INTRODUCTION With rising energy prices and increased incentives for buildings to be energy-efficient@ it becomes increasingly important to profile building energy performance. A building energy performance profile can be created by regressing building energy use as a function of independent variables@ such as weather or occupancy rate@ that affects energy consumption. The resulting regression profile provides a robust characterization of building performance@ and can be used for: ? Benchmarking ?C to compare the energy performance of similar-type buildings or to compare the energy performance of a building over time after removing the effects of changing weather and other energy drivers (Patil et al.@ 2005; Seryak and Kissock@ 2005; Kissock and Mulqueen@ 2008). ? Energy Use Breakdowns ?C to disaggregate building energy use into weather-dependent energy use@ weatherindependent energy use@ and energy use that fluctuates with other variables (Kissock and Eger@ 2007). ? Identifying Energy Saving Opportunities ?C by comparing profiles against expected profiles and identifying outlying data (Raffio et al.@ 2007). ? Energy Budgeting ?C to determine future energy use and cost at different seasons of the year and for changing independent variables@ such as occupancy rates. ? Measuring Energy Savings ?C by comparing performance profiles before and after building energy upgrades and modifications (Claridge et al.@ 1992; Kissock et al.@ 1998; Kissock and Eger@ 2008).