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Title: Anomaly Detection in Power System State Estimation: Review and New Directions
Foundational and state-of-the-art anomaly-detection methods through power system state estimation are reviewed. Traditional components for bad data detection, such as chi-square testing, residual-based methods, and hypothesis testing, are discussed to explain the motivations for recent anomaly-detection methods given the increasing complexity of power grids, energy management systems, and cyber-threats. In particular, state estimation anomaly detection based on data-driven quickest-change detection and artificial intelligence are discussed, and directions for research are suggested with particular emphasis on considerations of the future smart grid.  more » « less
Award ID(s):
1935389
NSF-PAR ID:
10477042
Author(s) / Creator(s):
; ;
Publisher / Repository:
Energies
Date Published:
Journal Name:
Energies
Volume:
16
Issue:
18
ISSN:
1996-1073
Page Range / eLocation ID:
6678
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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