The new trend of state estimation: From model-driven to hybrid-driven methods

XB Jin, RJ Robert Jeremiah, TL Su, YT Bai, JL Kong - Sensors, 2021 - mdpi.com
State estimation is widely used in various automated systems, including IoT systems,
unmanned systems, robots, etc. In traditional state estimation, measurement data are …

Research trends and applications of PMUs

G Paramo, A Bretas, S Meyn - Energies, 2022 - mdpi.com
This work is a survey of current trends in applications of PMUs. PMUs have the potential to
solve major problems in the areas of power system estimation, protection, and stability. A …

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 …

Assessment on power systems non-deterministic state estimation algorithms

I Lopez-Ramirez, JE Rodriguez-Seco… - Electric Power Systems …, 2023 - Elsevier
Power systems are operated in a deterministic way. However, the increase in uncertainties
(caused by measurement and communication errors or the absence of complete knowledge …

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 …

Deep Neural Network-Based State Estimator for Transmission System Considering Practical Implementation Challenges

AC Varghese, H Shah, B Azimian, A Pal… - Journal of Modern …, 2024 - ieeexplore.ieee.org
As the phasor measurement unit (PMU) placement problem involves a cost-benefit trade-off,
more PMUs get placed on the higher voltage buses. However, this causes many of the lower …

State estimation in partially observable power systems via graph signal processing tools

L Dabush, A Kroizer, T Routtenberg - Sensors, 2023 - mdpi.com
This paper considers the problem of estimating the states in an unobservable power system,
where the number of measurements is not sufficiently large for conventional state estimation …

A deep learning approach to anomaly sequence detection for high-resolution monitoring of power systems

KR Mestav, X Wang, L Tong - IEEE Transactions on Power …, 2022 - ieeexplore.ieee.org
A deep learning approach is proposed to detect data and system anomalies using high-
resolution continuous point-on-wave (CPOW) or phasor measurements. Both the anomaly …

Universal data anomaly detection via inverse generative adversary network

KR Mestav, L Tong - IEEE Signal Processing Letters, 2020 - ieeexplore.ieee.org
The problem of detecting data anomaly under unknown probability distributions is
considered. Whereas the probability distribution of the anomaly-free data is unknown …

State estimation in unobservable power systems via graph signal processing tools

L Dabush, A Kroizer, T Routtenberg - arXiv preprint arXiv:2106.02254, 2021 - arxiv.org
We consider the problem of estimating the states in an unobservable power system. To this
end, we propose novel graph signal processing (GSP) methods. For simplicity, we start with …