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Published May 31, 2022 | Version 4

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 (scout.energy.gov), 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 the U.S. buildings sector to 2050 (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050);

  • exploring the effects of key 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; 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 to 2050 under a given set of assumptions; and/or

  • identifying the energy and emissions 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.

Scenario Summary

A total of 8 scenarios explore the effects of changes across both the demand- and supply-side of building energy use on annual U.S. building energy use and CO2 emissions from 2022–2050. Scenarios are organized into three groups representing low, moderate, and best-case potentials for building decarbonization, respectively. Individual scenarios are distinguished by four input dimensions:

  • market-available technology performance range (EE): 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 (EL): the rate at which fossil-fired equipment is converted to electric service, and the efficiency level of the electric equipment;

  • early retrofits (R): 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 (P): the annual average CO2 emissions intensity of the electricity supplied to the buildings sector across the modeled time horizon (2022–2050), 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_Summary_Execution” XLSX.

Results data are reported as an annual time series (2022–2050) 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 also streamlining the scenario design and reflecting updated policy ambitions regarding deployment of building efficiency, flexibility, and electrification as well as power grid evolution. Three scenarios in the current dataset map back to past scenarios:

  • Scenario 2.1: EE1.P1 -> Scenario 6: HR 1T-2T-3T

  • Scenario 2.2: EE1.ELe1a.P1 -> Scenario 7: HR 1T-2T-3T FS0

  • Scenario 2.3: EE1.ELe1b.P1 -> Scenario 8: HR 1T-2T-3T FS20

The following scenario features are new in this dataset:

  • 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. Past versions reflected only efficiency and electrification measures.

  • The effects of progressively raising the market-available technology performance “floor” are explored by including reference case technologies in the measure competition and assuming codes/standards remove these technologies from the market-available mix beginning in a certain year. Past versions only explored the effects of a higher technology “ceiling”. 

  • Increasing ambitions for the top “Prospective” tier of measure performance are reflected. Past versions mapped much of this measure tier to the 2016 BTO MYPP.

  • Electrification is explored via both endogenous and exogenous model settings, where the former is based on Scout’s economic measure competition models and the latter is based on fuel switching scenarios developed by Guidehouse for the BTO E3 Initiative. Past versions only explored endogenous electrification.

  • Inefficient electrification is explored (past versions did not explore inefficient electrification). In such cases, consumers switch fossil-based heating and water heating equipment to a mix of electric resistance and heat pump technologies, with the mix determined by AEO 2021 Reference Case sales share data for these technologies.

  • The effects of early retrofitting behavior are isolated by running all but one scenario without early retrofits. Past versions assumed a 1% early retrofit rate.

  • More aggressive grid scenarios are explored using Brattle’s GridSIM model. Two scenarios are included—an 80% decarbonized grid by 2050 and 100% decarbonized grid by 2035. Past versions used the AEO 2018 “$25 carbon allowance fee” side case, which reached ~73% carbon-free electricity generation (including nuclear) by 2050.

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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)