TY - JOUR
T1 - Sensitivity analysis methods for building energy models
T2 - Comparing computational costs and extractable information
AU - Menberg, Kathrin
AU - Heo, Yeonsook
AU - Choudhary, Ruchi
N1 - Funding Information:
This study was conducted as part of the ‘Bayesian Building Energy Management (B.bem)’ project funded by the Engineering and Physical Sciences Research Council (EPSRC reference: EP/L024454/1). The financial support by travel grants for Kathrin Menberg and Yeonsook Heo as part of the European Commission Marie Curie BIMautoGEN IRSES grant is gratefully acknowledged. In particular, we would like to thank Prof. Patricio Vela, School of Electrical and Computer Engineering, Georgia Institute of Technology, and Prof. Godfried Augenbroe and Qinpeng Wang, School of Architecture, Georgia Institute of Technology, for the inspiring discussions and support.
Publisher Copyright:
© 2016 The Authors
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Though sensitivity analysis has been widely applied in the context of building energy models (BEMs), there are few studies that investigate the performance of different sensitivity analysis methods in relation to dynamic, high-order, non-linear behaviour and the level of uncertainty in building energy models. We scrutinise three distinctive sensitivity analysis methods: (a) the computationally efficient Morris method for parameter screening, (b) linear regression analysis (medium computational costs) and (c) Sobol method (high computational costs). It is revealed that the results from Morris method taking the commonly used measure for parameter influence can be unstable, while using the median value yields robust results for evaluations with small sample sizes. For the dominant parameters the results from all three sensitivity analysis methods are in very good agreement. Regarding the evaluation of parameter ranking or the differentiation of influential and negligible parameters, the computationally costly quantitative methods provide the same information for the model in this study as the computational efficient Morris method using the median value. Exploring different methods to investigate higher-order effects and parameter interactions, reveals that correlation of elementary effects and parameter values in Morris method can also provide basic information about parameter interactions.
AB - Though sensitivity analysis has been widely applied in the context of building energy models (BEMs), there are few studies that investigate the performance of different sensitivity analysis methods in relation to dynamic, high-order, non-linear behaviour and the level of uncertainty in building energy models. We scrutinise three distinctive sensitivity analysis methods: (a) the computationally efficient Morris method for parameter screening, (b) linear regression analysis (medium computational costs) and (c) Sobol method (high computational costs). It is revealed that the results from Morris method taking the commonly used measure for parameter influence can be unstable, while using the median value yields robust results for evaluations with small sample sizes. For the dominant parameters the results from all three sensitivity analysis methods are in very good agreement. Regarding the evaluation of parameter ranking or the differentiation of influential and negligible parameters, the computationally costly quantitative methods provide the same information for the model in this study as the computational efficient Morris method using the median value. Exploring different methods to investigate higher-order effects and parameter interactions, reveals that correlation of elementary effects and parameter values in Morris method can also provide basic information about parameter interactions.
KW - Building energy model
KW - Morris method
KW - Regression analysis
KW - Sensitivity analysis
KW - Sobol method
UR - http://www.scopus.com/inward/record.url?scp=85006797147&partnerID=8YFLogxK
U2 - 10.1016/j.enbuild.2016.10.005
DO - 10.1016/j.enbuild.2016.10.005
M3 - Article
AN - SCOPUS:85006797147
VL - 133
SP - 433
EP - 445
JO - Energy and Buildings
JF - Energy and Buildings
SN - 0378-7788
ER -