6 papers
Data-Driven Active Power Flow Modeling: A Behavioral Systems Approach
Sebastian Otzen, Hannes M. H. Wolf, Christian A. Hans
The increasing decentralization of power systems driven by a large number of renewable energy sources poses challenges in power flow optimization: Partially unknown power line prop…
Graph Neural Ordinary Differential Equations for Power System Identification
Hannes M. H. Wolf, Christian A. Hans
With the shift towards decentralized energy generation, the increasing complexity of power systems renders physics-based modeling challenging. At the same time the growing amount o…
Experimental Characterisation of Distributed Reactive Power Sharing under Communication-Induced Stress in Parallel Grid-Forming Inverters
E. D. Gomez Anccas, E. A. MacPherson, J. Tegeler +4
Synchronisation of parallel grid-forming inverters is crucial for stable operation of future power systems. This includes accurate and robust reactive power sharing under realistic…
Augmented Neural Ordinary Differential Equations for Power System Identification
Hannes M. H. Wolf, Christian A. Hans
Due the complexity of modern power systems, modeling based on first-order principles becomes increasingly difficult. As an alternative, dynamical models for simulation and control…
Identification of Power Systems with Droop-Controlled Units Using Neural Ordinary Differential Equations
Hannes M. H. Wolf, Christian A. Hans
In future power systems, the detailed structure and dynamics may not always be fully known. This is due to an increasing number of distributed energy resources, such as photovoltai…
Data-driven model predictive control of battery storage units
Johannes B. Lipka, Christian A. Hans
In many state-of-the-art control approaches for power systems with storage units, an explicit model of the storage dynamics is required. With growing numbers of storage units, iden…