Source Authentication of Distribution Synchrophasors for Cybersecurity of Microgrids

被引：8

作者：

Cui, Yi ^{[1
]}

Bai, Feifei ^{[1
]}

Yan, Ruifeng ^{[1
]}

Saha, Tapan ^{[1
]}

Ko, Ryan K. L. ^{[1
]}

Liu, Yilu ^{[2
,3
]}

机构：

[1] Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia

[2] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN 37996 USA

[3] Oak Ridge Natl Lab, Oak Ridge, TN 37831 USA

来源：

IEEE TRANSACTIONS ON SMART GRID | 2021年 / 12卷 / 05期

基金：

美国国家科学基金会;

关键词：

Authentication; Feature extraction; Testing; Phasor measurement units; Training; Time-frequency analysis; Data mining; Distribution network; cyber-physical security; synchrophasors; source authentication; NETWORK;

D O I：

10.1109/TSG.2021.3089041

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：4577 / 4580

页数：4

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