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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 - 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 - 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 - by comparing profiles against expected profiles and identifying outlying data (Raffio et al., 2007).

• Energy Budgeting - 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 - by comparing performance profiles before and after building energy upgrades and modifications (Claridge et al., 1992; Kissock et al., 1998; Kissock and Eger, 2008).