Quality assurance for building-stock energy models : a performance comparison of eleven uncertainty and sensitivity analysis methods
- Author
- Matthias Van Hove (UGent) , Marc Delghust (UGent) and Jelle Laverge (UGent)
- Organization
- Project
- Abstract
- Building-Stock Energy Models (BSEMs) have grown in popularity, implementation, scale and complexity. Yet, BSEM quality assurance processes have lagged behind. This article proposes a scalable methodology to apply Uncertainty (UA) and Sensitivity Analysis (SA) to BSEMs and studies the performance of eleven common UA-SA methods (OAT, SRC, SRRC, FFD, Morris, Sobol’, eFAST, FAST-RBD, DMIM, PAWN, DGSM) for three UA-SA targets: screening, ranking and indices. Applying UA and SA to BSEMs requires a two-step input parameter sampling that samples ‘across stocks’ and ‘within stocks’. To make efficient use of computational resources, practitioners should (i) distinguish between three UA-SA targets and (ii) choose a method based on the aimed UA-SA target. The computational cost varies according to the UA-SA target and method; (i) for screening: OAT, SRC, SRRC, FFD and Morris; (ii) for ranking: SRC, SRRC and Morris and (iii) for indices: Sobol’ is the most efficient, among the tested UA-SA methods.
- Keywords
- IEA EBC Annex 70, building-stock energy model, uncertainty analysis, sensitivity analysis, nested parameter sampling, convergence speed
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01H8P7PZQHE7CDK60VAJ3E9BAH
- MLA
- Van Hove, Matthias, et al. “Quality Assurance for Building-Stock Energy Models : A Performance Comparison of Eleven Uncertainty and Sensitivity Analysis Methods.” JOURNAL OF BUILDING PERFORMANCE SIMULATION, vol. 17, no. 2, 2024, pp. 149–75, doi:10.1080/19401493.2023.2248063.
- APA
- Van Hove, M., Delghust, M., & Laverge, J. (2024). Quality assurance for building-stock energy models : a performance comparison of eleven uncertainty and sensitivity analysis methods. JOURNAL OF BUILDING PERFORMANCE SIMULATION, 17(2), 149–175. https://doi.org/10.1080/19401493.2023.2248063
- Chicago author-date
- Van Hove, Matthias, Marc Delghust, and Jelle Laverge. 2024. “Quality Assurance for Building-Stock Energy Models : A Performance Comparison of Eleven Uncertainty and Sensitivity Analysis Methods.” JOURNAL OF BUILDING PERFORMANCE SIMULATION 17 (2): 149–75. https://doi.org/10.1080/19401493.2023.2248063.
- Chicago author-date (all authors)
- Van Hove, Matthias, Marc Delghust, and Jelle Laverge. 2024. “Quality Assurance for Building-Stock Energy Models : A Performance Comparison of Eleven Uncertainty and Sensitivity Analysis Methods.” JOURNAL OF BUILDING PERFORMANCE SIMULATION 17 (2): 149–175. doi:10.1080/19401493.2023.2248063.
- Vancouver
- 1.Van Hove M, Delghust M, Laverge J. Quality assurance for building-stock energy models : a performance comparison of eleven uncertainty and sensitivity analysis methods. JOURNAL OF BUILDING PERFORMANCE SIMULATION. 2024;17(2):149–75.
- IEEE
- [1]M. Van Hove, M. Delghust, and J. Laverge, “Quality assurance for building-stock energy models : a performance comparison of eleven uncertainty and sensitivity analysis methods,” JOURNAL OF BUILDING PERFORMANCE SIMULATION, vol. 17, no. 2, pp. 149–175, 2024.
@article{01H8P7PZQHE7CDK60VAJ3E9BAH,
abstract = {{Building-Stock Energy Models (BSEMs) have grown in popularity, implementation, scale and complexity. Yet, BSEM quality assurance processes have lagged behind. This article proposes a scalable methodology to apply Uncertainty (UA) and Sensitivity Analysis (SA) to BSEMs and studies the performance of eleven common UA-SA methods (OAT, SRC, SRRC, FFD, Morris, Sobol’, eFAST, FAST-RBD, DMIM, PAWN, DGSM) for three UA-SA targets: screening, ranking and indices. Applying UA and SA to BSEMs requires a two-step input parameter sampling that samples ‘across stocks’ and ‘within stocks’. To make efficient use of computational resources, practitioners should (i) distinguish between three UA-SA targets and (ii) choose a method based on the aimed UA-SA target. The computational cost varies according to the UA-SA target and method; (i) for screening: OAT, SRC, SRRC, FFD and Morris; (ii) for ranking: SRC, SRRC and Morris and (iii) for indices: Sobol’ is the most efficient, among the tested UA-SA methods.}},
author = {{Van Hove, Matthias and Delghust, Marc and Laverge, Jelle}},
issn = {{1940-1493}},
journal = {{JOURNAL OF BUILDING PERFORMANCE SIMULATION}},
keywords = {{IEA EBC Annex 70,building-stock energy model,uncertainty analysis,sensitivity analysis,nested parameter sampling,convergence speed}},
language = {{eng}},
number = {{2}},
pages = {{149--175}},
title = {{Quality assurance for building-stock energy models : a performance comparison of eleven uncertainty and sensitivity analysis methods}},
url = {{http://doi.org/10.1080/19401493.2023.2248063}},
volume = {{17}},
year = {{2024}},
}
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