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

<strong>Overview and Intended Use Cases</strong> 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. <strong>Scenario Summary</strong> 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. <strong>What's New in This Version</strong> 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 -&gt; Scenario 6: HR 1T-2T-3T Scenario 2.2: EE1.ELe1a.P1 -&gt; Scenario 7: HR 1T-2T-3T FS0 Scenario 2.3: EE1.ELe1b.P1 -&gt; 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 <em>without</em> 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.<strong>概述与适用场景</strong> 本数据集基于美国国家实验室为美国能源部建筑技术办公室（Building Technologies Office，BTO）开发的可复现、细粒度的美国建筑能源使用、碳排放及消费者成本模型Scout（scout.energy.gov），构建了到2050年美国建筑部门能源使用与二氧化碳（CO₂）排放的多种未来情景。Scout基准情景数据适用于以下典型应用场景：为美国建筑部门制定到2050年的高层政策目标（例如，到2030年实现建筑二氧化碳排放较2005年降低X%，到2050年降低Y%）；探究影响美国建筑部门到2050年能源使用与二氧化碳排放的关键驱动因素的作用效果，此类因素可受政策工具调控（例如，提高技术最低性能标准、加快电气化与改造速率、将突破性技术推向市场）；在给定假设条件下，确定美国建筑部门到2050年实现能源使用与二氧化碳减排的优先细分领域（区域、建筑类型、终端用能/技术类型）及实施顺序；以及/或者识别特定目标技术或运营方式的能源与碳排放影响或成本效益——可单独评估，也可结合情景组合中其他措施的竞争效应进行评估。<strong>情景概述</strong> 本数据集共包含8个情景，用于探究2022年至2050年间，建筑能源使用的需求侧与供给侧变化对美国年度建筑能源使用及二氧化碳排放的影响。情景分为三组，分别对应建筑脱碳的低、中、最优潜力情景。单个情景通过四大输入维度进行区分：市场可用技术性能范围（EE）：终端消费者可采购的建筑技术的能源性能水平，以最低性能“下限”与最高性能“上限”为边界；负荷电气化（EL）：化石燃料设备转换为电力服务的速率，以及电力设备的效率水平；早期改造（R）：选择在设备与围护结构部件使用寿命到期前更换它们的消费者比例；电网（P）：建模时间范围（2022–2050）内供应给建筑部门的电力的年度平均二氧化碳排放强度，按电网区域细分。如需了解情景细节与结果的更多信息，请参阅附件"Scenario_Guide" PDF文件；情景结果复现操作说明可在"Scenario_Summary_Execution" XLSX文件中获取。结果数据以年度时间序列（2022–2050）形式呈现，空间分辨率涵盖全国与区域（EMM电网区域）两个层级。尽管本数据集未包含此类数据，但年度时间序列数据可进一步转换为亚年度、小时级分辨率，以适配电网建模集成需求——如需更多信息，请联系数据集作者。<strong>本版本更新内容</strong> 本套基准情景延续了该数据集过往版本（原名为"Scout Core Measures Scenario Analysis"，已在本文中汇总）的部分内容，同时优化了情景设计，并反映了关于建筑能效提升、灵活性应用与电气化部署以及电网演进的最新政策目标。本数据集中有三个情景可对应至过往版本的情景：情景2.1：EE1.P1 → 情景6：HR 1T-2T-3T；情景2.2：EE1.ELe1a.P1 → 情景7：HR 1T-2T-3T FS0；情景2.3：EE1.ELe1b.P1 → 情景8：HR 1T-2T-3T FS20。本数据集新增了以下情景特性：“最优可用”层级的措施搭载了基于美国建筑-电网资源既往研究得出的负荷灵活性特性，过往版本仅考量了能效与电气化措施；通过在措施竞争中纳入参考情景技术，并假设相关法规/标准自某一特定年份起将此类技术从市场可用组合中移除，探究逐步提高市场可用技术性能“下限”的影响，过往版本仅探究了提高技术性能“上限”的效应；反映了对顶级“前瞻性”层级措施性能的更高要求，过往版本中该类措施层级大多对应2016年美国能源部建筑技术办公室（BTO）年度最低产品性能规划（MYPP）；本次通过内生与外生两种模型设置探究电气化效果：前者基于Scout的经济措施竞争模型，后者基于Guidehouse为BTO E3倡议开发的燃料转换情景，过往版本仅探究了内生电气化效应；本次还探究了低效电气化场景（过往版本未涉及此类场景）：在此类场景中，消费者将化石燃料供暖与热水设备更换为电电阻加热与热泵技术的混合方案，混合比例由2021年能源展望（AEO 2021）参考案例中该类技术的销售份额数据确定；通过将除一个情景外的所有情景设置为<em>不进行早期改造</em>，以隔离早期改造行为的影响，过往版本默认采用1%的早期改造率；本次采用Brattle的GridSIM模型构建了更具进取性的电网情景，共包含两类情景：到2050年实现80%脱碳的电网，以及到2035年实现100%脱碳的电网。过往版本采用的是AEO 2018的“25美元碳排放配额费”附加情景，该情景到2050年可实现约73%的零碳电力发电（含核电）。