Topological performance measures as surrogates for physical flow models for risk and vulnerability analysis for electric power systems.
(2015) In Risk Analysis: an official publication of the Society for Risk Analysis 35(4). p.608-623- 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 find 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 that can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. In this article, we suggest a classification of these models, which span from simple... (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 find 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 that can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. In this article, we suggest a classification of these models, which span from simple topologically-oriented models to advanced physical-flow-based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this article is to compare performance estimates achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combinations 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/5442014
- author
- LaRocca, Sarah ; Johansson, Jonas LU ; Hassel, Henrik LU and Guikema, Seth
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Risk Analysis: an official publication of the Society for Risk Analysis
- volume
- 35
- issue
- 4
- pages
- 608 - 623
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- pmid:26018246
- wos:000355287900007
- scopus:84929953369
- pmid:26018246
- ISSN
- 1539-6924
- DOI
- 10.1111/risa.12281
- language
- English
- LU publication?
- yes
- id
- 4cbb0b56-3d9f-461a-9b8a-b63fdc163bbb (old id 5442014)
- date added to LUP
- 2016-04-01 10:59:49
- date last changed
- 2022-04-04 23:20:48
@article{4cbb0b56-3d9f-461a-9b8a-b63fdc163bbb,
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 find 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 that can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. In this article, we suggest a classification of these models, which span from simple topologically-oriented models to advanced physical-flow-based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this article is to compare performance estimates achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combinations 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.}},
author = {{LaRocca, Sarah and Johansson, Jonas and Hassel, Henrik and Guikema, Seth}},
issn = {{1539-6924}},
language = {{eng}},
number = {{4}},
pages = {{608--623}},
publisher = {{John Wiley & Sons Inc.}},
series = {{Risk Analysis: an official publication of the Society for Risk Analysis}},
title = {{Topological performance measures as surrogates for physical flow models for risk and vulnerability analysis for electric power systems.}},
url = {{http://dx.doi.org/10.1111/risa.12281}},
doi = {{10.1111/risa.12281}},
volume = {{35}},
year = {{2015}},
}