Cybersecurity Enhancement of Transformer Differential Protection Using Machine Learning

Jahromi, MZ, Jahromi, AA, Sanner, S et al. (2 more authors) (2020) Cybersecurity Enhancement of Transformer Differential Protection Using Machine Learning. In: 2020 IEEE Power & Energy Society General Meeting (PESGM). 2020 IEEE Power & Energy Society General Meeting (PESGM), 02-06 Aug 2020, Montreal, QC, Canada. IEEE . ISBN 978-1-7281-5509-8

Abstract

Metadata

Authors/Creators:
  • Jahromi, MZ
  • Jahromi, AA
  • Sanner, S
  • Kundur, D
  • Kassouf, M
Copyright, Publisher and Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Cyberphysical systems, operational technology, machine learning, differential protective relays, transformers
Dates:
  • Published: 2 August 2020
  • Accepted: 17 February 2020
  • Published (online): 16 December 2020
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 27 Jan 2021 13:55
Last Modified: 29 Jan 2021 16:17
Status: Published
Publisher: IEEE
Identification Number: https://doi.org/10.1109/pesgm41954.2020.9282161

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