Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather
peer reviewed This paper presents a probabilistic methodology for assessing power system resilience,motivated by the extreme weather storm experienced in Iceland in December 2019. The methodologyis built on the basis of models and data available to the Icelandic transmission system operatorin antici...
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ftorbi:oai:orbi.ulg.ac.be:2268/253776 2024-04-21T08:05:41+00:00 Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather Karangelos, Efthymios Perkin, Samuel Wehenkel, Louis Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège 2020 https://orbi.uliege.be/handle/2268/253776 https://orbi.uliege.be/bitstream/2268/253776/1/applsci-10-05089-v2.pdf https://doi.org/10.3390/app10155089 en eng MDPI https://www.mdpi.com/2076-3417/10/15/5089 urn:issn:2076-3417 https://orbi.uliege.be/handle/2268/253776 info:hdl:2268/253776 https://orbi.uliege.be/bitstream/2268/253776/1/applsci-10-05089-v2.pdf doi:10.3390/app10155089 scopus-id:2-s2.0-85088561830 open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess Applied Sciences (2020) attacker-defender probabilistic resilience Engineering computing & technology Electrical & electronics engineering Ingénierie informatique & technologie Ingénierie électrique & électronique journal article http://purl.org/coar/resource_type/c_6501 info:eu-repo/semantics/article peer reviewed 2020 ftorbi https://doi.org/10.3390/app10155089 2024-03-27T14:59:46Z peer reviewed This paper presents a probabilistic methodology for assessing power system resilience,motivated by the extreme weather storm experienced in Iceland in December 2019. The methodologyis built on the basis of models and data available to the Icelandic transmission system operatorin anticipation of the said storm. We study resilience in terms of the ability of the system tocontain further service disruption, while potentially operating with reduced component availabilitydue to the storm impact. To do so, we develop a Monte Carlo assessment framework combiningweather-dependent component failure probabilities, enumerated through historical failure ratedata and forecasted wind-speed data, with a bi-level attacker-defender optimization model forvulnerability identification. Our findings suggest that the ability of the Icelandic power system tocontain service disruption moderately reduces with the storm-induced potential reduction of itsavailable components. In other words, and as also validated in practice, the system is indeed resilient. Article in Journal/Newspaper Iceland University of Liège: ORBi (Open Repository and Bibliography) Applied Sciences 10 15 5089 |
institution |
Open Polar |
collection |
University of Liège: ORBi (Open Repository and Bibliography) |
op_collection_id |
ftorbi |
language |
English |
topic |
attacker-defender probabilistic resilience Engineering computing & technology Electrical & electronics engineering Ingénierie informatique & technologie Ingénierie électrique & électronique |
spellingShingle |
attacker-defender probabilistic resilience Engineering computing & technology Electrical & electronics engineering Ingénierie informatique & technologie Ingénierie électrique & électronique Karangelos, Efthymios Perkin, Samuel Wehenkel, Louis Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather |
topic_facet |
attacker-defender probabilistic resilience Engineering computing & technology Electrical & electronics engineering Ingénierie informatique & technologie Ingénierie électrique & électronique |
description |
peer reviewed This paper presents a probabilistic methodology for assessing power system resilience,motivated by the extreme weather storm experienced in Iceland in December 2019. The methodologyis built on the basis of models and data available to the Icelandic transmission system operatorin anticipation of the said storm. We study resilience in terms of the ability of the system tocontain further service disruption, while potentially operating with reduced component availabilitydue to the storm impact. To do so, we develop a Monte Carlo assessment framework combiningweather-dependent component failure probabilities, enumerated through historical failure ratedata and forecasted wind-speed data, with a bi-level attacker-defender optimization model forvulnerability identification. Our findings suggest that the ability of the Icelandic power system tocontain service disruption moderately reduces with the storm-induced potential reduction of itsavailable components. In other words, and as also validated in practice, the system is indeed resilient. |
author2 |
Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège |
format |
Article in Journal/Newspaper |
author |
Karangelos, Efthymios Perkin, Samuel Wehenkel, Louis |
author_facet |
Karangelos, Efthymios Perkin, Samuel Wehenkel, Louis |
author_sort |
Karangelos, Efthymios |
title |
Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather |
title_short |
Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather |
title_full |
Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather |
title_fullStr |
Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather |
title_full_unstemmed |
Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather |
title_sort |
probabilistic resilience analysis of the icelandic power system under extreme weather |
publisher |
MDPI |
publishDate |
2020 |
url |
https://orbi.uliege.be/handle/2268/253776 https://orbi.uliege.be/bitstream/2268/253776/1/applsci-10-05089-v2.pdf https://doi.org/10.3390/app10155089 |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Applied Sciences (2020) |
op_relation |
https://www.mdpi.com/2076-3417/10/15/5089 urn:issn:2076-3417 https://orbi.uliege.be/handle/2268/253776 info:hdl:2268/253776 https://orbi.uliege.be/bitstream/2268/253776/1/applsci-10-05089-v2.pdf doi:10.3390/app10155089 scopus-id:2-s2.0-85088561830 |
op_rights |
open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.3390/app10155089 |
container_title |
Applied Sciences |
container_volume |
10 |
container_issue |
15 |
container_start_page |
5089 |
_version_ |
1796945108374913024 |