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Bayesian calibration of building energy models for uncertainty analysis through test cells monitoring

Calama-González, CM; Symonds, P; Petrou, G; Suárez, R; León-Rodríguez, ÁL; (2021) Bayesian calibration of building energy models for uncertainty analysis through test cells monitoring. Applied Energy , 282 (A) , Article 116118. 10.1016/j.apenergy.2020.116118. Green open access

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Abstract

Improving the energy efficiency of existing buildings is a priority for meeting energy consumption and CO2 emission targets in buildings. Building simulation tools play a crucial role in evaluating the performance of energy retrofit options. In this paper, a Bayesian calibration approach is applied to reduce the discrepancies between measured and simulated temperature data. Through its application to a test cell case study, the incorporation of sensitivity analysis and Bayesian calibration techniques are proven to improve the level of agreement between on-site measurements and simulated outputs, whilst accounting for both experimental and simulation uncertainties. The accuracy of a building simulation model developed using EnergyPlus was evaluated before and after calibration. Uncalibrated models were within the uncertainty ranges specified by the ASHARE Guidelines, with hourly simulation data over-predicting measurements by 3.2 °C on average. After Bayesian calibration, the average maximum temperature difference was reduced to around 0.68 °C, an improvement of almost 80%.

Type: Article
Title: Bayesian calibration of building energy models for uncertainty analysis through test cells monitoring
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.apenergy.2020.116118
Publisher version: https://doi.org/10.1016/j.apenergy.2020.116118
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Bayesian calibration, Sensitivity analysis, Uncertainty analysis, Building energy modelling, Mediterranean climate, Housing stock
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/10116413
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