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On the accuracy of Urban Building Energy Modelling

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journal contribution
posted on 21.01.2022, 16:38 by Argyris Oraiopoulos, Bianca HowardBianca Howard
The growing demand for energy in urban areas has led to the development of a variety of methodologies for modelling energy in buildings at large scale. However, their accuracy has yet to be thoroughly reviewed. This paper presents a systematic analysis of urban building energy models, that have been validated against measured data, using a singular taxonomy based on key attributes that could influence a model’s accuracy: application, scale, input data, computational method, calibration and validation methods. The analysis showed that the accuracy of urban building energy models is multi-dimensional, considered at a variety of temporal resolutions, spatial resolutions and measures of error, with the results demonstrating that there is no single key attribute that governs it. At the aggregate spatial and annual temporal resolutions, the accuracy, often reported in a single percent error value, can be as low as 1%, while for individual buildings at the annual resolution, the tails of the distribution of errors can reach 1000%. Models using non-calibrated physics-based computational methods were more likely to report overly large errors, while those employing Bayesian calibration consistently reported lower errors at the hourly temporal resolution, demonstrating the positive impact of calibration and in particular the Bayesian approach, on the models’ accuracy. Overall, the review has highlighted that more transparent and consistent reporting of accuracy is necessary and further research is essential for improving the evaluation of accuracy in modelling methodologies, if modern challenges are to be met through emerging applications such as energy systems integration and climate resilience.

Funding

FlexTECC: Flexible Timing of Energy Consumption in Communities

Engineering and Physical Sciences Research Council

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History

School

  • Architecture, Building and Civil Engineering

Published in

Renewable and Sustainable Energy Reviews

Volume

158

Publisher

Elsevier BV

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

Acceptance date

01/12/2021

Publication date

2022-01-20

Copyright date

2021

ISSN

1364-0321

Language

en

Depositor

Dr Bianca Howard. Deposit date: 21 January 2022

Article number

111976