Master Thesis Data-Driven Identification and Forecasting of Thermal Flexibility in Residential Heat Pump Systems
Core
Develop an automated end-to-end prototype workflow to identify thermal characteristics from monitoring data and forecast energy consumption and flexibility for residential heat pump systems.
Role type
Master Thesis Researcher (Data-Driven Identification & Forecasting)
Builds
Automated prototype workflow for parameter identification and load forecasting
Domain
Energy Systems / Building Physics / Data Science
Deliverable
production ML models | product features
Required skills
Python, data pipelines, statistical analysis, model benchmarking
Preferred skills
heat pump systems, databases, Neural ODEs
Technologies
Python, Neural ODEs, RC models
Responsibilities
Review existing modeling concepts, analyze empirical field monitoring data, automatically identify thermal parameters, integrate models into forecasting pipelines, validate prototype against measurement data, compare house-level and fleet-level data
Seniority
Master Thesis (6 months)