Masterarbeit: Datengetriebene Identifikation und Prognose der thermischen Flexibilität in Wärmepumpensystemen für Wohngebäude (w/m/div.)
Core
Develop an automated end-to-end workflow to identify thermal properties of heat pump systems in residential buildings from monitoring data and integrate them into forecasting pipelines to estimate energy consumption and available thermal flexibility.
Role type
Master's thesis researcher (data-driven thermal modeling & forecasting)
Builds
Automated prototype workflow for thermal parameter identification and flexibility forecasting
Domain
Energy systems / Building automation / Data science
Deliverable
production ML models
Required skills
Python, database management, thermal system modeling, statistical analysis, neural ordinary differential equations (Neural ODEs)
Preferred skills
knowledge of heat pump systems, benchmarking methodologies
Technologies
Python, Neural ODEs, monitoring data pipelines
Responsibilities
Analyze empirical field monitoring data to define data pipelines and quality criteria; automatically identify building- and storage-specific thermal parameters; integrate parameterized models into forecasting pipelines; validate the prototype using measurement data; benchmark identification methods (e.g., RC models vs. Neural ODEs).