SUMMARYThe development of standards governing the designed energy consumption of buildings has been sought by Congress to increase energy conservation. In determining what degree of energy conservation is desirable, efficiency and equity issues must be considered. Development of a performance standard that constrains design energy consumption to an economically efficient level requires identification of the least cost means of producing the desired building space conditioning characteristics. Accurate valuation of space conditioning inputs and outputs is also crucial to achieving economic efficiency in resource allocation.There is some evidence that market prices of fuels used for building space conditioning and lighting have been less than the actual social cost of these fuels, and therefore energy system designs have been chosen that make inefficient use of resources. The RIF x RUF multiplier concept, proposed by ASHRAE to fill the need for a factor by which to estimate the true cost of fuels, is evaluated and found lacking. Instead, estimates of social marginal cost are found to be the best means for incorporating the total cost of fuels in decisions determining design energy consumption for building space conditioning. This conclusion is supported by discussions of the historical patterns of fuel price distortion, identification of factors that influence the social costs of fuels, and estimates of the levels of social costs for conventional fuels.The social, environmental and economic effects of fuel consumption may be incorporated into building design decisions most comprehensively through the use of a life cycle cost methodology in which fuel prices are represented by estimates of marginal social cost incurred per end use Btu. It is recommended that if feasible, a marginal social cost estimate that accounts for fuel production efficiencies be used in determining minimum life cycle costs for building space conditioning. Since the expense of developing social cost estimates for nonmarket components of social cost is not justified by the findings of the review of the literature related to price distortion, the use of the marginal cost of new fuel supplies is recommended as a proxy. Whether iii market or social cost is used, the cost estimate should be derived for states or smaller regions, because of the extent of variation in fuel supply costs. iv SUMMARY FIGURES TABLES
Arab oil embargo. To accomplish this goal, Pacific Northwest Labratory (PNL) disaggregated the reduction in residential energy use per household since 1973 into six possible factors. The factors considered were: (1) building shell efficiencies, (2) geographic distribution of households, (3) appliance efficiency, (4) size of dwelling units, (5) fuel switching, and (6) consumer attitudes. The most important factor identified was improved building shell efficiency, although the impact of appliance efficiency is growing rapidly. Due to data limitations, PNL was not able to quantify the effects of two factors (size of dwelling units and fuel switching) within the framework of this study. The total amount of the energy reduction explained ranged from 18 to 46 percent over the years 1974 to 1980. iii SUMMARY. 1.0 INTRODUCTION. 2.0 RESULTS • 2.1 BASE CASE 2.2 TOTAL ENERGY SAVINGS 2.3 BUILDING SHELL EFFICIENCY 2.4 HOUSEHOLD MIGRATION 2.5 APPLIANCE EFFICIENCY CONTENTS 3.0 RECOMMENDATIONS FOR FURTHER RESEARCH 3.1 ANALYSIS OF RECS DATA 3.2 FUEL SWITCHING 3.3 DEMOGRAPHIC CHARACTERISTICS • 4.0 METHODOLOGY 4.1 BASIC APPROACHES 4.2 BUILDING SHELL EFFICIENCY 4.3 GEOGRAPHIC DISTRIBUTION OF HOUSEHOLDS .
Impact of New Passenger Car Technology on Fuel Consumption D.13 0.9 Components of Total Net Fuel Savings in the Automobile Sector D.14 D.10 Predicted Vehicle Stock and Consumption. D.15 D.11 Predicted Vehicle Miles Travelled and Consumption. D.16 0.12 Components of the Reduction in Automobile Fuel Use D.18 D.13 Actual Light Duty Truck Fuel Demand D.20 D.14 Actual Light Duty Truck Fuel Use and Alternative Base Cases. D.22 D.15 Estimates of Total Light Duty Truck Fuel Savings D.23 0.16 Analysis of Light Truck Market Size Mix Shift 1975-1982 D.25 D.17 Components of Total Net Fuel Savings in the Light Truck Sector D.26 X 3 Dummy variables have a value of 1 if the condition is true, and 0 otherwise.
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