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Sökning: id:"swepub:oai:research.chalmers.se:699d96d6-0f48-4d28-8f8f-180c2ad37034" > Developing a common...

Developing a common approach for classifying building stock energy models

Langevin, Jared (författare)
Lawrence Berkeley National Laboratory
Reyna, J. L. (författare)
National Renewable Energy Laboratory
Ebrahimigharehbaghi, S. (författare)
Technische Universiteit Delft,Delft University of Technology (TU Delft)
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Sandberg, N. (författare)
Norges teknisk-naturvitenskapelige universitet (NTNU),Norwegian University of Science and Technology (NTNU)
Fennell, P. (författare)
University College London (UCL)
Nägeli, Claudio, 1987 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Laverge, J. (författare)
Universiteit Gent,Ghent university
Delghust, M. (författare)
Universiteit Gent,Ghent university
Mata Las Heras, Erika, 1980 (författare)
IVL Svenska Miljöinstitutet
Van Hove, M. (författare)
Universiteit Gent,Ghent university
Webster, J. (författare)
Federico, F. (författare)
University of California
Jakob, Martin (författare)
Camarasa, Clara (författare)
Danmarks Tekniske Universitet,Technical University of Denmark
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 (creator_code:org_t)
Elsevier BV, 2020
2020
Engelska.
Ingår i: Renewable and Sustainable Energy Reviews. - : Elsevier BV. - 1879-0690 .- 1364-0321. ; 133
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Annan naturresursteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Other Environmental Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Annan samhällsbyggnadsteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Other Civil Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Energisystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Energy Systems (hsv//eng)

Nyckelord

Building stock energy models
IEA Annex 70
Urban building energy modeling
Energy epidemiology
Model classification

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