Source Authentication of Distribution Synchrophasors for Cybersecurity of Microgrids
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Bai, F
Yan, R
Saha, T
Ko, RKL
Liu, Y
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Abstract
This letter proposes a hybrid approach combining Self-Adaptive Mathematical Morphology (SAMM) and Time-Frequency (TF) techniques to authenticate the source information of Distribution Synchrophasors (DS) within near-range locations. The SAMM can adaptively regulate the synchrophasors variations which are representatives of local environmental characteristics. Subsequently, TF mapping is employed to extract informative signatures from the regulated synchrophasors variation. Finally, Random Forest Classification (RFC) is used to correlate the extracted signatures with the source information based on the derived TF mapping. Experiment results using DS collected at multiple small geographical scales validated the proposed methodology.
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IEEE Transactions on Smart Grid
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12
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5
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© 2021 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.
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Electrical engineering
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Electronics, sensors and digital hardware
Distributed computing and systems software
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Cui, Y; Bai, F; Yan, R; Saha, T; Ko, RKL; Liu, Y, Source Authentication of Distribution Synchrophasors for Cybersecurity of Microgrids, IEEE Transactions on Smart Grid, 2021, 12 (5), pp. 4577-4580