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Measuring the in-use thermal performance of dwellings: improving the precision by accounting for variability

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posted on 2025-10-24, 16:28 authored by Max Eastwood, David AllinsonDavid Allinson, Matthew LiMatthew Li, Ben M RobertsBen M Roberts
<p dir="ltr">Governments around the world are regulating the thermal performance of new and retrofitted dwellings to reduce the significant energy demand for space heating. These efforts are undermined by case-study evidence of a significant performance gap between the thermal performance predicted for compliance and the thermal performance that is achieved in-use. Overall building thermal performance is most simply described by the Heat Transfer Coefficient (HTC) metric. New low-cost methods are being developed to measure the in-use HTC of dwellings, i.e. measured during occupancy. If deployed at scale, these methods could provide much-needed evidence of the performance gap and help to close it through feedback and quality assurance. This paper quantifies, for the first time, the variability in repeated measurements of the in-use HTC of occupied dwellings over a winter heating season and demonstrates that this variability can be explained by changes in the average boundary conditions (indoor air temperatures and weather). This finding could provide measurements of the in-use HTC with a higher precision than when the variability is simply assumed to be part of the uncertainty in the measurement. The in-use HTC of 19 occupied dwellings was repeatedly calculated over rolling 20-day periods for up to 6 months. The inuse HTC of the dwellings had a coefficient of variation (standard deviation divided by mean) of between 1.0% and 11.8% (mean 7.1%). Valid linear models that described the variability in the in-use HTC (dependent variable) by considering variations in the boundary conditions at the time of each repeated measurement (independent variables) were created for 17 of the 19 dwellings. The in-use HTC for each dwelling had a unique relationship with the boundary conditions and required a unique linear model. The linear model explained at least 80% of the variability in 13 of 17 dwellings.</p>

Funding

EPSRC and SFI Centre for Doctoral Training in Energy Resilience and the Built Environment

Engineering and Physical Sciences Research Council

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History

School

  • Architecture, Building and Civil Engineering

Published in

Journal of Building Physics

Publisher

SAGE

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Acceptance date

2025-07-25

Publication date

2025-09-30

Copyright date

2025

ISSN

1744-2591

eISSN

1744-2583

Language

  • en

Depositor

Dr Ben Roberts. Deposit date: 31 July 2025

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