301 citations · 1.2k across the 57 of their papers we have counts for
8 papers · 1 filter
Explainable time-series forecasting with sampling-free SHAP for Transformers
Matthias Hertel, Sebastian Pütz, Ralf Mikut +2
Time-series forecasts are essential for planning and decision-making in many domains. Explainability is key to building user trust and meeting transparency requirements. Shapley Ad…
A Highly Configurable Framework for Large-Scale Thermal Building Data Generation to drive Machine Learning Research
Thomas Krug, Fabian Raisch, Dominik Aimer +5
Data-driven modeling of building thermal dynamics is emerging as an increasingly important field of research for large-scale intelligent building control. However, research in data…
Cyber-Physical Systems on the Megawatt Scale: The impact of battery control on grid frequency stability
Carsten Hartmann, Edoardo De Din, Daniele Carta +9
Electric power systems are undergoing fundamental change. The shift to inverter-based generation challenges frequency stability, while growing digitalisation heightens vulnerabilit…
Real-E: A Foundation Benchmark for Advancing Robust and Generalizable Electricity Forecasting
Chen Shao, Yue Wang, Zhenyi Zhu +5
Energy forecasting is vital for grid reliability and operational efficiency. Although recent advances in time series forecasting have led to progress, existing benchmarks remain li…
BUILDA: A Thermal Building Data Generation Framework for Transfer Learning
Thomas Krug, Fabian Raisch, Dominik Aimer +4
Transfer learning (TL) can improve data-driven modeling of building thermal dynamics. Therefore, many new TL research areas emerge in the field, such as selecting the right source…
Understanding the European energy crisis through structural causal models
Sarah Schreyer, Anton Tausendfreund, Florian Immig +5
Natural gas supplies in Europe were disrupted and energy prices soared in the context of Russia's invasion of Ukraine. Electricity prices in France experienced the largest relative…