4 papers · 1 filter
Physics-Informed Neural Networks for Non-linear System Identification for Power System Dynamics
Jochen Stiasny, George S. Misyris, Spyros Chatzivasileiadis
Varying power-infeed from converter-based generation units introduces great uncertainty on system parameters such as inertia and damping. As a consequence, system operators face in…
Multi-Terminal DC Fault Identification for MMC-HVDC Systems based on Modal Analysis -- A Localized Protection Scheme
Vaibhav Nougain, Sukumar Mishra, George S. Misyris +1
We propose a localized protection scheme based on modal analysis in multi-terminal modular multilevel converter (MMC) based high voltage DC (HVDC) systems. The paper addresses the…
Neural Networks for Encoding Dynamic Security-Constrained Optimal Power Flow
Ilgiz Murzakhanov, Andreas Venzke, George S. Misyris +1
This paper introduces a framework to capture previously intractable optimization constraints and transform them to a mixed-integer linear program, through the use of neural network…
Physics-Informed Neural Networks for Power Systems
George S. Misyris, Andreas Venzke, Spyros Chatzivasileiadis
This paper introduces for the first time, to our knowledge, a framework for physics-informed neural networks in power system applications. Exploiting the underlying physical laws g…