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Analysis approach and input assumptions

The analysis results presented here used the following approach and input assumptions. Differences in approach or format of results may make comparisons to other efficiency potential analyses invalid. More details on the methodology and input assumptions can be found in the NREL technical report, Energy Efficiency Potential in the U.S. Single-Family Housing Stock.

Definition of energy efficiency potential
The energy efficiency potential is presented as annual energy savings specific to each state, assuming full turnover of the stock of equipment and appliances at wear out, which could take 15–30 years, depending on the type of equipment. Full uptake of applicable and cost-effective enclosure improvements was also assumed. Thus, the savings presented are the economic potential, as opposed to market potential which might be informed by historical adoption rates. Policy and programs could be implemented to lower other market barriers and reduce the difference between market potential and economic potential.
Energy savings
The energy savings estimates were calculated using ResStock™, a highly granular model that uses 350,000 physics-based building energy models (OpenStudio®/EnergyPlus™) to statistically represent the diversity of the U.S. single-family housing stock (80 million homes) across a range of climates (216 climate regions), vintages, sizes, fuel types, equipment, insulation, occupancy, etc. For heating/cooling equipment and appliance upgrades considered at wear out, only the incremental savings and cost over the reference replacement scenario (e.g., federal minimum standards) is counted. Detailed descriptions of each improvement scenario are provided in the technical report. The analysis did not account for state/local codes and standards.
Packages/measure interaction
The statewide savings potential values presented in the upper right box are based on simulated packages of cost-effective improvements, including the state's top 10 improvements listed and other, lower priority, improvements. The packages are tailored to maximize the NPV in each of the 350,000 representative home models. The packages account for any diminished returns due to interaction between heating/cooling equipment and enclosure upgrades, as well as the potential for reduced upfront cost through heating/cooling equipment downsizing. The green bar graph shows the statewide economic potential energy savings of the top 10 individual improvements, not accounting for interactions between them.
Cost-effectiveness perspective
The presented energy efficiency potential aggregates savings across all homes in which the improvement or package has a positive net present value (NPV), evaluated using costs and benefits from the building owner’s perspective rather than a utility or societal perspective. Health and safety benefits were not quantified.
Economic assumptions
For NPV calculations, 30 years of future cash flows (utility bill savings, equipment replacement at end of life, and residual value) are brought to the present using a 3% real discount rate. The technical report provides additional results using an alternative (more stringent) cost-effectiveness criterion of simple payback period less than five years.
Tenant-occupied homes
The same economic calculations are used for both owner-occupied and tenant-occupied single-family homes. For tenant-occupied housing, it is assumed that either the building owner pays the utility bills or rent is increased by an amount equal to utility bill savings.
Utility prices
Electricity rates were assumed to be flat volumetric charges ($/kWh), were derived from EIA Form 861 sales and revenue data (2013), assumed $8 per month in fixed customer charges, and were applied at the county level based on utility service territories reported on EIA Form 861. Rates for on-site fuel use were derived from 2015 EIA data (natural gas) and 2010 EIA data (propane and fuel oil), and were applied by state.
Improvement costs
Improvement costs include all material, labor, and overhead costs paid by the building owner. In the case of equipment replaced at wear out, only the incremental cost of the improvement over the reference (e.g., federal minimum standards) is included. As noted above, future replacement costs and residual value at the end of the 30-year cash flow analysis are accounted for. With a few exceptions, the initial costs and lifetimes for each upgrade and reference scenario are national averages sourced from the National Residential Efficiency Measures Database.
State, utility, and local incentives (e.g., rebates) were not included in the economic analysis, due to the large number of unique incentives that exist. A federal income tax credit for residential energy efficiency was included and assumed to be available in future years (capped at $500 per household). The eligible improvements include high-efficiency heating, cooling, and water heating equipment, as well as insulation and windows upgrades.
Sectoral scope
The analysis covers single-family detached housing only. The housing stock characteristics tool developed for ResStock currently is limited to single-family detached housing and excludes all multifamily buildings (including duplexes and townhomes) as well as mobile homes. Expansion to the multifamily sector is planned in 2018.
Geographic scope
The fact sheets are limited to the 48 contiguous U.S. states. Sources of housing characteristics and consumption data (particularly the Residential Energy Consumption Survey) for Alaska, Hawaii, and U.S. territories tend to have low sample sizes, resulting in high uncertainty in the data.
Temporal scope
House counts and housing characteristics are a snapshot based on circa-2012 data; projections of future construction and changes in housing characteristics were not included in this analysis.

The ResStock software can be used to analyze additional scenarios with different input assumptions, for additional technologies, or with additional input data for specific city, state, or utility territories. ResStock is free, open source, and publicly available, with the large-scale simulations running on Amazon cloud computing. See for more information on using the software, and to learn how to partner with NREL or third-party consultants on additional analyses.

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