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arxiv: 2606.01994 · v2 · pith:T4E73EWBnew · submitted 2026-06-01 · 💻 cs.DB

Real-world and simulated thermal data from 960 residential multi-zone buildings in Central Europe

Fabian Raisch , Matthias Kersken , Markus Male , Benjamin Tischler This is my paper

Pith reviewed 2026-06-28 12:14 UTC · model grok-4.3

classification 💻 cs.DB
keywords ThermBuild datasetthermal dynamics modelingheat pump systemsbuilding energy dataTRNSYS simulationsresidential thermal zonesfault detectiondata-driven control
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The pith

The ThermBuild dataset supplies real measurements from two homes and simulations from 958 buildings to support thermal dynamics modeling for heat pumps.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents the ThermBuild dataset, which includes 15-minute resolution data from two real single-family homes over 15 months and from 958 simulated TRNSYS models over 3 years. The buildings vary across air-source heat pump systems, zone counts, occupancy, ages, thermal masses, sizes, orientations, glazings, five European climates, and ventilation setups. Each time series covers heat pump operation, heating and hot water systems, weather, and indoor climate variables. The dataset is positioned to enable data-driven modeling that can improve building energy control and support fault detection. A sympathetic reader would see value in having a large, varied collection for developing models that work across real and simulated conditions.

Core claim

The ThermBuild dataset comprises real-world measurements from two single-family homes and simulations of 958 TRNSYS building models covering 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, with each building time series including detailed measurements of heat pump operation, the heating distribution system, the domestic hot water system, weather conditions, and zone-level

What carries the argument

The ThermBuild dataset of real and TRNSYS-simulated multi-zone residential building time series with heat pump and climate variables at 15-minute resolution.

If this is right

  • The data supports development of energy-efficient control strategies for residential heat pump systems.
  • It enables fault detection and diagnosis algorithms that operate on zone-level and system-level measurements.
  • The mix of real and simulated records facilitates transfer learning and simulation-to-reality model adaptation.
  • Researchers can use the collection for benchmarking and generalization testing across climates and building configurations.
  • The resource promotes reproducible experiments in thermal modeling of multi-zone buildings.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Models trained on this dataset could be tested for robustness by applying them to buildings in climates outside the five European ones included.
  • The real-simulated pairing offers a natural testbed for techniques that quantify and reduce the gap between simulation and field performance in energy systems.
  • Patterns extracted from the 960-building collection might identify which building parameters most influence heat pump efficiency, guiding targeted retrofits.
  • Extending the dataset with newer construction standards or different heating technologies would allow direct comparison of modeling accuracy across eras.

Load-bearing premise

The 958 TRNSYS simulations accurately capture real thermal dynamics and heat pump behavior across the described variations in building age, thermal mass, climate, and ventilation.

What would settle it

Direct comparison of key thermal response metrics such as zone temperature trajectories or heat pump power draw under identical weather inputs between the simulated models and additional real measurements from comparable unmodeled buildings.

Figures

Figures reproduced from arXiv: 2606.01994 by Benjamin Tischler, Fabian Raisch, Markus Male, Matthias Kersken.

Figure 1
Figure 1. Figure 1: Fraunhofer IBP TwinHouse test site near Holzkirchen (Germany) and installed heat pump system [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Floor plan of the ground floor (left) and the attic (right) of the TwinHouses, including the indication of open and closed doors as well as the supply and extract air positions for the mechanical ventilation system. floor and the attic [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Building service equipment installation. convective-radiative split of approximately 50%. For the occupancy profiles, we used the Occdem software 27 . Further information on software usage and occupancy will be provided in Section 2.2.2. The setpoint temperatures in both houses are set to 20 °C for all rooms with no night setback. The buildings are equipped with a mechanical ventilation system operating at… view at source ↗
Figure 4
Figure 4. Figure 4: These parameters were selected because they most strongly influence the thermal dynamic behavior of [PITH_FULL_IMAGE:figures/full_fig_p004_4.png] view at source ↗
Figure 4
Figure 4. Figure 4: Overview of the simulation study variations. A total of 1,080 systematic building configurations were generated, while parameters marked as random selection were assigned individually for each simulation case. 2.2.1 Building properties The varied building properties include building size, building age, thermal mass, window glazing, number of rooms, and orientation. Size The size of the building influences … view at source ↗
Figure 5
Figure 5. Figure 5: Schematic representation of the instrumentation concept for the heating case. 4 Technical Validation We validated the dataset using several methods. Section 4.1 describes the sensor validation of the real-world data. For the simulated data, we follow the recommendations of 36 and applied two validation approaches: (1) comparison of the simulated data with real-world data, as presented in Section 4.2, and (… view at source ↗
Figure 6
Figure 6. Figure 6: Comparison of simulation data to real-world TwinHouse data. positioning, (iii) differences between on-site micro-climatic conditions and the meteorological input data, and (iv) variations in actual infiltration rates compared to model assumptions. The deviations could potentially be reduced through parameter optimization. However, this step was intentionally omitted because the objective of the dataset is … view at source ↗
Figure 7
Figure 7. Figure 7: Scatter plot analysis of simulation results on building level using two measurement variables and one varied parameter. 12 [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Scatter plot analysis of simulation results for the living room. 5 Data Availability The ThermBuild dataset is available at https://fordatis.fraunhofer.de/handle/fordatis/486 35. The dataset contains real-world measurements from the two TwinHouses over 15 months, including raw measurements, gap￾filled measurements generated using the kNN imputation method, and additional room temperature measurement data. … view at source ↗
read the original 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.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript presents the ThermBuild dataset, comprising 15-minute resolution operational data from two real single-family homes (15 months) and 958 TRNSYS-simulated multi-zone residential buildings (3 years). The buildings span diverse 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. Each time series includes heat pump operation, heating distribution system, domestic hot water system, weather conditions, and zone-level indoor climate variables. The dataset is positioned to support data-driven thermal dynamics modeling for energy-efficient control, fault detection and diagnosis, transfer learning, generalization, benchmarking, and simulation-to-reality transfer.

Significance. If the TRNSYS simulations faithfully reproduce real thermal dynamics and heat pump behavior, the scale and diversity of the dataset would provide a valuable resource for training robust data-driven models in building energy management, enabling better generalization across Central European residential stock and supporting reproducible research on sim-to-reality transfer. The inclusion of both real and simulated data is a strength for benchmarking purposes.

major comments (2)
  1. [Abstract] Abstract: The central claim that the dataset supports 'simulation-to-reality transfer' and 'generalization modeling' requires that the 958 TRNSYS models accurately capture real thermal dynamics across the stated parameter ranges; however, no validation against the two measured homes (e.g., quantitative comparison of heat pump COP, zone temperatures, or energy consumption for comparable configurations) is described.
  2. [Abstract] Dataset description (implied by abstract claims): With ground truth limited to two single-family homes, the absence of error characterization, fidelity metrics, or sensitivity analysis for the simulated buildings undermines the utility for fault detection and data-driven control across varied ages, thermal masses, climates, and ventilation configurations.
minor comments (1)
  1. [Title] Title states '960 residential multi-zone buildings' while the abstract describes two real homes plus 958 simulated models; the manuscript should explicitly state the total count and whether the real homes are included in the 960.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback on the ThermBuild dataset manuscript. We address each major comment below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The central claim that the dataset supports 'simulation-to-reality transfer' and 'generalization modeling' requires that the 958 TRNSYS models accurately capture real thermal dynamics across the stated parameter ranges; however, no validation against the two measured homes (e.g., quantitative comparison of heat pump COP, zone temperatures, or energy consumption for comparable configurations) is described.

    Authors: We agree that the manuscript does not include quantitative validation of the TRNSYS models against the two real homes. The paper presents a dataset resource containing both real and simulated data to enable community research on simulation-to-reality transfer and generalization; it does not claim to have performed such validation itself. We will revise the abstract to clarify the dataset's intended use cases without overstating demonstrated fidelity, and add a limitations discussion on the parameterization approach. revision: yes

  2. Referee: [Abstract] Dataset description (implied by abstract claims): With ground truth limited to two single-family homes, the absence of error characterization, fidelity metrics, or sensitivity analysis for the simulated buildings undermines the utility for fault detection and data-driven control across varied ages, thermal masses, climates, and ventilation configurations.

    Authors: The limited real-world ground truth (two homes) is a factual constraint of the dataset. The 958 simulations were generated using TRNSYS models parameterized from Central European building standards and literature values for the listed diversity factors, but the manuscript does not provide explicit error metrics or sensitivity results. We will incorporate a new subsection on simulation assumptions, available fidelity indicators from the TRNSYS setup, and acknowledged uncertainties to better support the claimed use cases. revision: yes

Circularity Check

0 steps flagged

No circularity: dataset paper with no derivations or fitted predictions

full rationale

The paper presents a dataset of real measurements from two homes plus TRNSYS simulations for 958 buildings. No equations, parameter fits, predictions, or first-principles derivations are claimed. The central contribution is data release for downstream modeling; the TRNSYS models are described as input generators rather than outputs derived from the paper's own results. No self-citation chains, ansatzes, or renamings reduce any claim to its own inputs. This matches the default expectation of no circularity for a non-derivational paper.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Dataset release paper with no mathematical derivations, fitted parameters, background axioms, or new postulated entities.

pith-pipeline@v0.9.1-grok · 5699 in / 1159 out tokens · 35374 ms · 2026-06-28T12:14:51.718533+00:00 · methodology

discussion (0)

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Reference graph

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