Control Limits for Building Energy End Use Based on Frequency Analysis and Quantile Regression

For buildings designed to meet aggressive energy goals, there is a need for tools to assist in the monitoring and maintenance of performance once the building is in operation. In particular, dashboard visualizations that show real-time and historic end use energy consumption alongside expected performance are powerful tools for both occupant engagement and the identification of operational issues. This article focuses on two related approaches to calculating upper and lower control limits for acceptable ranges of end use, which use a combination of modeled and measured usage data to generate realistic energy-conservative control limits. The first approach centers on the analysis of frequency distributions for end use consumption as functions of a main effect variable, while the second approach uses multivariate quantile regression based on principal components to generate control limits from all available measured variables.