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Towards a Model for Assessing the Effects of Social-Cyber-Physical Threats on the Future Power Grid - Review and Workshop Results
School of Marketing and Communication and VEBIC, University of Vaasa, Vaasa, Finland.
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0002-3809-3156
University of Vaasa, Digital Economy Research Platform, Vaasa, Finland.
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electromagnetic Engineering and Fusion Science.ORCID iD: 0000-0002-2964-7233
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2024 (English)In: 2024 International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation, AIE 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024Conference paper, Published paper (Refereed)
Abstract [en]

The energy system, including the electrical power system, is currently undergoing major changes to meet increased demands and climate target plans, and to stand against potential malicious activities and all sorts of disruptions. Specifically, the electrical power system is drastically changing with regards to consumption, production, transmission, control, monitoring, markets, and digitalization. Such a change, however, makes the power system an attractive and vulnerable target to all kinds of disruptive events and social-cyber-physical attacks since the system is crucial for the functioning of the society and economy. In this work, to act against such events and to study the future power system's susceptibility and resilience towards social-cyber-physical attacks, the Resilient Digital Sustainable Energy Transition (REDISET) project has shown the need for a new model that is able to describe the future electrical power system in a way that reflects the future reality. In this paper, existing power system models, the changing landscape of power systems, the drivers for a new model, the suggested model that comprises 7 building blocks instead of today's 3, and finally a direction of future related work are presented.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024.
Keywords [en]
Power Grid, Resilience, Social-cyber-physical Threats
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-350715DOI: 10.1109/AIE61866.2024.10561312ISI: 001265777700009Scopus ID: 2-s2.0-85197885404OAI: oai:DiVA.org:kth-350715DiVA, id: diva2:1884681
Conference
2024 International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation, AIE 2024, Vaasa, Finland, May 20 2024 - May 22 2024
Note

Part of ISBN 9798350364965

QC 20240719

Available from: 2024-07-17 Created: 2024-07-17 Last updated: 2024-09-05Bibliographically approved

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Berlijn, Sonja MonicaHilber, PatrikXu, Qianwen

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