Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems
(2013)- 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:
https://lup.lub.lu.se/record/3916491
- author
- LaRocca, Sarah ; Johansson, Jonas LU ; Hassel, Henrik LU and Guikema, Seth
- organization
- publishing date
- 2013
- type
- Other contribution
- publication status
- published
- subject
- keywords
- critical infrastructure, electric power, functional models, topological models, load flow
- 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
- 2016-04-04 11:37:47
- date last changed
- 2020-12-03 13:29:18
@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}},
keywords = {{critical infrastructure; electric power; functional models; topological models; load flow}},
language = {{eng}},
title = {{Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems}},
url = {{http://arxiv.org/abs/1306.6696}},
year = {{2013}},
}