3 citations · 5 across the 5 of their papers we have counts for
5 papers
Probabilistic Behavioral Aggregation: A Case Study on the Nordic Power Grid
Anna Büttner, Frank Hellmann
This study applies the Probabilistic Behavioral Tuning (ProBeTune) framework to transient power grid simulations to address challenges posed by increasing grid complexity. ProBeTun…
Projected Neural Differential Equations for Learning Constrained Dynamics
Alistair White, Anna Büttner, Maximilian Gelbrecht +4
Neural differential equations offer a powerful approach for learning dynamical systems from data. However, they do not inherently respect known constraints, such as conservation la…
Complex-Phase, Data-Driven Identification of Grid-Forming Inverter Dynamics
Anna Büttner, Hans Würfel, Sebastian Liemann +2
The increasing integration of renewable energy sources (RESs) into power systems requires the deployment of grid-forming inverters to ensure a stable operation. Accurate modeling o…
Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions
Christian Nauck, Rohan Gorantla, Michael Lindner +3
The geometry of a graph is encoded in dynamical processes on the graph. Many graph neural network (GNN) architectures are inspired by such dynamical systems, typically based on the…
Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning
Christian Nauck, Anna Büttner, Sebastian Liemann +2
Due to the increasing share of renewables, the analysis of the dynamical behavior of power grids gains importance. Effective risk assessments necessitate the analysis of large numb…