Data-Driven Cyberphysical Anomaly Detection for Microgrids With GFM Inverters

Data-Driven Cyberphysical Anomaly Detection for Microgrids With GFM Inverters

Microgrids (MGs) have gained significant attention considering their enhanced capability to integrate increasing distributed energy resources (DERs). The application of grid forming (GFM) inverters in a MG can control voltage/frequency, enable both islanded and grid-connected operation, and achieve...

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Bibliographic Details
Main Authors: Xiaorui Liu, Hui Li
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of Power Electronics
Subjects:
Anomaly detection and classification
cyberphysical security
data-driven
FDIAs
GFM inverters
HIFs
Online Access:https://ieeexplore.ieee.org/document/10168219/

Internet

https://ieeexplore.ieee.org/document/10168219/

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