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[HTML][HTML] A framework for synthetic power system dynamics
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 …
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
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 …
structure. For networked dynamical systems, structure is typically quantified with network …
Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning
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 …
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 …
century is a huge global challenge. The renewable energy transition is one of the key pillars …