Portions of this document m y be iliegibie in electronic image products. Images are produced from the best available original document. DISCLAIMERThis report was prepared as a n account of work sponsored by a n agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, make any warranty, express or implied, or assumes any legal liability or mponn'bility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or sem'ce by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necesSarily state or reflect those of the United States Government or any agency thereof. EXECUTIVE SUMMARYThis report supplements Lee et al. (1995), which presents the findings of an impact evaluation of the Manufactured Housing Acquisition Program (MAP). Pacific Northwest Laboratory conducted the evaluation and prepared both reports.This report presents detailed technical information relevant to the MAP impact evaluation. It ,is intended to provide the interested reader with enough information to answer most technical questions about the analysis and results. TIERED ANALYSIS APPROACHWe used a three-tiered process to analyze the energy consumption of both MAP and baseline homes. The information from each analysis was useful for designing our final analysis. \The first approach was a comparison of annual billing data, followed'by a simplified regression analysis to adjust for major home characteristics. We compared the mean annual kWh consumption of MAP and baseline homes, and used the'difference to estimate energy savings. We made no adjustments for long-term weather.This first analysis showed that MAP homes consumed less electricity than the baseline homes used in our analysis, but the differences were'less than the pre-program estimates suggested. We identified several factors to examine further. First, nonelectric supplemental heating was more common in baseline homes than in MAP homes. Second, in some cases heat pumps were more common in baseline homes than MAP homes and they tended to reduce energy consumption. Third, the average baseline home in our sample was smaller than the average MAP home, thus reducing the difference between electricity use in MAP and baseline homes. Fourth, we found that the distribution of total electricity consumption and consumption per square foot in MAP homes exhibited less variance than in, baseline homes.The second-tier approach was an application of the PRlnceton Scorekeeping Method (PRISM). This methodology uses monthly billing data to estimate coefficients that can be used to predict the non-temperature-and temperature-sensitive portions of energy consumption. W...

Building Technologies Program (DOE/BTP). According to DOE, buildings account for over 40% of total energy use and over 70% of electricity use in the United States. To reduce building energy usage, DOE/BTP established a strategic goal to significantly improve the energy efficiency of new and existing commercial buildings across the nation.In direct support of DOE's goal, the objective of this work is to develop a package of energy efficiency measures (EEMs) that demonstrates the feasibility of achieving at least 50% energy savings for quick-service restaurants (QSRs) with a simple payback of five years or less. As defined, the 50% goal involves reducing site energy usage in all eight U.S. climate zones, relative to buildings constructed to just meet minimal code-compliant requirements of ANSI/ASHRAE/IESNA Standard 90. 2 ) QSR building model that was based on actual floor plans in prototypical QSR design drawings. PNNL used EnergyPlus, a state-of-art energy simulation program, to determine the energy savings provided by the EEM package. The prototype building was analyzed in all eight U.S. climate zones that were further divided into moist, dry, and marine regions in which 16 representative climate cities were identified. The TSD establishes the baseline energy use by end-use category in a typical QSR, and provides the site energy and energy cost savings from implementation of the recommended EEMs. Finally, this TSD provides an estimate of the incremental first costs and simple payback years for an energy-efficient QSR in various climate locations. Table ES.1 summarizes the recommended EEMs for QSRs. Implementation of these EEMs can achieve a weighted-average energy savings of 45% across the nation, ranging from 41% to 52% by climate zone. Cost-effectiveness analysis to implement the EEMs shows a payback period ranging from 1.5 years to 3.5 years, depending on the climate location. These results are summarized for the 16 representative cities in Table ES.2.The project goal was to enable QSRs to achieve whole-building energy savings of at least 50% across all eight U.S. climate zones. Although we found that a national-weighted-average energy savings of 45% can be achieved, only the two coldest climates were able to reach the 50% energy-saving target. The key reason is that QSR is a special building type in which energy use is driven by very intensive process loads (i.e., the energy used for food preparation and storage). Process loads constitute 45% to 65% of wholebuilding energy consumption in a typical QSR. We have achieved significant energy savings in this area with optimized kitchen ventilation system and innovative food preparation/storage technologies ( Figure ES.1), but technologies are not yet available (from multiple vendors) to allow us to attain the 50% energy savings goal in all climate zones. If the process loads are removed from Figure ES.1, the energy savings from the building-related components are well beyond the 50% energy saving goal, ranging from 55% in warm climates to 65% in cold climates. i...

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EXECUTIVE SUMMARYThis report presents the results of an impact evaluation of the Manufactured Housing Acquisition Program. This evaluation was conducted for Bonneville by Pacific Northwest Laboratory to determine MAP'S energy impacts and cost-effectiveness. Two other reports supplement this overall report on the evaluation. Lee et al. (1995) provides technical details of the study. Sandahl, Lee, and Chin (1995) presents detailed information about the home owner survey conducted for this evaluation. DATA COLLECTIONTo estimate MAP savings we developed MAP and baseline home samples. We conducted telephone interviews to collect home and owner information for both homes. We completed 167 MAP occupant interviews and collected 134 utility billing release forms. For the baseline homes, we completed 183 interviews and obtained signed utility billing release forms from 123 respondents. ANALYSIS OVERVIEWWe conducted a three-tiered analysis of the utility billing data to estimate program electriccty savings. The first (a raw billing data comparison and simple regression analysis) and second (PRISM) tier analyses provided useful findings for the third-tier analysis by which program savings were estimated.The third-tier approach used a conditional demand type regression analysis to analyze monthly energy consumption, taking into account significant factors likely to influence electricrty usage. We used the regression results to estimate energy savings under "normal" weather conditions for each climate zone.For purposes of estimating savings we had to define a comparison home based on typical characteristics. The "pre-MAP baseline" home represents a home with dimensions typical of current homes, but with an efficiency level typical of homes built prior to MAP. The electricity savings estimates were very sensitive to assumptions made about the use of non-electric (primarily wood) space heat; about 20% of our combined sample of homes used some non-electric heat. We found no consistent evidence that MAP homes used non-electric heat more often.iii We used two approaches to estimate energy savings impacts of MAP. In the first, we calculated electricity savings based on the overall observed m'ix of heating types. In the second case, we calculated energy savings based on the assumption that all heating was supplied by an electric resistance furnace.The savings estimates were based on the third-tier, regression results. Acquisition energy savings were calculated as the energy consumption difference between preprogram baseline and MAP homes. These were the direct energy savings associated with homes built under MAP. MAP, however, had significant market transformation effects not accounted for by the acquisition savings.MAP occurred in two phases. During Phase 1, April 1992 through October 1994, the original national HUD code was in effect and utilities paid manufacturers $2,500 for each MAP home. Phase 2 started after October 1994, when a new, more efficient HUD code went into effect and the payment declined to $1,500. We estimated ene...

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