Assessing overall building energy performance of a large population of residential single-family homes using limited field data. Issue 4 (4th July 2019)

• Record Type: Journal Article
• Authors: Xie, Yulong; Mendon, Vrushali; Halverson, Mark; Bartlett, Rosemarie; Hathaway, John; Chen, Yan; Rosenberg, Michael; Taylor, Todd; Liu, Bing
• Is Part Of: Journal of building performance simulation. Volume 12:Issue 4(2019)
• Page Start: 480
• Page End: 493
• Publication Date: 2019-07-04
• Subjects: Building energy simulation -- building energy code compliance -- energy savings potential -- Monte Carlo -- bootstrap sampling; 690.0113
• DOI: 10.1080/19401493.2018.1477833
• Languages: English
• ISSNs: 1940-1493

Abstract

Abstract : Building energy simulation plays a significant role in building design and retrofit. Most applications deal with individual buildings which allow for the specification of detailed model inputs. However, building energy simulation can be a powerful tool for assessing energy performance even when comprehensive building characteristics are unavailable. In this study, limited field data were collected on randomly selected new homes in eight US states with a goal of evaluating energy code compliance and energy savings potential. The limited data do not allow the derivation of comprehensive model inputs for each individual home sampled, let alone for the entire unknown residential construction stock. Therefore, we used prototype buildings to construct a large number of models and utilized bootstrap sampling to draw inputs from the limited data. This research demonstrates that overall energy performance of a large population of new homes can be assessed by the novel framework, given limited data.