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Stock modelling, based on representative archetypes, is a promising tool for exploring areas for resource and emission reductions in the residential sector. The use of archetypes developed using detailed statistical analysis (multi-linear regression analysis, clustering and descriptive statistics) rather than traditional qualitative techniques allows a more accurate representation of the overall building stock variability in terms of geometric form, constructional materials and operation. This paper presents a methodology for the development of archetypes based on information from literature and a sample of detailed energy-related housing data. The methodology involves a literature review of studies to identify the most important variables which explain energy use and regression analysis of a housing database to identify the most relevant variables associated with energy consumption. A statistical analysis of the distributions for each key variable was used to identify representative parameters. Corresponding construction details were chosen based on knowledge of housing construction details. Clustering analysis was used to identify coincident groups of parameters and construction details; this led to the identification of 13 representative archetypes.
Please cite this article in press as: A.A. Famuyibo, et al., Developing archetypes for domestic dwellings—An Irish case study, Energy Buildings (2012), doi:10.1016/j.enbuild.2012.03.033