1 citations · 1 across the 3 of their papers we have counts for
3 papers
Scalability and Sample Efficiency Analysis of Graph Neural Networks for Power System State Estimation
Ognjen Kundacina, Gorana Gojic, Mirsad Cosovic +2
Data-driven state estimation (SE) is becoming increasingly important in modern power systems, as it allows for more efficient analysis of system behaviour using real-time measureme…
Near Real-Time Distributed State Estimation via AI/ML-Empowered 5G Networks
Ognjen Kundacina, Miodrag Forcan, Mirsad Cosovic +5
Fifth-Generation (5G) networks have a potential to accelerate power system transition to a flexible, softwarized, data-driven, and intelligent grid. With their evolving support for…
Distributed Nonlinear State Estimation in Electric Power Systems using Graph Neural Networks
Ognjen Kundacina, Mirsad Cosovic, Dragisa Miskovic +1
Nonlinear state estimation (SE), with the goal of estimating complex bus voltages based on all types of measurements available in the power system, is usually solved using the iter…