A tool for estimating the future energy use, carbon emissions, and capital and operating cost impacts of energy efficiency and demand flexibility technologies in the U.S. residential and commercial building sectors.
This pull request changes the way that end use-level electricity use is allocated from census divisions to EMM regions and states.
Previous Approach
We allocated annual total electricity use projections at the end use level by census division to EMM regions across all end uses on the basis of total EMM electricity sales data (resolved by residential and commercial building types, but not end-use-resolved) from EIA. We used the same approach to disaggregate electricity use data from census divisions to states, using EIA state-level electricity consumption data.
This approach preserves the end use shares of the census division-building type combinations within each EMM or state that comprises it.
That's fine for most end uses, but for census divisions with lots of climatic variation and/or large intra-regional differences in electric equipment penetration, e.g., the Southeast or Pacific census divisions, it can fail to capture differences in heating/cooling loads and relative shares within the census division. For example, in the Southeast, Virginia is heating-dominated, while Florida is cooling-dominated.
Revised Approach
Electricity projections by end use are allocated from census divisions to EMM regions by multiplying each of the end-use electricity totals in a given census division by the share of the total that occurs in each EMM region that the census division intersects with. These shares are calculated from county-level annual end use electricity totals from ResStock and ComStock (from the End-Use Load Profiles [EULP] data), which are mapped to EMM region/census division and Scout's residential and commercial building types. An identical approach is applied to transform electricity use data from census divisions to states.
The full mapping between Scout and ResStock and ComStock end uses for the purposes of this disaggregation is in this spreadsheet.
The diagnostic plots below show the electricity projections for the calibration year (2018) before and after the adjustment. These plots show distinct differences, e.g., in residential for FRCC (Florida) where the previous approach overestimates heating and underestimates cooling electricity use.
This pull request changes the way that end use-level electricity use is allocated from census divisions to EMM regions and states.
Previous Approach
We allocated annual total electricity use projections at the end use level by census division to EMM regions across all end uses on the basis of total EMM electricity sales data (resolved by residential and commercial building types, but not end-use-resolved) from EIA. We used the same approach to disaggregate electricity use data from census divisions to states, using EIA state-level electricity consumption data.
This approach preserves the end use shares of the census division-building type combinations within each EMM or state that comprises it.
That's fine for most end uses, but for census divisions with lots of climatic variation and/or large intra-regional differences in electric equipment penetration, e.g., the Southeast or Pacific census divisions, it can fail to capture differences in heating/cooling loads and relative shares within the census division. For example, in the Southeast, Virginia is heating-dominated, while Florida is cooling-dominated.
Revised Approach
Electricity projections by end use are allocated from census divisions to EMM regions by multiplying each of the end-use electricity totals in a given census division by the share of the total that occurs in each EMM region that the census division intersects with. These shares are calculated from county-level annual end use electricity totals from ResStock and ComStock (from the End-Use Load Profiles [EULP] data), which are mapped to EMM region/census division and Scout's residential and commercial building types. An identical approach is applied to transform electricity use data from census divisions to states.
The full mapping between Scout and ResStock and ComStock end uses for the purposes of this disaggregation is in this spreadsheet.
The diagnostic plots below show the electricity projections for the calibration year (2018) before and after the adjustment. These plots show distinct differences, e.g., in residential for FRCC (Florida) where the previous approach overestimates heating and underestimates cooling electricity use.