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cs.LG2026
Knowledge Distillation for Efficient Transformer-Based Reinforcement Learning in Hardware-Constrained Energy Management Systems
Pascal Henrich, Jonas Sievers, Maximilian Beichter +3
Transformer-based reinforcement learning has emerged as a strong candidate for sequential control in residential energy management. In particular, the Decision Transformer can lear…
cs.LG2025
Decision-Focused Fine-Tuning of Time Series Foundation Models for Dispatchable Feeder Optimization
Maximilian Beichter, Nils Friederich, Janik Pinter +7
Time series foundation models provide a universal solution for generating forecasts to support optimization problems in energy systems. Those foundation models are typically traine…
cs.LG2024
On autoregressive deep learning models for day-ahead wind power forecasting with irregular shutdowns due to redispatching
Stefan Meisenbacher, Silas Aaron Selzer, Mehdi Dado +6
Renewable energies and their operation are becoming increasingly vital for the stability of electrical power grids since conventional power plants are progressively being displaced…