An unsupervised cyberattack detection scheme for AC microgrids using Gaussian process regression and one‐class support vector machine anomaly detection

An unsupervised cyberattack detection scheme for AC microgrids using Gaussian process regression and one‐class support vector machine anomaly detection

Abstract This paper addresses the cybersecurity of hierarchical control of AC microgrids with distributed secondary control. The false data injection (FDI) cyberattack is assumed to alter the operating frequency of inverter‐based distributed generators (DGs) in an islanded microgrid. For the microgr...

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Bibliographic Details
Main Authors: Jeewon Choi, Behshad Roshanzadeh, Manel Martínez‐Ramón, Ali Bidram
Format: Article
Language:English
Published: Wiley 2023-06-01
Series:IET Renewable Power Generation
Subjects:
cyber‐physical systems
distributed control
Gaussian processes
microgrids
support vector machines
Online Access:https://doi.org/10.1049/rpg2.12753

Internet

https://doi.org/10.1049/rpg2.12753

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