Real-world and simulated thermal data from 960 residential multi-zone buildings in Central Europe
2026-06-01 • Databases
Databases
AI summaryⓘ
The authors created the ThermBuild dataset, which includes detailed heating and climate data from two real houses and nearly a thousand simulated buildings across Europe. The data covers various building features like heat pumps, room setups, and weather conditions collected every 15 minutes over months or years. This dataset is meant to help researchers build better models for managing building temperatures more efficiently and detecting problems early. It is useful for training and testing algorithms that work with different buildings and climates.
Thermal dynamicsHeat pumpsBuilding simulationTRNSYSTransfer learningEnergy efficiencyFault detectionIndoor climateThermal zonesVentilation
Authors
Fabian Raisch, Matthias Kersken, Markus Male, Benjamin Tischler
Abstract
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.