Issue |
E3S Web Conf.
Volume 111, 2019
CLIMA 2019 Congress
|
|
---|---|---|
Article Number | 04027 | |
Number of page(s) | 8 | |
Section | High Energy Performance and Sustainable Buildings, Simulation models and predictive tools for the buildings HVAC, IEQ and energy | |
DOI | https://doi.org/10.1051/e3sconf/201911104027 | |
Published online | 13 August 2019 |
Metamodeling of building energy consumption focused on climate, operation, space use and users related factors
1 LaSIE, Université de La Rochelle, Av. Michel Crépeau, 17043 La Rochelle cedex 1, France
2 TERAO, 10 Cité de Trévise, 75009, Paris, France
* Corresponding author: author@e-mail.org
* anovel@terao.fr
Energy performance guarantee projects aim at achieving a given energy consumption in real life conditions. Building energy consumption monitoring during operation phase often reveals that energy consumption is sensitive to building spaces use and systems operation quality, especially for buildings with high energy performance characteristics [7]. Other investigations show the impact of building users’ behaviour on energy consumption [28]. These factors must be added to climate factors for energy consumption prediction during operation phase. Number of factors and possible combinations is very high. Building energy modeling is limited regarding this issue and metamodeling has been used to solve this problem [25]. We developed metamodels that are polynomial functions using D-optimal design of experiment (DOE) approach. Such metamodels can become operational tools to use in the IPMVP framework, associated with a M&V plan. This paper shows the application of the method on a cultural building that comprises numerous systems and usages. We obtain a reliable metamodel of the energy consumption as a function of climate, operation, and space use factors. which meets IPMVP [11] and ASHRAE Guideline 14 [3] modeling uncertainties criteria. We also determine the global uncertainty resulting from predictors’ uncertainties propagation and modelling uncertainty associated with the metamodel.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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