Energy and Housing Stock Segmentation to Achieve Community Energy Savings

Municipalities require robust energy and building data in order to meet energy efficiency and emissions reduction goals, but these data can also be used to inform and achieve broader community goals such as those related to affordable housing or economic development. These data need to be tailored to each community’s unique building stock to most effectively help policymakers prioritize investments and resources. Despite increasing demand for and access to housing and energy data at the aggregate and building level, there is still no broad understanding of how particular homes types use energy differently.

This paper summarizes the replicable methodology for characterizing single family housing stock and energy use. The analysis combines the measured energy consumption in over 400,000 homes and the property assessor data of one million homes in Cook County, Illinois. Then the paper presents results from an analysis of measured energy use performance and housing characteristics segmented by construction type, age and size. The analysis provides distinct energy outcomes and provides a method to prioritize homes for maximum aggregate energy savings.

The paper then describes how housing segmentation has been applied in the Chicago region in residential energy retrofit programs, adding geo-spatial and census level household income analysis. Last, the paper discusses results and presents recommendations for how measured energy use across populations of homes can be used to examine trends that cannot be observed in single home comparisons, provide clarity in real estate transactions, and have a dramatic impact on how community-scale programs are developed and implemented.