Data-Driven Thermal Flexibility Thesis for Residential Heat Pumps

About the role

This Master's thesis focuses on the automated estimation and forecasting of the flexibility potential of residential heat‑pump systems. You will investigate how thermal characteristics and storage capacities can be identified from monitoring data and used to quantify the flexibility that a heat‑pump system can provide.

Key responsibilities

• Review existing approaches, analyse field monitoring data and define suitable data‑processing workflows.
• Identify key thermal parameters of buildings and storage systems and estimate available flexibility over time.
• Integrate the developed models into a flexibility‑forecasting workflow and evaluate performance using real‑world data.
• Extend and validate an end‑to‑end workflow covering data preprocessing, system characterization, storage‑capacity estimation, flexibility estimation and analysis of individual and aggregated fleets.

Required profile

• Enrolled in a Master’s program in Computer Science or a comparable field.
• Business‑fluent in German and English.
• Reliable, curious and self‑motivated with a willingness to learn new concepts.

Required skills

• Python programming.
• Experience with databases (advantageous).
• Knowledge of heat‑pump systems (advantageous).