Sensitivity Assessment of Building Energy Performance Simulations Using MARS Meta-Modeling in Combination with Sobol’ Method

Amin Nouri (), Christoph van Treeck and Jérôme Frisch ()
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Amin Nouri: Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, 52074 Aachen, Germany
Christoph van Treeck: Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, 52074 Aachen, Germany
Jérôme Frisch: Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, 52074 Aachen, Germany

Energies, 2024, vol. 17, issue 3, 1-24

Abstract: Large discrepancies can occur between building energy performance simulation (BEPS) outputs and reference data. Uncertainty and sensitivity analyses are performed to discover the significant contributions of each input parameter to these discrepancies. Variance-based sensitivity analyses typically require many stochastic simulations, which is computationally demanding (especially in the case of the large number of input parameters involved in the analysis). To overcome these impediments, this study proposes a reliable meta-model-based sensitivity analysis, including validation, Morris’ method, multivariate adaptive regression splines (MARS) meta-modeling, and Sobol’ method, to identify the most influential input parameters on BEPS prediction (annual energy consumption) at the early building design process. A hypothetical building is used to analyze the proposed methodology. Six statistical metrics are applied to verify and quantify the accuracy of the model. It is concluded that the cooling set-point temperature and g-value of the window are the most influential input parameters for the analyzed case study.

Keywords: building energy performance simulation; validation; Monte Carlo simulation; meta-model; global sensitivity analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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