Real-world and simulated thermal data from 960 residential multi-zone buildings in Central Europe
For researchers in building energy modeling, this dataset provides a large-scale, diverse resource for transfer learning and benchmarking, though it is incremental as it extends existing data collection efforts.
The paper introduces the ThermBuild dataset, containing real-world measurements from two homes and simulations of 958 building models, with 15-minute resolution data over 15 months to 3 years, designed to support data-driven thermal dynamics modeling for energy-efficient control and fault detection.
This paper presents the ThermBuild dataset, which comprises real-world measurements from two single-family homes and simulations of 958 TRNSYS building models. The buildings cover diverse combinations of air-source heat pump systems, numbers of thermal zones, occupancy profiles, building ages, thermal masses, sizes, orientations, window glazings, five European climates, and ventilation configurations. The dataset contains 15-minute-resolution operational data spanning 15 months for the real-world buildings and 3 years for the simulated buildings. Each building time series includes detailed measurements of heat pump operation, the heating distribution system, the domestic hot water system, weather conditions, and zone-level indoor climate variables. The ThermBuild dataset is designed for data-driven thermal dynamics modeling, thereby supporting the deployment of energy-efficient control, as well as fault detection and diagnosis in buildings. It is particularly suited for transfer learning, generalization modeling, benchmarking, simulation-to-reality transfer, and reproducible thermal modeling research.