Título:
Identifying key parameters in building energy models : Sensitivity analysis applied to residential typologies.
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Autor:
Gervaz, Sofía
Favre, Federico
Favre, Federico
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Tipo de documento:
Artículo
Editor:
Palabras clave:
Building energy model
Sensitivity analysis
Building simulation
Sensitivity analysis
Building simulation
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Año de publicación:
2024
Contenido:
Resumen:
Building energy modeling tools play a crucial role in quantifying and understanding the energy performance of buildings. These tools require substantial amounts of data, which can be challenging to obtain and are often associated with significant uncertainties. The incorporation of sensitivity analysis is a crucial step toward developing reliable models as it identifies the most critical parameters that require meticulous characterization. In this study, a sensitivity analysis based on the Morris method was conducted to assess the relevance of 14 input parameters affecting thermal loads across four dwelling typologies modeled in EnergyPlus. Different numbers of Morris trajectories and levels were considered to analyze the impact of the user-defined values of r and p when employing the Morris method. Convergence was achieved at r = 200 and p = 12, which are higher than the typically employed values (r = 10 and p = 4). Roof solar absorptivity, setpoint temperatures, orientation, and the roof conductance rank among the top five most influential parameters affecting thermal loads in all four of the studied typologies. Occupancy was also among the top five most relevant parameters in three of the four typologies.
Descripción:
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Editorial:
MDPI
EN:
Buildings, vol.14, no. 9, 2024, 2804.
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Citación:
Gervaz, S. y Favre, F. "Identifying key parameters in building energy models: sensitivity analysis applied to residential typologies". Buildings. [en línea] 2024 vol.14, no. 9, 2804. DOI: https://doi.org/10.3390/buildings14092804.
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Licencia:
Licencia Creative Commons Atribución (CC - By 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| GF24.pdf | Versión publicada | 1.57 MB | Adobe PDF |