Handling uncertainty in housing stock models

• Published in: Building and environment 2012-02, Vol.48 (FEV), p.35-47
• Main Authors: Booth, A.T., Choudhary, R., Spiegelhalter, D.J.
• Format: Article
• Language: English
• Subjects: Applied sciences; Bayesian; Building technical equipments; Buildings; Buildings. Public works; Calibration; Computation methods. Tables. Charts; Constraining; Energy; Energy management and energy conservation in building; Environmental engineering; Exact sciences and technology; Handling; Housing; Materials handling; Raw materials; Residential building; Retrofitting; Sensitivity analysis; Stock; Structural analysis. Stresses; Types of buildings; Uncertainty
• ISSN: 0360-1323; 1873-684X
• DOI: 10.1016/j.buildenv.2011.08.016

Housing stock models can be useful tools in helping to assess the environmental and socio-economic impacts of retrofits to residential buildings; however, existing housing stock models are not able to quantify the uncertainties that arise in the modelling process from various sources, thus limiting the role that they can play in helping decision makers. This paper examines the different sources of uncertainty involved in housing stock models and proposes a framework for handling these uncertainties. This framework involves integrating probabilistic sensitivity analysis with a Bayesian calibration process in order to quantify uncertain parameters more accurately. The proposed framework is tested on a case study building, and suggestions are made on how to expand the framework for retrofit analysis at an urban-scale. ► Previous housing stock models are reviewed. ► The sources of uncertainty in housing stock energy models are outlined. ► A framework for handling these sources of uncertainty is proposed. ► Bayesian calibration of uncertain model parameters is investigated. ► Methods for extending the calibration framework are described.