End-use energy consumption estimates for U.S. commercial buildings, 1992

Abstract

Portions of thisin the study combines elements of engineering simulations and statistical analysis to estimate end-use intensities for heating, cooling, ventilation, lighting, refrigeration, hot water, cooking, and miscellaneous equipment.Adjusted Engineering (SAE) models were estimated by building type. r SAE models used variables such as building size, vintage, on, weekly operating hours, and employee density to adjust the model predicted loads to the observed consumption (based upon ing information). 6751 buildings in the 1992 CBECS. This report describes anThe methodology used End-use consumption by fuel was estimated for The report displays the summary 11 separate building types as well as for the total U.S. commercial building stock.i i i SUMMARY An accurate picture o f how energy is used in the nation's stock of commercial buildings can serve a variety of program planning and policy needs of the U.S. Department of Energy, utilities, and other groups seeking to improve the efficiency of energy use in the building sector. estimations of energy consumption by end use--heating, cooling, 1 ighting, hot water, etc., --based on data from the 1992 Commerci a1 Bui 1 ding Energy Consumption Survey (CBECS). This work was conducted by Pacific Northwest National Laboratory (PNNL) for the Energy End Use and Integrated Statistics Division (EEUISD) within the Energy Information Administration (EIA). generated estimates of end-use consumption for the 1989 CBECS and published these estimates in 1993. This report presents PNNL previouslyCommercial end-use intensity (EUI), defined as energy consumption per square foot, will be used to 1) support the EIA commercial, sector energy modeling and forecasting efforts as part of the National Energy Modeling System (NEMS) and 2) augment the statistical summary information from the survey as published by the EIA. GENERAL APPROACHESDevelopment of EUIs for buildings can follow three general approaches: 1) direct metering, 2) statistical analysis known as Conditional Demand Analysis, and 3) engineering simulation. combination of the elements of the engineering simulation and Conditional Demand Analysis. model, begins by estimating end-use components with an engineering-oriented building simulation model. Predicted energy consumption for each end use in each CBECS sample building is dependent on some or all of the following factors : 1) bui 1 ding physical characteristics , 2) operating characteri sti cs, and 3) weather.The approach used in this study was a This approach, the Statistically Adjusted Engineering (SAE)The second stage of the SAE procedure uses the predicted end-use components as regressors to expl ai n actual total bui 1 ding energy consumption based on billing data. ment coefficients for each of the engineering-based end-use estimates.The regression model coefficients are interpreted as adjustThe V adjustment c o e f f i c i e n t s are then used t o generate t h e f i n a l end-use estimates for a l l b u i l d i n g s , i n c l u d i n g those t h a t may not have been i...

Documentation for FY2003 BTS GPRA Metrics

“…The table's figures were calculated based on the 1997 ORNL Metaevaluation report, (2) the ORNL Meeting the Challenge report, (4) and special tabulations from the 1997 RECS. (5) Previous year's estimates were based on program resource allocations at levels reflecting a formula bias towards homes in colder climates in the Northeast and Midwest. The higher appropriation levels projected for FY 2002 and beyond will be allocated under a formula that shifts a higher proportion of new revenues to the South and West, where saving rates are lower.…”

“…A net present value of $161 per household (5) (1989 $), adjusted for inflation, was used for the FY 2003 effort, based on the estimated non-energy benefits resulting from enhanced property values and extended lifetimes of the dwellings, reduced fires, and reduced arrearages. Non-energy benefits associated with employment and environmental exter-nalities are captured elsewhere in reporting and therefore are not included here.…”

“…Based on a series of simulations that include various U.S. locations and that were developed specifically to evaluate the two ASHRAE standards (often referred to as the "determination" study [5] ), the average reduction in site energy use was estimated to be about 3.5% or about 2 MMBtu/square foot. The GPRA estimates were partly based on states' accelerated adoption schedule of the ASHRAE 90.1-1999 standard.…”

“…The spreadsheet model required several key baseline inputs. Projected annual floor space additions by building type were based on Annual Energy Outlook 2001 (5) and were taken from the BESET database. Baseline energy use/sq ft for lighting by building type was taken from PNNL's 1997 study to estimate end-use energy consumption for U.S. commercial buildings.…”

“…Baseline energy use/sq ft for lighting by building type was taken from PNNL's 1997 study to estimate end-use energy consumption for U.S. commercial buildings. (5) The model was applied to the following building types: offices, retail, education, health services, assembly, and lodging.…”