Abstract
This paper describes the methods used and the assumptions made in developing a regional data base for each of the nine U.S. census, divisions. The data are used to provide regional input to a comprehensive engineering-economic computer model to simulate energy use in the residential sector from 1970 to 2000. These regional models provide an analytical tool with which conservation policies, technologies, and strategies can be evaluated for their effects on residential energy use, fuel expenditures, and capital costs.
Highlights
The structure of these models is identical to that of the national residential energy model developed at ORNL.^'^ The major contribution of this study is to develop the regional data sets that replace the original national data set as inputs to the model
As in the national model, the regional models deal with annual energy use for four fuels; eight end uses; and three housing types
We developed a simple ad hoc scheme to "create" equipment ownership estimates for the nine divisions based on the 1970 ownership patterns for the divisions" and the 1973 and 1974 ownership patterns for the regions." The basic assumption used to derive these estimates is that the ratio of market-shares between two divisions within a region is the same in 1973 and 1974 as it was in 1970
Summary
The structure of these models is identical to that of the national residential energy model developed at ORNL.^'^ The major contribution of this study is to develop the regional data sets that replace the original national data set as inputs to the model. The housing model is sensitive to both national and regional inputs in its calculations of households, housing choices, and new construction. The motivation for constructing regional models concerns the varia tions among regions in characteristics that influence residential energy use: population growth, housing choices, fuel prices and availabilities, income, climate, and fuel choices; see Table 1. These models enable us to evaluate the regional effects of national conservation policies and programs; and evaluate the regional effects of regional programs
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