Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?

Urban Building Energy Models (UBEMs) are emerging as a powerful tool for cities and regions seeking to make decisions on the best pathways for increasing the energy efficiency of their buildings. As model results are used to inform critical policy decisions, it is essential to understand and communi...

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Main Authors: Pamela J Fennell, Shima Ebrahimigharehbaghi, Érika Mata, Georgios Kokogiannakis, Shyam Amrith, Sotiria Ignatiadou, Samuele Lo Piamo
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Communications
Subjects:
Online Access:https://doi.org/10.1088/2515-7620/ad9438
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author Pamela J Fennell
Shima Ebrahimigharehbaghi
Érika Mata
Georgios Kokogiannakis
Shyam Amrith
Sotiria Ignatiadou
Samuele Lo Piamo
author_facet Pamela J Fennell
Shima Ebrahimigharehbaghi
Érika Mata
Georgios Kokogiannakis
Shyam Amrith
Sotiria Ignatiadou
Samuele Lo Piamo
author_sort Pamela J Fennell
collection DOAJ
description Urban Building Energy Models (UBEMs) are emerging as a powerful tool for cities and regions seeking to make decisions on the best pathways for increasing the energy efficiency of their buildings. As model results are used to inform critical policy decisions, it is essential to understand and communicate the limits of inference of model results and how sensitive they are to changes in inputs. In the absence of standard datasets and protocols for model validation, Uncertainty Analysis and Sensitivity Analysis (UASA) procedures offer vital insights. However, there is no consensus on how UASA should be applied to bottom-up building physics-based UBEMs, nor on how different use cases might influence the choice of UASA approach. This study uses a systematic review of the literature (2009–2023) to explore the procedures which are applied and assess their appropriateness. We find a need for a more holistic view of uncertainty to be taken, and present a decision framework for selecting the most appropriate form of quantitative sensitivity analysis, based on model form, data provenance and use case. We also propose a number of approaches to improve the application of sensitivity analysis in UBEM studies, including the importance of undertaking a complementary assessment of information quality.
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spelling doaj-art-e9169dca3120445c8e76c8cc3ce09a702025-08-20T03:00:54ZengIOP PublishingEnvironmental Research Communications2515-76202025-01-017202200210.1088/2515-7620/ad9438Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?Pamela J Fennell0https://orcid.org/0000-0002-3935-3466Shima Ebrahimigharehbaghi1Érika Mata2https://orcid.org/0000-0002-0735-3744Georgios Kokogiannakis3Shyam Amrith4Sotiria Ignatiadou5Samuele Lo Piamo6https://orcid.org/0000-0002-2625-483XUCL Energy Institute, University College London , 14 Upper Woburn Place, London, WC1H 0NN, United KingdomDelft University of Technology , Faculty of Architecture and the Built Environment, Julianalaan 134, Delft, The NetherlandsIVL Swedish Environmental Research Institute , Aschebergsgatan 44, 41133 Gothenburg, SwedenSustainable Buildings Research Centre (SBRC), Innovation Campus, University of Wollongong , AustraliaUCL Energy Institute, University College London , 14 Upper Woburn Place, London, WC1H 0NN, United KingdomIVL Swedish Environmental Research Institute , Aschebergsgatan 44, 41133 Gothenburg, SwedenFaculty of the Built Environment, University of Reading , Whiteknights Campus, Reading, RG6 6ED, United KingdomUrban Building Energy Models (UBEMs) are emerging as a powerful tool for cities and regions seeking to make decisions on the best pathways for increasing the energy efficiency of their buildings. As model results are used to inform critical policy decisions, it is essential to understand and communicate the limits of inference of model results and how sensitive they are to changes in inputs. In the absence of standard datasets and protocols for model validation, Uncertainty Analysis and Sensitivity Analysis (UASA) procedures offer vital insights. However, there is no consensus on how UASA should be applied to bottom-up building physics-based UBEMs, nor on how different use cases might influence the choice of UASA approach. This study uses a systematic review of the literature (2009–2023) to explore the procedures which are applied and assess their appropriateness. We find a need for a more holistic view of uncertainty to be taken, and present a decision framework for selecting the most appropriate form of quantitative sensitivity analysis, based on model form, data provenance and use case. We also propose a number of approaches to improve the application of sensitivity analysis in UBEM studies, including the importance of undertaking a complementary assessment of information quality.https://doi.org/10.1088/2515-7620/ad9438building stockurban building energy modelsbuilding energy demanduncertainty analysissensitivity analysisUBEM
spellingShingle Pamela J Fennell
Shima Ebrahimigharehbaghi
Érika Mata
Georgios Kokogiannakis
Shyam Amrith
Sotiria Ignatiadou
Samuele Lo Piamo
Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?
Environmental Research Communications
building stock
urban building energy models
building energy demand
uncertainty analysis
sensitivity analysis
UBEM
title Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?
title_full Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?
title_fullStr Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?
title_full_unstemmed Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?
title_short Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?
title_sort urban building energy models how can we improve the treatment of uncertainty for energy policy decision making
topic building stock
urban building energy models
building energy demand
uncertainty analysis
sensitivity analysis
UBEM
url https://doi.org/10.1088/2515-7620/ad9438
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