7 citations · 14 across the 10 of their papers we have counts for
3 papers · 1 filter
To Learn or Not to Learn: A Litmus Test for Using Reinforcement Learning in Control
Victor Schulte, Michael Eichelbeck, Matthias Althoff
Reinforcement learning (RL) can be a powerful alternative to classical control methods when standard model-based control is insufficient, e.g., when deriving a suitable model is in…
CommonPower: A Framework for Safe Data-Driven Smart Grid Control
Michael Eichelbeck, Hannah Markgraf, Matthias Althoff
The growing complexity of power system management has led to an increased interest in reinforcement learning (RL). To validate their effectiveness, RL algorithms have to be evaluat…
Contingency-constrained economic dispatch with safe reinforcement learning
Michael Eichelbeck, Hannah Markgraf, Matthias Althoff
Future power systems will rely heavily on micro grids with a high share of decentralised renewable energy sources and energy storage systems. The high complexity and uncertainty in…