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Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems

LaRocca, Sarah; Johansson, Jonas LU ; Hassel, Henrik LU and Guikema, Seth (2013) In ARXIV
Abstract
Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of

society. To improve the performance of such systems, we often use risk and vulnerability analysis to nd and

address system weaknesses. A critical component of such analyses is the ability to accurately determine the

negative consequences of various types of failures in the system. Numerous mathematical and simulation models

exist which can be used to this end. However, there are relatively few studies comparing the implications of

using dierent modeling approaches in the context of comprehensive risk analysis of critical infrastructures.

Thus in this paper, we suggest a classication... (More)
Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of

society. To improve the performance of such systems, we often use risk and vulnerability analysis to nd and

address system weaknesses. A critical component of such analyses is the ability to accurately determine the

negative consequences of various types of failures in the system. Numerous mathematical and simulation models

exist which can be used to this end. However, there are relatively few studies comparing the implications of

using dierent modeling approaches in the context of comprehensive risk analysis of critical infrastructures.

Thus in this paper, we suggest a classication of these models, which span from simple topologically-oriented

models to advanced physical

ow-based models. Here, we focus on electric power systems and present a study

aimed at understanding the tradeos between simplicity and delity in models used in the context of risk

analysis. Specically, the purpose of this paper is to compare performances measures achieved with a spectrum

of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if

more simplied topological measures can be combined using statistical methods to be used as a surrogate

for physical

ow models. The results of our work provide guidance as to appropriate models or combination

of models to use when analyzing large-scale critical infrastructure systems, where simulation times quickly

become insurmountable when using more advanced models, severely limiting the extent of analyses that can

be performed. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
submitted
subject
keywords
critical infrastructure, electric power, functional models, topological models, load flow
in
ARXIV
publisher
Cornell University Library
language
English
LU publication?
yes
id
2ae9066e-8b53-4e24-b8a8-8ceca9ccebcb (old id 3916491)
alternative location
http://arxiv.org/abs/1306.6696
date added to LUP
2013-07-22 12:20:24
date last changed
2016-10-11 08:41:51
@misc{2ae9066e-8b53-4e24-b8a8-8ceca9ccebcb,
  abstract     = {Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of<br/><br>
society. To improve the performance of such systems, we often use risk and vulnerability analysis to nd and<br/><br>
address system weaknesses. A critical component of such analyses is the ability to accurately determine the<br/><br>
negative consequences of various types of failures in the system. Numerous mathematical and simulation models<br/><br>
exist which can be used to this end. However, there are relatively few studies comparing the implications of<br/><br>
using dierent modeling approaches in the context of comprehensive risk analysis of critical infrastructures.<br/><br>
Thus in this paper, we suggest a classication of these models, which span from simple topologically-oriented<br/><br>
models to advanced physical <br/><br>
ow-based models. Here, we focus on electric power systems and present a study<br/><br>
aimed at understanding the tradeos between simplicity and delity in models used in the context of risk<br/><br>
analysis. Specically, the purpose of this paper is to compare performances measures achieved with a spectrum<br/><br>
of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if<br/><br>
more simplied topological measures can be combined using statistical methods to be used as a surrogate<br/><br>
for physical <br/><br>
ow models. The results of our work provide guidance as to appropriate models or combination<br/><br>
of models to use when analyzing large-scale critical infrastructure systems, where simulation times quickly<br/><br>
become insurmountable when using more advanced models, severely limiting the extent of analyses that can<br/><br>
be performed.},
  author       = {LaRocca, Sarah and Johansson, Jonas and Hassel, Henrik and Guikema, Seth},
  keyword      = {critical infrastructure,electric power,functional models,topological models,load flow},
  language     = {eng},
  publisher    = {ARRAY(0x8ba4218)},
  series       = {ARXIV},
  title        = {Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems},
  year         = {2013},
}