1.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of KasselDE13 papers
- AIT Austrian Institute of Technology GmbHAT7 papers
- National Technical University of AthensGR6 papers
- Delft University of TechnologyNL5 papers
- Technical University of DenmarkDK5 papers
- European Distributed Energy Resources LaboratoriesDE4 papers
- Oldenburger Institut für InformatikDE4 papers
- University of StrathclydeGB4 papers
- HAW HamburgDE3 papers
- Laboratoire de Génie Électrique de GrenobleFR3 papers
- Tennet (Netherlands)NL3 papers
- Université Grenoble AlpesFR3 papers
6 papers · 1 filter
Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach
Mohamed Hassouna, Clara Holzhüter, Malte Lehna +4
The rising proportion of renewable energy in the electricity mix introduces significant operational challenges for power grid operators. Effective power grid management demands ada…
Graph Reinforcement Learning for Power Grids: A Comprehensive Survey
Mohamed Hassouna, Clara Holzhüter, Pawel Lytaev +3
The increasing share of renewable energy and distributed electricity generation requires the development of deep learning approaches to address the lack of flexibility inherent in…
CARE to Compare: A real-world dataset for anomaly detection in wind turbine data
Christian Gück, Cyriana M. A. Roelofs, Stefan Faulstich
Anomaly detection plays a crucial role in the field of predictive maintenance for wind turbines, yet the comparison of different algorithms poses a difficult task because domain sp…
Transfer learning applications for anomaly detection in wind turbines
Cyriana M. A. Roelofs, Christian Gück, Stefan Faulstich
Anomaly detection in wind turbines typically involves using normal behaviour models to detect faults early. However, training autoencoder models for each turbine is time-consuming…
Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents
Malte Lehna, Jan Viebahn, Christoph Scholz +2
The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production. As a consequence, active grid manage…
A Reinforcement Learning Approach for the Continuous Electricity Market of Germany: Trading from the Perspective of a Wind Park Operator
Malte Lehna, Björn Hoppmann, René Heinrich +1
With the rising extension of renewable energies, the intraday electricity markets have recorded a growing popularity amongst traders as well as electric utilities to cope with the…