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Improve estimation of new vs. existing energy use #514

@jtlangevin

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@jtlangevin

Scout partitions new vs. existing energy use on the basis of new vs. existing square footage in the AEO forecast. This does not account for the likelihood that new construction is more efficient on a sf-normalized basis than existing construction, and would therefore use less energy than its share of total sf would suggest.

An improved approach would use BuildStock data and vintage bins to estimate the EUIs of new vs. existing construction and apply that as an additional layer on top of the square footage-based partitioning carried out now. A candidate approach:

  1. Pull total energy use by end use, building type, fuel type, and region from the Stock dataset, and map to Scout end uses/building types/fuel types/regions (state and EMM versions).
  2. Partition the result from number 1 by that attributable to the newest vintage bin vs. that attributable to all other vintage bins.
  3. Divide the new and existing subsets from number 2 by total square footage for those new and existing bins to get a segment-specific EUI for new equipment and a segment-specific EUI for existing equipment.
  4. Develop a segment-specific ratio between the new equipment EUI and the existing equipment EUI, which we can apply when separating EIA energy segment projections into new vs. existing.

For example, let's say in the Stock data there's a 1000 MMBtu segment for electric heating in CA single family homes, which constitute 100 square feet, of which 5 square feet is new. Of this, 2 MMBtu are attributable to the newest vintage bin and the remaining 98 are attributable to all earlier vintage bins. EUI_new = 2/5 = 0.4 MMBtu/sf; EUI_exist = 98/95 = 1.03 MMBtu/sf. Ratio of new vs. existing EUI = 0.4 / 1.03 = 0.39.
Now we would translate that into the Scout/EIA data. There we have a 2000 MMBtu segment, 500 square feet, with 50 of it new. So the new portion of that segment = 2000 * (50/500) * 0.39 = 78 MMBtu. And existing is the remaining 2000 - 78 = 1922 MMBtus.

@handichan should lead the development of a fix.

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