Dynamic functional connectivity graph for assessing cascading events in power system
Ahmad, Tabia and Papadopoulos, Panagiotis N. (2024) Dynamic functional connectivity graph for assessing cascading events in power system. Electric Power Systems Research, 235. 110724. ISSN 0378-7796 (https://doi.org/10.1016/j.epsr.2024.110724)
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Abstract
During power system cascading disturbances it becomes crucial to quickly identify the vulnerable transmission interconnections. Understanding the impact of a triggering outage on these critical interconnections is important for enhancing situational awareness and taking targeted control actions. This paper proposes a new machine learning (ML) based graph-theoretic approach for learning the dynamic functional connectivity (DFC) between power system buses with respect to their vulnerability to cascading failures (CF). The learnt DFC graph is then used to characterise vulnerable regions of the power-system using complex network theory based indices. A key feature of the proposed DFC graph is that it takes into account detailed power system dynamics and the action of protection devices when deriving the DFC, going beyond a static representation of the power system graph based on electrical admittances. Multiple operational scenarios for load and renewable generation are also considered when doing so. The proposed algorithm is validated for a dynamic model of the IEEE-10 machine 39 bus system with Type IV wind generation.
ORCID iDs
Ahmad, Tabia and Papadopoulos, Panagiotis N. ORCID: https://orcid.org/0000-0001-7343-2590;-
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Item type: Article ID code: 89900 Dates: DateEvent31 October 2024Published1 July 2024Published Online17 June 2024Accepted28 September 2023SubmittedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering
Technology > Electrical engineering. Electronics Nuclear engineering > Production of electric energy or powerDepartment: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 10 Jul 2024 11:57 Last modified: 26 Sep 2024 13:20 URI: https://strathprints.strath.ac.uk/id/eprint/89900