A State Partition Particle Filter based Approach for Detection of Switching Attack

Conference Paper (2024)
Author(s)

Seema Yadav (Motilal Nehru National Institute of Technology)

Nand Kishor (Østfold University College)

Shubhi Purwar (Motilal Nehru National Institute of Technology)

Vetrivel Subramaniam Rajkumar (TU Delft - Intelligent Electrical Power Grids)

Alex Stefanov (TU Delft - Intelligent Electrical Power Grids)

Research Group
Intelligent Electrical Power Grids
DOI related publication
https://doi.org/10.1109/SmartGridComm60555.2024.10738041
More Info
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Publication Year
2024
Language
English
Research Group
Intelligent Electrical Power Grids
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
135-140
ISBN (print)
979-8-3503-1856-2
ISBN (electronic)
979-8-3503-1855-5
Reuse Rights

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Abstract

The increasing risk of cyber-physical attacks (CPAs) on power infrastructure has led to need for reliable detection technologies. As the landscape of cyber threats evolves, it becomes imperative to continually update and enhance attack detection techniques. This research investigates the formulation of detection algorithm, via combination of State Partition Particle Filter (SP-PF) theories for power system security. The proposed approach applies intelligent partitioning of the state space so as to be accurately represented with fewer particles. This reduction in computational demand enhances the algorithm’s efficiency, making it more practical for real-time applications. The detection algorithm based on SP-PF is tested against switching attacks (SAs) launched on the governor and excitation systems associated with the generator. The RTDS platform is utilized for conducting real-time simulations of IEEE 9-bus power network in order to demonstrate the efficacy of proposed SP-PF based detection SA in real-time.

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