7 papers
Averaging favors MPC: How typical evaluation setups overstate MPC performance for residential battery scheduling
Janik Pinter, Maximilian Beichter, Ralf Mikut +2
Residential prosumers with PV-battery systems increasingly manage their electricity exchange with the power grid to minimize costs. This study investigates the performance of Model…
LeDiFlow: Learned Distribution-guided Flow Matching to Accelerate Image Generation
Pascal Zwick, Nils Friederich, Maximilian Beichter +3
Enhancing the efficiency of high-quality image generation using Diffusion Models (DMs) is a significant challenge due to the iterative nature of the process. Flow Matching (FM) is…
EAP4EMSIG -- Enhancing Event-Driven Microscopy for Microfluidic Single-Cell Analysis
Nils Friederich, Angelo Jovin Yamachui Sitcheu, Annika Nassal +12
Microfluidic Live-Cell Imaging (MLCI) yields data on microbial cell factories. However, continuous acquisition is challenging as high-throughput experiments often lack real-time in…
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…
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…
Probabilistic Day-Ahead Battery Scheduling based on Mixed Random Variables for Enhanced Grid Operation
Janik Pinter, Frederik Zahn, Maximilian Beichter +2
The increasing penetration of renewable energy sources introduces significant challenges to power grid stability, primarily due to their inherent variability. A new opportunity for…