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Published June 28, 2023 | Version 5

Scout Benchmark Scenarios for U.S. Building Energy and CO2 Emissions to 2050

  • 1. Lawrence Berkeley National Laboratory
  • 2. National Renewable Energy Laboratory

Description

Overview and Intended Use Cases

These scenarios establish a range of futures for U.S. buildings sector energy use and CO2 emissions to 2050 using Scout, a reproducible and granular model of U.S. building energy use, emissions, and consumer costs developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office (BTO).

Scout benchmark scenario data are suitable for the following example use cases:

  • Setting high-level policy goals for U.S. buildings sector energy use, electricity demand, and CO2 emissions over both the near- and long-term (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050);

  • Exploring the effects of key deployment dynamics driving U.S. buildings sector energy and CO2 emissions to 2050 that could be affected by policy levers (e.g., raising minimum technology performance levels; improving market penetration of commercially available technologies; accelerating electrification and/or retrofit rates; introducing breakthrough technologies to the market);

  • Determining priority segments (regions, building types, and end use/technology types) and sequencing of U.S. buildings sector energy and CO2 emissions reductions and/or changes in total consumption by fuel type to 2050 under a given set of assumptions;

  • Identifying the energy and CO2 impacts or cost effectiveness of specific technologies or operational approaches of interest—in isolation or after considering competition with other measures in a scenario portfolio; and/or

  • Exploring the total cost of deploying different portfolios of building energy efficiency, demand flexibility, and end-use electrification measures, as well as the total consumer energy cost savings potential of those portfolios.

Scenario Summary

A total of 5 scenarios explore total building energy use, CO2 emissions, and technology and energy costs from 2023–2050 under varying levels of demand-side deployment of building efficiency, flexibility, and electrification measures and parallel decarbonization of buildings’ electricity supply. Narrative descriptions of these scenarios are as follows: 

  • IRA: IRA provisions lead to modestly accelerated deployment of HPs/HPWHs but not other efficiency measures in the buildings sector. The power sector decarbonizes under a moderately aggressive scenario that reaches around 75% decarbonization by 2050 vs. 2005 levels.

  • Mid: Policy makers rely mostly on market-based instruments to moderately increase deployment of efficient technology and fuel switching to heat pumps. The power sector decarbonizes under an aggressive scenario that reaches 95% decarbonization by 2050 vs. 2005 levels.

  • High: Policy makers use both regulations and market-based instruments to dramatically accelerate deployment of high efficiency technologies and fuel switching to heat pumps, though building technologies with breakthrough increases in performance at low cost do not materialize on the market. The power sector fully decarbonizes by 2035.

  • Breakthrough: Research and innovation breakthroughs lead to market availability of cost-effective, high-performance building technologies by 2030; these, coupled with accelerated deployment of high efficiency technologies and fuel switching to heat pumps, lead to aggressive buildings sector transformation. The power sector fully decarbonizes by 2035.

  • Inefficient Electrification Sensitivity: Policy makers use regulations and market-based instruments to encourage fuel switching but do not include provisions that require switching to efficient heat pumps, resulting in a substantial amount of switching to inefficient electric resistance heating and water heating technologies. The power sector decarbonizes under a moderately aggressive scenario that reaches around 75% decarbonization by 2050 vs. 2005 levels.

The key input dimensions that are varied to produce the above range of scenarios are as follows:

  • Market-available technology performance range: the energy performance levels of building technologies available for purchase by end use consumers, bounded by a minimum performance “floor” and maximum performance “ceiling”;

  • Load electrification rate and efficiency: the rate at which fossil-fired equipment is converted to electric service, and the efficiency level of the electric equipment;

  • Early retrofits: the fraction of consumers that choose to replace existing building equipment and/or envelope components before the end of their useful lifetimes; and

  • Power grid decarbonization: the annual average CO2 emissions intensity of the electricity supplied to the buildings sector across the modeled time horizon (2023–2050), resolved by grid region.

Refer to the attached “Scenario_Guide" PDF for further scenario details and results; instructions for reproducing scenario results are available in “Scenario_Execution” XLSX.

Results data are reported as an annual time series (2023–2050) at both a national and regional (EMM grid region) spatial resolution. While not reflected in this dataset, annual time series data may be further translated to a sub-annual, hourly resolution for integration with grid modeling—please contact the authors for more information.

What's New in This Version

This set of benchmark scenarios carries forward elements of past versions of this dataset (previously titled “Scout Core Measures Scenario Analysis” and summarized in this paper) while continuing to streamline he scenario design, updating input data, and reflecting the latest policy ambitions regarding deployment of building efficiency, flexibility, and electrification as well as power grid evolution.

The following scenario features are new in this dataset:

  • More aggressive grid scenarios are explored using NREL’s Standard Scenarios, as published via the Cambium dataset. Three scenarios are included:

    • Mid-case (with tax credit phaseout): includes central estimates for inputs such as technology costs, fuel prices, and demand growth with no nascent technologies and electric sector policies as they existed in September 2022; IRA’s PTC and ITC are assumed to start phasing out in 2038.

    • Mid-case with 95% Decarbonization by 2050 (without tax credit phaseout): includes the same set of base assumptions as the first scenario, but nascent technologies are included and there is a national electricity sector decarbonization constraint that linearly declines to 5% of 2005 emissions on net by 2050; IRA’s PTC and ITC are assumed to not phase out.

    • Mid-case with 100% Decarbonization by 2035 (without tax credit phaseout): includes the same set of assumptions as the “Mid-case with 95% Decarbonization by 2050” scenario but with a national electricity sector decarbonization constraint that linearly declines to zero on net by 2035. 

    • The previous version of the benchmark datasets used scenarios from Brattle’s GridSIM model, including an “80% zero-carbon by 2050” and “100% zero-carbon by 2035” grid decarbonization scenario, as well as the AEO 2018 “$25 carbon allowance fee” side case, which reached ~73% carbon-free electricity generation (including nuclear) by 2050.

  • As before, measures in the “best available” tier are deployed with load flexibility features that are based on a previous study of the U.S. building-grid resource; for the current benchmark dataset, however, flexibility load savings shapes have been updated as part of a more recent study of U.S. building decarbonization pathways.  

  • In addition to the updates to the flexibility measure saving shapes described above, we updated the cost, performance, and lifetime inputs for all measures in the analysis to reflect the latest available estimates of technology cost, performance, and lifetime (for example, from EIA’s updated data here, and reflecting multiple updated ENERGY STAR specifications and ASHRAE 90.1-2022). Sourcing information is documented in detail in each measure definition.

  • Electrification is explored only via exogenous model settings, which are based on fuel switching rates developed by Guidehouse for the BTO E3 Initiative. The previous version of the benchmark dataset included scenarios with endogenous representation of electrification based on incentives in the Build Back Better Act. We expect to include refined representation of electrification incentives from the Inflation Reduction Act in a future scenario dataset publication.

  • The measure sets now include two residential and commercial ground-source heat pump measures (one measure in each sector at the “ESTAR” and “Best Available” performance tiers) with updated cost and performance data from the EIA.

Files

Measure_Sets.zip

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Additional details

Related works

References
Journal article: 10.1016/j.joule.2019.07.013 (DOI)
Journal article: 10.1016/j.joule.2021.06.002 (DOI)
Dataset: 10.5281/zenodo.4602369 (DOI)
Preprint: 10.2139/ssrn.4253001 (DOI)