[HTML][HTML] A framework for synthetic power system dynamics

A Büttner, A Plietzsch, M Anvari… - … Interdisciplinary Journal of …, 2023 - pubs.aip.org
We present a modular framework for generating synthetic power grids that consider the
heterogeneity of real power grid dynamics but remain simple and tractable. This enables the …

Predicting Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning

C Nauck, M Lindner, N Molkenthin, J Kurths… - arxiv preprint arxiv …, 2024 - arxiv.org
A central question of network science is how functional properties of systems arise from their
structure. For networked dynamical systems, structure is typically quantified with network …

Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning

C Nauck, A Büttner, S Liemann, F Hellmann… - arxiv preprint arxiv …, 2024 - arxiv.org
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 number …

[KIRJA][B] Applying modeling, simulation and machine learning for the renewable energy transition

M Lindner - 2023 - search.proquest.com
Mitigating climate change and reducing emissions of greenhouse gases to net-zero by mid-
century is a huge global challenge. The renewable energy transition is one of the key pillars …