Petrou, Giorgos;
Mavrogianni, Anna;
Symonds, Phil;
Chalabi, Zaid;
Lomas, Kevin;
Mylona, Anastasia;
Davies, Michael;
(2024)
Development of a Bayesian calibration framework for archetype-based housing stock models of summer indoor temperature.
Journal of Building Performance Simulation
10.1080/19401493.2024.2421330.
(In press).
Preview |
Text
Development of a Bayesian calibration framework for archetype-based housing stock models of summer indoor temperature.pdf - Published Version Download (4MB) | Preview |
Abstract
Archetype-based housing stock models of summer indoor temperature can support the development of policies to manage the climate change-driven increase in cooling demand and heat-related health impacts. Calibration can reduce the performance gap of such models, however, work on this topic is limited. Motivated by the growing importance of this underexplored research area, this paper introduces a framework for the Bayesian calibration of archetype-based housing stock models of summer indoor temperature. The framework includes data-driven procedures to classify dwellings into homogeneous groups and specify prior probability distributions. To demonstrate its application, an established bottom-up model based on EnergyPlus was calibrated using data collected from 193 dwellings monitored during the 2009 4M survey in Leicester, England. Post-calibration, the root-mean-square error reduced from 2.5°C to 0.6°C and remaining uncertainties were quantified. The application of this modular framework may be extended to models of energy use and other indoor environmental parameters.
| Type: | Article |
|---|---|
| Title: | Development of a Bayesian calibration framework for archetype-based housing stock models of summer indoor temperature |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/19401493.2024.2421330 |
| Publisher version: | https://doi.org/10.1080/19401493.2024.2421330 |
| Language: | English |
| Additional information: | © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
| Keywords: | Bayesian calibration; archetype-based modelling; housing stock model; indoor temperature; uncertainty quantification; performance gap |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10199852 |
Archive Staff Only
 |
View Item |
