Defensive Islanding to Enhance the Resilience of Distribution Systems Against Cyber-Induced Failures

Abdelmalak, Michael; Guatam, Mukesh; Thapa, Jitendra; Hotchkiss, Eliza; Benidris, Mohammed

doi:10.1109/IAS54023.2022.9939864

Title: Defensive Islanding to Enhance the Resilience of Distribution Systems Against Cyber-Induced Failures

Conference · 17 November 2022

DOI:https://doi.org/10.1109/IAS54023.2022.9939864· OSTI ID:1915257

Abdelmalak, Michael; Guatam, Mukesh; Thapa, Jitendra; Hotchkiss, Eliza; Benidris, Mohammed

The extensive integration of communication, computation, and control technologies into cyber-physical power systems (CPPSs) has increased the vulnerabilities of CPPSs to cyberattacks. This calls for developing solutions that assess and reduce the impacts of cyber-induced failures on CPPSs. This paper proposes a defensive islanding strategy to isolate impacted parts of the CPPS and form self-sufficient islanded grids with an objective of minimum load curtailment. The defensive islanding aims to split a power system into smaller grids to improve its resilience against a potential extreme event. A clustering approach that leverages the hierarchical spectral clustering method is utilized for the optimal defensive islanding. The proposed approach captures the fragility behavior and loading conditions of power system components due to cyber-induced failures. A graphical-based coupling framework is used to map the impacts of cyber failures into operation of power system components. The proposed method is demonstrated on a modified 33-node distribution feeder system integrated with distributed energy resources. The amount of load curtailment and radiality constraints have been used to evaluate the performance of the proposed clustering strategies. The results show the capability of the proposed algorithm to create islands considering the cyber-induced failures for enhanced resilience.

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Research Organization:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Organization:: National Science Foundation (NSF)

DOE Contract Number:: AC36-08GO28308

OSTI ID:: 1915257

Report Number(s):: NREL/CP-5R00-85102; MainId:85875; UUID:333275ef-9f1c-46ea-9c4a-bcd185844cfe; MainAdminID:68525

Resource Relation:: Conference: Presented at the 2022 IEEE Industry Applications Society Annual Meeting (IAS), 9-14 October 2022, Detroit, Michigan

Country of Publication:: United States

Language:: English

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