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Titel |
Development and evaluation of a building energy model integrated in the TEB scheme |
VerfasserIn |
B. Bueno, G. Pigeon, L. K. Norford, K. Zibouche, C. Marchadier |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1991-959X
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Digitales Dokument |
URL |
Erschienen |
In: Geoscientific Model Development ; 5, no. 2 ; Nr. 5, no. 2 (2012-03-29), S.433-448 |
Datensatznummer |
250002450
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Publikation (Nr.) |
copernicus.org/gmd-5-433-2012.pdf |
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Zusammenfassung |
The use of air-conditioning systems is expected to increase as a consequence
of global-scale and urban-scale climate warming. In order to represent
future scenarios of urban climate and building energy consumption, the Town
Energy Balance (TEB) scheme must be improved. This paper presents a new
building energy model (BEM) that has been integrated in the TEB scheme.
BEM-TEB makes it possible to represent the energy effects of buildings and
building systems on the urban climate and to estimate the building energy
consumption at city scale (~10 km) with a resolution of a
neighbourhood (~100 m). The physical and geometric definition of
buildings in BEM has been intentionally kept as simple as possible, while
maintaining the required features of a comprehensive building energy model.
The model considers a single thermal zone, where the thermal inertia of
building materials associated with multiple levels is represented by a
generic thermal mass. The model accounts for heat gains due to transmitted
solar radiation, heat conduction through the enclosure, infiltration,
ventilation, and internal heat gains. BEM allows for previously unavailable
sophistication in the modelling of air-conditioning systems. It accounts for the dependence of
the system capacity and efficiency on indoor and outdoor air temperatures
and solves the dehumidification of the air passing through the system.
Furthermore, BEM includes specific models for passive systems, such as
window shadowing devices and natural ventilation. BEM has satisfactorily
passed different evaluation processes, including testing its modelling
assumptions, verifying that the chosen equations are solved correctly, and
validating the model with field data. |
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