Physics-informed machine learning for data anomaly detection, classification, localization, and mitigation: A review, challenges, and path forward

MJ Zideh, P Chatterjee, AK Srivastava - IEEE Access, 2023 - ieeexplore.ieee.org
Advancements in digital automation for smart grids have led to the installation of
measurement devices like phasor measurement units (PMUs), micro-PMUs (-PMUs), and …

FDI attack detection using extra trees algorithm and deep learning algorithm-autoencoder in smart grid

SH Majidi, S Hadayeghparast, H Karimipour - International Journal of …, 2022 - Elsevier
Today's smart grid (SG) combines the classical power system with the information
technology, leading to a cyber-physical system (CPS). Its strong dependencies on digital …

[HTML][HTML] Anomaly Detection in Power System State Estimation: Review and New Directions

A Cooper, A Bretas, S Meyn - Energies, 2023 - mdpi.com
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 …

Deep ensemble learning-based approach to real-time power system state estimation

N Bhusal, RM Shukla, M Gautam, M Benidris… - International Journal of …, 2021 - Elsevier
Power system state estimation (PSSE) is commonly formulated as weighted least-square
(WLS) algorithm and solved using iterative methods such as Gauss-Newton methods …

Anomaly detection and classification in power system state estimation: Combining model-based and data-driven methods

S Asefi, M Mitrovic, D Ćetenović, V Levi… - … Energy, Grids and …, 2023 - Elsevier
Power system state estimation is being faced with different types of anomalies. These might
include bad data caused by gross measurement errors or communication system failures …

A tri-level optimization model for power grid defense with the consideration of post-allocated DGs against coordinated cyber-physical attacks

H He, S Huang, Y Liu, T Zhang - International Journal of Electrical Power & …, 2021 - Elsevier
Due to the extensive integration of communication infrastructures, the power grid is
vulnerable to a range of cyber-physical coordinated attacks. To increase the reliability of the …

[HTML][HTML] XTM: A novel transformer and LSTM-based model for detection and localization of formally verified fdi attack in smart grid

A Baul, GC Sarker, PK Sadhu, VP Yanambaka… - Electronics, 2023 - mdpi.com
The modern smart grid (SG) is mainly a cyber-physical system (CPS), combining the
traditional power system infrastructure with information technologies. SG is frequently …

[HTML][HTML] Implementation aspects of smart grids cyber-security cross-layered framework for critical infrastructure operation

D Agnew, N Aljohani, R Mathieu, S Boamah… - Applied Sciences, 2022 - mdpi.com
Communication networks in power systems are a major part of the smart grid paradigm. It
enables and facilitates the automation of power grid operation as well as self-healing in …

Power system anomaly detection and classification utilizing WLS-EKF state estimation and machine learning

S Asefi, M Mitrovic, D Ćetenović, V Levi… - arXiv preprint arXiv …, 2022 - arxiv.org
Power system state estimation is being faced with different types of anomalies. These might
include bad data caused by gross measurement errors or communication system failures …

Cross‐layered distributed data‐driven framework for enhanced smart grid cyber‐physical security

A Starke, K Nagaraj, C Ruben, N Aljohani… - IET Smart …, 2022 - Wiley Online Library
Smart Grid (SG) research and development has drawn much attention from academia,
industry and government due to the great impact it will have on society, economics and the …