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A scenario based threat assessment using Bayesian networks for a high voltage direct current converter platform

Tecklenburg, Babette and Gabriel, Alexander and Sill Torres, Frank (2022) A scenario based threat assessment using Bayesian networks for a high voltage direct current converter platform. In: Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022), pp. 2637-2644. Research Publishing. 32nd European Safety and Reliability Conference, 28. Aug - 1. Sep 2022, Dublin, Ireland. doi: 10.3850/978-981-18-5183-4_S16-05-494-cd. ISBN 978-981-18-5183-4.

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Official URL: https://www.rpsonline.com.sg/proceedings/esrel2022/pdf/S16-05-494.pdf

Abstract

The climate change challenges a variety of aspects in our society. One spect is the energy production and the composition of the energy mix. Through the last years the amount of offshore wind farms has increased as well as the structure of the electricity producing infrastructure has changed from a more centralized (power plant oriented) to a more regional mode (decentral (offshore) wind farms and solar panels) of production. The vulnerability of the power-generating infrastructure is also changing. Therefore a quantification of the threat level is necessary. This paper should evaluate if a Bayesian network as a quantitative risk assessment model can be used to assess the threat level of an offshore wind farm. Common approaches build a Bayesian network based on a qualitative risk assessment. The Bayesian network presented in the paper is build based on a Functional Resonance Analysis Method (FRAM) based process model because a threat is strongly influenced by the scenario under consideration. The developed approach will be applied to the case study “unauthorized access to an high voltage direct current converter platform (HVDCC)”.

Item URL in elib:https://elib.dlr.de/189076/
Document Type:Conference or Workshop Item (Speech)
Title:A scenario based threat assessment using Bayesian networks for a high voltage direct current converter platform
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Tecklenburg, BabetteBabette.Tecklenburg (at) dlr.dehttps://orcid.org/0000-0003-0606-0381
Gabriel, AlexanderAlexander.Gabriel (at) dlr.dehttps://orcid.org/0000-0002-9660-1366
Sill Torres, FrankFrank.SillTorres (at) dlr.dehttps://orcid.org/0000-0002-4028-455X
Date:2022
Journal or Publication Title:Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI:10.3850/978-981-18-5183-4_S16-05-494-cd
Page Range:pp. 2637-2644
Editors:
EditorsEmailEditor's ORCID iD
Leva, Maria ChiaraUNSPECIFIEDUNSPECIFIED
Patelli, EdoardoUNSPECIFIEDUNSPECIFIED
Podofillini, LucaUNSPECIFIEDUNSPECIFIED
Wilson, SimonUNSPECIFIEDUNSPECIFIED
Publisher:Research Publishing
ISBN:978-981-18-5183-4
Status:Published
Keywords:Bayesian network, Functional Resonance Analysis Method, threat assessment, high voltage direct current converter platform, unauthorized access, offshore wind farm
Event Title:32nd European Safety and Reliability Conference
Event Location:Dublin, Ireland
Event Type:international Conference
Event Dates:28. Aug - 1. Sep 2022
Organizer:European Safety and Reliability Association
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Bremerhaven
Institutes and Institutions:Institute for the Protection of Maritime Infrastructures > Reslience of Maritime Systems
Deposited By: Tecklenburg, Babette
Deposited On:01 Nov 2022 14:58
Last Modified:13 Jan 2023 12:53

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  • A scenario based threat assessment using Bayesian networks for a high voltage direct current converter platform. (deposited 01 Nov 2022 14:58) [Currently Displayed]

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