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Challenges and Less...
Challenges and Lessons Learned in Applying Sensitivity Analysis to Building Stock Energy Models
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- Fennell, P. (author)
- University College London (UCL)
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- Van Hove, M. (author)
- Universiteit Gent,Ghent university
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Weinberg, Lia (author)
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- Bennett, George J. (author)
- University College London (UCL)
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- Delghust, M. (author)
- Universiteit Gent,Ghent university
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- Forthuber, Sebastian (author)
- Technische Universität Wien,Vienna University of Technology
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Jakob, Martin (author)
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- Mata Las Heras, Erika, 1980 (author)
- IVL Svenska Miljöinstitutet AB,IVL Swedish Environmental Research Institute
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- Nägeli, Claudio, 1987 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Reyna, J. L. (author)
- National Renewable Energy Laboratory
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Catenazzi, Giacomo (author)
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(creator_code:org_t)
- KU Leuven, 2022
- 2022
- English.
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In: Building Simulation Conference Proceedings. - : KU Leuven. - 2522-2708. ; , s. 2203-2210
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Abstract
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- Uncertainty Analysis (UA) and Sensitivity Analysis (SA) offer essential tools to determine the limits of inference of a model and explore the factors which have the most effect on the model outputs. However, despite a well-established body of work applying UA and SA to models of individual buildings, a review of the literature relating to energy models for larger groups of buildings undertaken by Fennell et al. (2019) highlighted very limited application at larger scales. This contribution describes the efforts undertaken by a group of research teams in the context of IEA-EBC Annex 70 working with a diverse set of Building Stock Models (BSMs) to apply global sensitivity analysis methods and compare their results. Since BSMs are a class of model defined by their output and coverage rather than their structure and inputs, they represent a diverse set of modelling approaches. Key challenges for the application of SA are identified and explored, including the influence of model form, input data types and model outputs. This study combines results from 7 different modelling teams, each using different models across a range of urban areas to explore these challenges and begin the process of developing standardised workflows for SA of BSMs.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Annan samhällsbyggnadsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Other Civil Engineering (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
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- By the author/editor
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Fennell, P.
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Van Hove, M.
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Weinberg, Lia
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Bennett, George ...
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Delghust, M.
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Forthuber, Sebas ...
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show more...
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Jakob, Martin
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Mata Las Heras, ...
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Nägeli, Claudio, ...
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Reyna, J. L.
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Catenazzi, Giaco ...
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show less...
- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Other Computer a ...
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Civil Engineerin ...
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and Other Civil Engi ...
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Mathematics
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and Probability Theo ...
- Articles in the publication
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Building Simulat ...
- By the university
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Chalmers University of Technology