Analysis of Pre-Retrofit Building and Utility Data - Southeast United States

This project delves into the workflow and results of regression models on monthly and daily utility data (meter readings of electricity consumption), outlining a process for screening and gathering useful results from inverse models. Energy modeling predictions created in Building Energy Optimization software (BEopt) Version 2.0.0.3 (BEopt 2013) are used to infer causes of differences among similar homes. This simple data analysis is useful for the purposes of targeting audits and maximizing the accuracy of energy savings predictions with minimal costs.

The data for this project are from two adjacent military housing communities of 1,166 houses in the southeastern United States. One community was built in the 1970s, and the other was built in the mid-2000s. Both communities are all electric; the houses in the older community were retrofitted with ground source heat pumps in the early 1990s, and the newer community was built to an early version of ENERGY STAR with air source heat pumps. The houses in the older community will receive phased retrofits (approximately 10 per month) in the coming years. All houses have had daily electricity metering readings since early 2011.

This project explores a dataset at a simple level and describes applications of a utility data normalization. There are far more sophisticated ways to analyze a dataset of dynamic, high resolution data; however, this report focuses on simple processes to create big-picture overviews of building portfolios as an initial step in a community-scale analysis.

TO4 9.1.2: Comm. Scale Military Housing Upgrades