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

Javier Hernandez Fernandez, Aymen Omri, Roberto Di Pietro

2022International Journal of Electrical Power & Energy Systems21 citationsDOIOpen Access PDF

Abstract

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 dBμV (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.

Topics & Concepts

Smart gridComputer scienceGridNoise (video)Topology (electrical circuits)Network topologyDistributed computingReal-time computingElectronic engineeringEngineeringComputer networkElectrical engineeringArtificial intelligenceMathematicsImage (mathematics)GeometryPower Line Communications and NoiseSmart Grid Security and ResilienceSmart Grid Energy Management
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