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Power grid surveillance: Topology change detection system using power line communications

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journal contribution
submitted on 2024-08-14, 10:20 and posted on 2024-08-14, 10:21 authored by Javier Hernandez Fernandez, Aymen Omri, Roberto Di Pietro

This paper proposes an efficient channel impulse response (CIR)-based technique to detect topology changes in the power grid. The features of the proposed approach include the following aspects: (i) it is a software-only solution, not requiring any intervention on the current smart grid architecture; (ii) topology changes can be detected via a simple distributed algorithm that requires only local communications; and, (iii) both memory and computational footprints of the proposed solution are minimal. The above-mentioned features make this contribution notably appealing for the resource-constrained smart grid domain. Furthermore, the paper provides a detailed discussion of the introduced technique, accompanied by an implementation reflecting a realistic use case, and presents an extensive simulation campaign to show the quality and viability of the proposed approach. A unique feature of our solution is that it performs well even when the communication channel is affected by a high noise level. For instance, with noise levels below 100 dB μ V (the typical PLC noise power range), the proposed solution showed a ≈ 100 % detection rate. To the best of our knowledge, our solution is the first one proposing a fully CIR-based, distributed, deterministic algorithm for intrusion detection and localization. We believe that the performance and advantages of the proposed technique pave the way for further smart grid applications and solutions.

Other Information

Published in: International Journal of Electrical Power & Energy Systems
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.ijepes.2022.108634

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU
  • Iberdrola Innovation Middle East QSTP LLC