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Johannes Kruse
Johannes Kruse
PhD student in physics, Forschungszentrum Jülich
Verified email at fz-juelich.de
Title
Cited by
Cited by
Year
Revealing drivers and risks for power grid frequency stability with explainable AI
J Kruse, B Schäfer, D Witthaut
Patterns 2 (11), 100365, 2021
522021
Open database analysis of scaling and spatio-temporal properties of power grid frequencies
L Rydin Gorjão, R Jumar, H Maass, V Hagenmeyer, GC Yalcin, J Kruse, ...
Nature communications 11 (1), 6362, 2020
462020
Predictability of power grid frequency
J Kruse, B Schäfer, D Witthaut
IEEE access 8, 149435-149446, 2020
252020
Secondary control activation analysed and predicted with explainable AI
J Kruse, B Schäfer, D Witthaut
Electric power systems research 212, 108489, 2022
162022
Exploring deterministic frequency deviations with explainable AI
J Kruse, B Schäfer, D Witthaut
2021 IEEE International Conference on Communications, Control, and Computing …, 2021
162021
Pre-processed power grid frequency time series
J Kruse, B Schäfer, D Witthaut
Zenodo https://doi. org/10.5281/zenodo 3744121, 2020
52020
Self-localization of Bose–Einstein condensates in optical lattices
J Kruse, R Fleischmann
Journal of Physics B: Atomic, Molecular and Optical Physics 50 (5), 055002, 2017
52017
Predicting dynamic stability from static features in power grid models using machine learning
M Titz, F Kaiser, J Kruse, D Witthaut
Chaos: An Interdisciplinary Journal of Nonlinear Science 34 (1), 2024
42024
Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI
S Pütz, B Schäfer, D Witthaut, J Kruse
Energy Informatics 5 (Suppl 4), 46, 2022
42022
Physics-Informed Machine Learning for Power Grid Frequency Modeling
J Kruse, E Cramer, B Schäfer, D Witthaut
PRX energy 2 (4), 043003, 2023
3*2023
Regulatory Changes in German and Austrian Power Systems Explored with Explainable Artificial Intelligence
S Pütz, J Kruse, D Witthaut, V Hagenmeyer, B Schäfer
Companion Proceedings of the 14th ACM International Conference on Future …, 2023
2023
Machine learning of power grid frequency dynamics and control: prediction, explanation and stochastic modelling
J Kruse
Universität zu Köln, 2023
2023
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