreme events with a focus on power grids. Infrastructures are modelled as three domains – physical, cyber, and human. Each domain is described with respect to the services it provides. Each domain is represented by geometric graphs for each service it provides. The resilience models use geometric graphs with each graph's nodes and edges characterised based on relevant attributes. This study also discusses various applied aspects related to resilience models including the impact of changing operating environment, human-driven processes, such as logistics, and service buffers. Due to their stated particular importance in the U.S. Presidential Policy Directive 21, particular attention is placed on the power infrastructure and its impact on the public communication infrastructures as a main critical load. This study focuses on the multi-time scale power system operation to capture cascading outages within, and subsequently to its dependent infrastructure – the public communication system (e.g. wireless or ‘cellular’ communication networks) as a main critical load. This study illustrates the merits of the proposed models in calculating resilience in extreme events and derives physical domain representation for electric and communication systems using cell tower and substation data from the USA.https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0170critical infrastructuressubstationspower gridsgraph theorypower engineering computingcommunication systemspower systemsdependent infrastructuregeneralised critical infrastructures resilience modelpower gridsgeometric graphsservice bufferspower infrastructurepublic communication infrastructuresmultitime scale power system operationpublic communication systemderives physical domain representationelectric systemssubstation datacell tower
collection DOAJ
language English
format Article
sources DOAJ
author Vaidyanathan Krishnamurthy
Bing Huang
Bing Huang
Alexis Kwasinski
Evan Pierce
Ross Baldick
spellingShingle Vaidyanathan Krishnamurthy
Bing Huang
Bing Huang
Alexis Kwasinski
Evan Pierce
Ross Baldick
Generalised resilience models for power systems and dependent infrastructure during extreme events
IET Smart Grid
critical infrastructures
substations
power grids
graph theory
power engineering computing
communication systems
power systems
dependent infrastructure
generalised critical infrastructures resilience model
power grids
geometric graphs
service buffers
power infrastructure
public communication infrastructures
multitime scale power system operation
public communication system
derives physical domain representation
electric systems
substation data
cell tower
author_facet Vaidyanathan Krishnamurthy
Bing Huang
Bing Huang
Alexis Kwasinski
Evan Pierce
Ross Baldick
author_sort Vaidyanathan Krishnamurthy
title Generalised resilience models for power systems and dependent infrastructure during extreme events
title_short Generalised resilience models for power systems and dependent infrastructure during extreme events
title_full Generalised resilience models for power systems and dependent infrastructure during extreme events
title_fullStr Generalised resilience models for power systems and dependent infrastructure during extreme events
title_full_unstemmed Generalised resilience models for power systems and dependent infrastructure during extreme events
title_sort generalised resilience models for power systems and dependent infrastructure during extreme events
publisher Wiley
series IET Smart Grid
issn 2515-2947
publishDate 2019-12-01
description This study presents a generalised critical infrastructures resilience model for extreme events with a focus on power grids. Infrastructures are modelled as three domains – physical, cyber, and human. Each domain is described with respect to the services it provides. Each domain is represented by geometric graphs for each service it provides. The resilience models use geometric graphs with each graph's nodes and edges characterised based on relevant attributes. This study also discusses various applied aspects related to resilience models including the impact of changing operating environment, human-driven processes, such as logistics, and service buffers. Due to their stated particular importance in the U.S. Presidential Policy Directive 21, particular attention is placed on the power infrastructure and its impact on the public communication infrastructures as a main critical load. This study focuses on the multi-time scale power system operation to capture cascading outages within, and subsequently to its dependent infrastructure – the public communication system (e.g. wireless or ‘cellular’ communication networks) as a main critical load. This study illustrates the merits of the proposed models in calculating resilience in extreme events and derives physical domain representation for electric and communication systems using cell tower and substation data from the USA.
topic critical infrastructures
substations
power grids
graph theory
power engineering computing
communication systems
power systems
dependent infrastructure
generalised critical infrastructures resilience model
power grids
geometric graphs
service buffers
power infrastructure
public communication infrastructures
multitime scale power system operation
public communication system
derives physical domain representation
electric systems
substation data
cell tower
url https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0170
work_keys_str_mv AT vaidyanathankrishnamurthy generalisedresiliencemodelsforpowersystemsanddependentinfrastructureduringextremeevents
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AT alexiskwasinski generalisedresiliencemodelsforpowersystemsanddependentinfrastructureduringextremeevents
AT evanpierce generalisedresiliencemodelsforpowersystemsanddependentinfrastructureduringextremeevents
AT rossbaldick generalisedresiliencemodelsforpowersystemsanddependentinfrastructureduringextremeevents
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