Version 1
: Received: 8 August 2024 / Approved: 12 August 2024 / Online: 12 August 2024 (09:31:47 CEST)
How to cite:
Gervaz, S.; Favre, F. Identifying Key Parameters in Building Energy Models: Sensitivity Analysis Applied to Residential Typologies. Preprints2024, 2024080772. https://doi.org/10.20944/preprints202408.0772.v1
Gervaz, S.; Favre, F. Identifying Key Parameters in Building Energy Models: Sensitivity Analysis Applied to Residential Typologies. Preprints 2024, 2024080772. https://doi.org/10.20944/preprints202408.0772.v1
Gervaz, S.; Favre, F. Identifying Key Parameters in Building Energy Models: Sensitivity Analysis Applied to Residential Typologies. Preprints2024, 2024080772. https://doi.org/10.20944/preprints202408.0772.v1
APA Style
Gervaz, S., & Favre, F. (2024). Identifying Key Parameters in Building Energy Models: Sensitivity Analysis Applied to Residential Typologies. Preprints. https://doi.org/10.20944/preprints202408.0772.v1
Chicago/Turabian Style
Gervaz, S. and Federico Favre. 2024 "Identifying Key Parameters in Building Energy Models: Sensitivity Analysis Applied to Residential Typologies" Preprints. https://doi.org/10.20944/preprints202408.0772.v1
Abstract
Building energy modelling tools play a crucial role in quantifying and comprehending the energy performance of buildings. These tools demand substantial amounts of data, which can be challenging to acquire and are often associated with significant uncertainties. The incorporation of Sensitivity Analysis represents a relevant step towards developing reliable models, as it identifies the most critical parameters that require a meticulous characterization. In this study, a Sensitivity Analysis based on Morris method was conducted to assess the relevance of 14 input parameters affecting thermal loads across four dwelling typologies modelled in EnergyPlus. Different number of Morris trajectories and levels were considered to analyse the impact of the user-defined values of r and p when employing Morris method. Convergence was achieved from r=200 and p=12, which are higher than the typically employed values (r=10 and p=4). Setpoint temperatures, orientation, roof solar absorptivity and roof conductance rank among the most relevant parameters affecting thermal loads, however variations are observed for the four case studies.
Keywords
building energy model; sensitivity analysis; building simulation
Subject
Engineering, Architecture, Building and Construction
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
