Estimation of Energy End-Use Intensities The 1995 energy end-use tables provide estimates of the amount of natural gas and electricity used specifically for nine end uses: space heating, cooling, ventilation, water heating, lighting, cooking, refrigeration, office equipment, and other.   The end-use estimates were calculated by using two main sources of data: (1) survey data collected by the CBECS and (2) building energy simulations provided by the Facility Energy Decision Screening (FEDS) system. The CBECS provided data on building characteristics and total energy consumption (i.e., for all end uses) for a national sample of commercial buildings. Using data collected by the CBECS, the FEDS engineering modules were used to produce estimates of energy consumption by end use. The FEDS engineering estimates were then statistically adjusted to match the CBECS total energy consumption.   This section briefly describes the FEDS load estimation methodology, the statistical adjustment procedure, and the remaining steps necessary to produce the final end-use estimates.   The Facility Energy Decision Screening Engineering Estimates   The energy consumption data provided by energy suppliers cover all end uses performed within commercial buildings. Total energy consumption can be disaggregated into end-use consumption by several approaches: engineering simulations, statistical modeling, or a hybrid approach known as a statistically adjusted engineering (SAE) approach. The CBECS end-use estimates were developed by using the SAE approach, with the FEDS system providing the initial engineering estimates.   The FEDS software was developed for the U.S. Department of Energy’s Federal Energy Management Program and the U.S. Army Construction Engineering Research Laboratory as a tool for screening groups of buildings on Federal facilities (such as Army bases) for energy efficiency retrofits. The engineering modules, which estimate the energy load to be subjected to retrofit optimization, are one in a series of well-known building energy simulations which include DOE-2 and ASEAM. The FEDS uses high-level installation information (number, age, size, and types of buildings and energy systems), an internal data base of typical energy-system configurations and performance data, and sophisticated energy simulation and optimization models to estimate the net present value of potential energy retrofits in Federal installations.   The FEDS engineering models are designed to produce estimates for five end uses: space heating, cooling, ventilation, lighting, and water heating. Two other end uses, cooking and refrigeration, are also calculated internally by the model, although they are not part of the normal FEDS output. These seven end uses, plus an “other” end use, represent the FEDS accounting for total building end use. Estimates for office equipment energy use were not provided by the FEDS model.   Estimates for the first five end uses are based on detailed building engineering simulations. Estimates for the latter two rely on parameters developed in the Regional End-Use Monitoring Program (REMP), formerly known as the End-Use Load and Consumer Assessment Program (ELCAP) study. REMP was a large end-use monitoring project sponsored by the Bonneville Power Administration. As it was designed to be used in facilities, only a general description of a building need be input for the building energy loads to be estimated interactively, relying on an extensive series of internal default values. Some of these defaults were based on data from prior CBECS, but many were based on the REMP study. For use with the CBECS, the FEDS interface was changed from interactive to batch, with the CBECS survey data supplying as many values as possible.   Besides values relating to the building characteristics, the engineering estimates also required hourly weather profiles. For each calendar month, the average temperature, humidity, and cloudiness during each hour of the day were calculated and input to the model.   Statistically Adjusted Engineering Estimates   The FEDS estimates were based on building characteristics and weather only. At the statistically adjusted engineering (SAE) stage, the engineering estimates were modified to match the observed CBECS consumption data. The basic idea behind the SAE method is simple. Let euibfu be the end-use consumption per square foot estimated by the FEDS model for building b, fuel f, and end use u, and let euibf be the total energy consumption (from the CBECS Energy Suppliers Survey) per square foot for building b and fuel f. Then a set of coefficients afu can be estimated statistically, i.e., by multiple regression, such that           The coefficients adjust the FEDS engineering estimates upward or downward to match the reported energy use. The eûibf are referred to as SAE estimates. If each estimated value of afu is equal to one, the eui’s are the same as those calculated in the engineering model. A value other than one can reflect a variety of factors. The FEDS model assumed values for a number of engineering variables on the basis of a typical or average building. If the characteristics within the sample buildings differ on average from the assumed values, then the actual eui’s will diverge from the engineering eui’s.   The basic SAE equation stated above assumes that there is a constant bias in the engineering estimates. However, the assumption of constant bias may be inappropriate. The bias may vary along a number of dimensions. Building type, building age, occupant density, and the presence of energy-intensive activities within the building were some of the variables examined to explore the patterns of bias. A nonlinear SAE equation was developed to incorporate these items. The nonlinear framework allowed greater flexibility in the way that variables, such as building age and employment density, could interact with the engineering estimates of end-use consumption. The SAE equations were estimated separately for electricity, natural gas, fuel oil, and district heat.   The Final End-Use Estimates   Because the SAE procedure calibrated the engineering estimates to the reported data for aggregates of buildings, SAE estimates for individual buildings could still vary from the values on the CBECS Master File. For the final end-use estimates, the value on the CBECS Master File (whether reported or imputed) was prorated in proportion to the SAE estimates.   The office equipment estimate was also made after the SAE estimation by using both REMP estimates and estimates from Arthur D. Little Inc. (ADL). The REMP database contains estimates for subcomponents of “other” end-use consumption and was used to estimate the office equipment share of the “other” end-use energy consumption for the 1989 and 1992 CBECS. Included in office equipment were large computer equipment (if the CBECS data indicated the presence of a computer area with a separate air-conditioning system), personal computer equipment, and general office equipment (typewriters, copiers, cash registers, etc.). For the 1995 CBECS, the REMP computer energy consumption estimates were replaced with the more recent ADL estimates before calculating the office equipment share was calculated.   Top   Return to “Technical Information on CBECS”     Specific questions on these topics may be directed to: Alan Swenson alan.swenson@eia.doe.gov Phone: (202) 586-1129 -or-   Joelle Michaels joelle.michaels@eia.doe.gov CBECS Manager Phone: (202) 586-8952 FAX: (202) 586-0018   File last modified November 16, 1999 URL: http://www.eia.doe.gov/emeu/cbecs/tech_end_use.html