3 papers
cs.LG2026
Learning Without Adversarial Training: A Physics-Informed Neural Network for Secure Power System State Estimation under False Data Injection Attacks
Solon Falas, Markos Asprou, Charalambos Konstantinou +1
Power System State Estimation (PSSE) converts geographically distributed measurements into the voltage magnitudes and phase angles needed for grid monitoring and control. Learned e…
cs.LG2025
Robust Power System State Estimation using Physics-Informed Neural Networks
Solon Falas, Markos Asprou, Charalambos Konstantinou +1
Modern power systems face significant challenges in state estimation and real-time monitoring, particularly regarding response speed and accuracy under faulty conditions or cyber-a…
eess.SP2018
Monitoring of Low Voltage Distribution Grid Considering the Neutral Conductor
Andreas Kotsonias, Lenos Hadjidemetriou, Markos Asprou +1
The most widely used method for monitoring Low Voltage Distribution Grids (LVDGs) is the three phase Weighted Least Squares (WLS) State Estimation (SE), which was initially develop…