 A review of sensitivity analysis methods in building energy analysisWei Tian Renewable and Sustainable Energy Reviews, 2013, vol. 20, issue C, 411-419 Abstract: Sensitivity analysis plays an important role in building energy analysis. It can be used to identify the key variables affecting building thermal performance from both energy simulation models and observational study. This paper is focused on the application of sensitivity analysis in the field of building performance analysis. First, the typical steps of implementation of sensitivity analysis in building analysis are described. A number of practical issues in applying sensitivity analysis are also discussed, such as the determination of input variations, the choice of building energy programs, how to reduce computational time for energy models. Second, the sensitivity analysis methods used in building performance analysis are reviewed. These methods can be categorized into local and global sensitivity analysis. The global methods can be further divided into four approaches: regression, screening-based, variance-based, and meta-model sensitivity analysis. Recent research has been concentrated on global methods because they can explore the whole input space and most of them allow the self-verification, i.e., how much variance of the model output (building energy consumption) has been explained by the method used in the analysis. Third, we discuss several important topics, which are often overlooked in the domain of building performance analysis. These topics include the application of sensitivity analysis in observational study, how to deal with correlated inputs, the computation of the variations of sensitivity index, and the software issues. Lastly, the practical guidance is given based on the advantages and disadvantaged of different sensitivity analysis methods in assessing building thermal performance. The recommendations for further research in the future are made to provide more robust analysis in assessing building energy performance. Keywords: Building energy; Sensitivity analysis; Global method; Variance-based method; Correlated inputs (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:20:y:2013:i:c:p:411-419 Ordering information: This journal article can be ordered from DOI: 10.1016/j.rser.2012.12.014 Access Statistics for this article Renewable and Sustainable Energy Reviews is currently edited by L. Kazmerski More articles in Renewable and Sustainable Energy Reviews from Elsevier |
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