Residential Energy Analysis: Regression Analysis of Heating Degree Days With Temperature Setback for Selected ASHRAE Climate Zones Available to Purchase

Heating Degree Days (HDDs), calculated from hourly weather data, are often used to estimate energy savings for a variety of energy efficiency measures (EEMs) to be applied to conditioned spaces in buildings. More specifically, application of HDDs is useful for estimating savings from weather-dependent EEMs. For first order estimation, it is often problematic to calculate HDDs for a given base temperature, when temperature setbacks are used in the conditioned spaces. This paper provides a set of correlations to characterize HDDs for selected ASHRAE Climate Zones as functions of three key parameters including the base temperature, setback temperature level (delta-T), and setback duration. In addition to the well-documented pattern of decreasing HDDs for decreasing base temperature, it was also shown that HDDs are inversely proportional to both setback duration and temperature setback differential levels. In the analysis presented in this paper, corrections to estimate HDDs when temperature setbacks are used for typical residential space heating schedules during unoccupied periods which occurred from 8 am to 5 pm Monday through Friday. In particular, regression correlations using two- and three-parameter models have been developed to estimate HDDs for multiple US locations that account for the impact of temperature setbacks on the heating requirements of residential buildings. For the two-parameter model, the input variables for the regression correlations are setback hours and delta T; for the three-parameter model, the input variables for the correlations include setback hours, delta T, and base temperature. The prediction accuracy for the energy savings, due to a set of EEMs, obtained from the HDD method —using the developed correlations— is tested against whole-building detailed energy simulation analysis for two single family homes. Detailed energy audits including utility data analysis have been carried out for both homes to calibrate the detailed simulation model and evaluate the effectiveness of the EEMs in reducing building energy use. The results from the detailed simulation analysis are then compared to those obtained from the HDD with temperature setbacks.