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…
cs.LG2023
Physics-Informed Neural Networks for Accelerating Power System State Estimation
Solon Falas, Markos Asprou, Charalambos Konstantinou +1
State estimation is the cornerstone of the power system control center since it provides the operating condition of the system in consecutive time intervals. This work investigates…