The Residential Energy Demand Temperature Index (REDTI) is based on population weighted* heating and cooling degree days, and as such, is a valuable tool for explaining year-to-year fluctuations in energy demand for residential heating and cooling. Residential energy consumption is known to be highly correlated with heating and cooling degree days. Energy consumption increases as the number of heating and cooling degree days increases and falls as the number of heating and cooling degree days falls. Diaz and Quayle (1980) found the correlation between energy use and heating degree days to be as high as 0.97 at the household level. Because of this strong relationship, seasonal changes in the REDTI can provide a good indication of the nation's fluctuating energy demands.
The Residential Energy Demand Temperature Index is calculated on a seasonal basis, using the sum of population weighted HDD's and CDD's (base 65), to provide retrospective information on the impact of seasonal temperatures on residential energy demand from 1895 to the present. To simplify year-to-year comparisons, the index is scaled from 0 to 100. An index of 100 is assigned to the year with the greatest population weighted degree day average while the year with the smallest degree day average receives an index of 0.
In creating the winter season index, for example, the population weighted degree day totals are calculated for each winter season. From this series, the maximum and minimum yearly degree day totals are identified. The minimum value is then subtracted from all years in the series so that a new series of values is created which ranges from zero to a value equal to the arithmetic difference between the maximum and minimum. This new series is then scaled to have a range of 0 to 100 using a common scaling factor**.
To determine how well the index captures year-to-year changes in energy demand, the REDTI was correlated with residential energy consumption*** for the period 1980-2000/01. National residential energy consumption values are available from 1973 through the winter of 2001, but because the later half of the 1970's was a period of dramatic change in energy conservation methods, high energy prices, and changing demand patterns, these years were omitted from the analysis. The effects of an increasing trend in residential energy consumption since 1980 were removed by linearly detrending the energy consumption time series prior to the correlation analysis. Because other factors, such as the effects of generally increasing US temperatures, are also removed from the detrended energy consumption time series, the REDTI was also detrended. Figures 1 through 4 contain scatter plots of detrended energy consumption and the REDTI during each season as well as the resulting correlations which were not less than 0.70 and as high as 0.86.
Table 1 contains residential energy demand in trillion BTU, and Table 2 contains the seasonal REDTI values. Both sets of data are for the period 1973 - 2001 prior to detrending. An example of the national summer season REDTI since 1895 is shown in figure 5.
Missing values are denoted by -99.99
*Population weighting is based on 2000 census figures in 344 climate divisions throughout the period of record. The use of population weighting in averaging degree days across the nation results in a national degree day average that more closely reflects large temperature deviations in heavily populated areas of the country.
**Calculation of scaling factor: The scaling factor was calculated using the maximum value in the new series. This scaling factor was calculated to be the number that, when multiplied by the maximum value in the new series, resulted in a value of 100. The degree day totals for all years in the new series were then multiplied by the same scaling factor to arrive at the scaled series.
***Residential Energy Demand figures were supplied by the Energy Information Administration and are comprised of residential coal, natural gas, petroleum and electricity (excluding electricity losses) usage.
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