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      SENSITIVITY ANALYSIS OF BUILDING ENERGY PERFORMANCE BASED ON POLYNOMIAL CHAOS EXPANSION

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          ABSTRACT

          Global sensitivity analysis based on polynomial chaos expansion (PCE) shows interesting characteristics, including reduced simulation runs for computer models and high interpretability of sensitivity results. This paper explores these features of the PCE-based sensitivity analysis using an office building as a case study with the EnergyPlus simulation program. The results indicate that the predictive performance of PCE models is closely correlated with the stability of the sensitivity index, depending on sample number and expansion degree. Therefore, it is necessary to carefully assess model accuracy of PCE models and evaluate convergence of the sensitivity index when using PCE-based sensitivity analysis. It is also found that more simulation runs of building energy models are required for a higher expansion degree of the PCE model to obtain a reliable sensitivity index. A bootstrap technique with a random sample can be used to construct confidence intervals for sensitivity indicators in building energy assessment to provide robust sensitivity rankings.

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          Most cited references 24

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          A review of sensitivity analysis methods in building energy analysis

           Wei Tian (2013)
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            A comparison of uncertainty and sensitivity analysis results obtained with random and Latin hypercube sampling

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              Computing derivative-based global sensitivity measures using polynomial chaos expansions

               B. Sudret,  C.V. Mai (2015)
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                Author and article information

                Journal
                jgrb
                Journal of Green Building
                College Publishing
                1943-4618
                1552-6100
                Fall 2020
                9 December 2020
                : 15
                : 4
                : 173-183
                Author notes

                1. College of Mechanical Engineering, Tianjin University of Science and Technology, Tianjin, China, 300222

                2. Tianjin International Joint Research and Development Center of Low-Carbon Green Process Equipment, Tianjin 300222, China

                3. Chair of Building Performance Analysis, University of Plymouth, Plymouth, Devon PL4 8AA, United Kingdom

                4. Tianjin Architecture Design Institute, Tianjin, China, 300074

                * Corresponding email: tjtianjin@ 123456126.com
                Article
                i1943-4618-15-4-173
                10.3992/jgb.15.4.173

                Volumes 1-10 of JOGB are open access and do not require permission for use, though proper citation should be given. To view the licenses, visit https://creativecommons.org/licenses/by-nc/4.0/

                Page count
                Pages: 12
                Product
                Categories
                RESEARCH ARTICLES

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