Remote Home Energy Performance Assessment

One of the goals of the 2030 Challenge, adopted by The American Institute of Architects and the U.S. Green Building Council, is renovation of existing building stock to achieve 50% reduction in fossil fuel use. This goal translates into about 1.5 million major retrofits (i.e., insulation, air sealing and/or heating system upgrades) of existing homes per year. Identification of the retrofit opportunities in existing homes at scale is required to achieve this goal, yet the current identification practice involves on-site home energy assessments that can be inconvenient to homeowners, expensive, and of variable accuracy. In this talk, we will discuss remote home energy assessment technologies powered by data from ubiquitous sensors - communicating thermostats. We use coarse-grained physics-based modeling to estimate physical building parameters corresponding to the target retrofit opportunities, i.e., whole-home R value and ACH50, and to predict the post-retrofit energy savings. Comparisons of these estimates with results of on-site home energy assessments will be shown. The developed method is scalable and can be automatically applied to numerous households to identify home improvement opportunities.