Quality assurance for building-stock energy models: a performance comparison of eleven uncertainty and sensitivity analysis methods

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

Acknowledgements

The authors gratefully acknowledge the strong support of Annex 70 from the International Energy Agency Energy in Buildings and Communities Programme (IEA-EBC). The author, Van Hove M. Y. C., would like to acknowledge Ghent University for supporting this work under BOF Grant (01D04818).

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are subject to third party restrictions (from the Flemish Energy and Climate Agency) and were used under license for this study. Data are therefore available from the authors with the permission of the Flemish Energy and Climate Agency.

Nomenclature

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Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by Bijzonder Onderzoeksfonds UGent [grant number 01D04818].