Iterative learning control in prosumer-based microgrids with hierarchical control. - Lia Strenge; Xiaohan Jing; Ruth Boersma; Paul Schultz; Frank Hellmann; Jürgen Kurths; Jörg Raisch; Thomas Seel (CoRR, 2020)

A multilayer, multi-timescale model approach for economic and frequency control in power grids. - Lia Strenge; Paul Schultz; Jürgen Kurths; Jörg Raisch; Frank Hellmann (CoRR, 2020)

NetworkDynamics.jl - Composing and simulating complex networks in Julia. - Michael Lindner; Lucas Lincoln; Fenja Drauschke; Julia Monika Koulen; Hans Würfel; Anton Plietzsch; Frank Hellmann (CoRR, 2020)

A normal form for grid forming power grid components. - Raphael Kogler; Anton Plietzsch; Paul Schultz; Frank Hellmann (CoRR, 2021)

Probabilistic Stability Assessment for Active Distribution Grids. - Sebastian Liemann; Lia Strenge; Paul Schultz; Holm Hinners; Johannis Porst; Marcel Sarstedt; Frank Hellmann (CoRR, 2021)

Predicting Dynamic Stability of Power Grids using Graph Neural Networks. - Christian Nauck; Michael Lindner; Konstantin Schürholt; Haoming Zhang; Paul Schultz; Jürgen Kurths; Ingrid Isenhardt; Frank Hellmann (CoRR, 2021)

Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems. - Frank Hellmann; Ekaterina Zolotarevskaia; Jürgen Kurths; Jörg Raisch (CoRR, 2021)

An Open Source Software Stack for Tuning the Dynamical Behavior of Complex Power Systems. - Anna Büttner; Hans Würfel; Anton Plietzsch; Michael Lindner; Frank Hellmann (OSMSES, 2022)

Dynamic stability of power grids - new datasets for Graph Neural Networks. - Christian Nauck; Michael Lindner; Konstantin Schürholt; Frank Hellmann (CoRR, 2022)

Towards dynamic stability analysis of sustainable power grids using graph neural networks. - Christian Nauck; Michael Lindner; Konstantin Schürholt; Frank Hellmann (CoRR, 2022)

PowerDynamics.jl - An experimentally validated open-source package for the dynamical analysis of power grids. - Anton Plietzsch; Raphael Kogler; Sabine Auer; Julia Merino; Asier Gil-de-Muro; Jan Liße; Christina Vogel; Frank Hellmann (SoftwareX, 2022)

Spike Spectra for Recurrences. - K. Hauke Kraemer; Frank Hellmann; Mehrnaz Anvari; Jürgen Kurths; Norbert Marwan (Entropy, 2022)

Predicting Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning. - Christian Nauck; Michael Lindner; Nora Molkenthin; Jürgen Kurths; Eckehard Schöll; Jörg Raisch; Frank Hellmann (CoRR, 2024)

Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning. - Christian Nauck; Anna Büttner; Sebastian Liemann; Frank Hellmann; Michael Lindner (CoRR, 2024)

Dirac-Bianconi Graph Neural Networks - Enabling Non-Diffusive Long-Range Graph Predictions. - Christian Nauck; Rohan Gorantla; Michael Lindner; Konstantin Schürholt; Antonia S. J. S. Mey; Frank Hellmann (CoRR, 2024)

Complex-Phase, Data-Driven Identification of Grid-Forming Inverter Dynamics. - Anna Büttner; Hans Würfel; Sebastian Liemann; Johannes Schiffer; Frank Hellmann (CoRR, 2024)

Projected Neural Differential Equations for Learning Constrained Dynamics. - Alistair White; Anna Büttner; Maximilian Gelbrecht; Valentin Duruisseaux; Niki Kilbertus; Frank Hellmann; Niklas Boers (CoRR, 2024)

Small-signal stability of power systems with voltage droop. - Jakob Niehues; Robin Delabays; Frank Hellmann (CoRR, 2024)

Probabilistic Behavioral Aggregation: A Case Study on the Nordic Power Grid. - Anna Büttner; Frank Hellmann (CoRR, 2024)

Complex Phase Analysis of Power Grid Dynamics. - Jakob Niehues; Anna Büttner; Anne Riegler; Frank Hellmann (CoRR, 2025)