Explore the Affordable Home Energy Shot for insight into DOE’s goals of halving upfront home upgrade costs and reducing energy bills by 20% within a decade. Analyzing and decarbonizing the residential building stock is crucial for fostering innovative breakthroughs and cost.
In the United States, residential energy consumption comprises 21% of total energy use. Understanding the characteristics of the residential building stock and the impacts of varying strategies on energy use and costs is key to developing and implementing best practices that enable high-performing, affordable, reliable, comfortable, and healthy homes.
This web page serves as a guide for entities and stakeholders, including state and local energy analysts, utilities, manufacturers, and program implementers. These resources allow users to explore the impacts of multiple analysis pathways by answering “what if?” Extensive modeling results are available to the public to support the analysis of specific use cases. For example, an analyst may choose to produce derivative products based on the public datasets.
The following is a comprehensive, though non-exhaustive, list of studies and tools for residential buildings analysis.
Characterizing the Existing U.S. Housing Stock
U.S. Building Stock Characterization StudyAn overview of the diversity of existing buildings and energy use intensity of different segments. | |||
Resource | Publish Date | Audience | Use Case |
U.S. Building Typology Segmentation Residential | May 27, 2021 | State energy offices, analysts, utilities | Analyze representative data of the U.S. residential building stock to inform decision-making around pathways to decarbonization |
Example analysis questions this dashboard can answer:
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Resource | Publish Date | Audience | Use Case |
U.S. Building Typology Segmentation Residential Thermal Component Loads | April 12, 2021 (updated Nov. 15, 2023) | Building analysts, consultants | Visualize how over a dozen building components (e.g., windows, infiltration, etc.) affect residential heating and cooling loads with climate-zone specific granularity |
Example analysis questions this dashboard can answer:
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ResStock: End-Use Load Profiles for the U.S. Building StockEnd-use load profiles are critically important to understanding the time-sensitive value of energy efficiency, demand response, and other distributed energy resources. | ||
Publish Date | Audience | Use Case |
October 2021 | Electric utilities, grid operators, manufacturers, government entities, and research organizations | Explore visual representations of residential loads at the end-use level at 15-minute intervals for a whole year to conduct analysis on load shifting and shaving. |
Example analysis question this resource can answer:
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Exploring Changes to the Existing U.S. Housing Stock
ResStock Datasets for National Decarbonization Analysis OF Residential Buildings | ||||
ResStock™ is a tool that models the energy consumption of the U.S. housing stock. It is developed and maintained by the National Renewable Energy Laboratory (NREL). Its two main functions are:
The ResStock output dataset includes the energy consumption of each modeled dwelling unit and its respective dwelling unit characteristics (e.g., insulation level, foundation type, wall construction) and household characteristics (e.g., setpoint properties, occupant information, household income). A dwelling unit is a single housing residence, such as one townhome, a single apartment within an apartment building, or a single-family detached home. | ||||
Purpose | ||||
These datasets were published for analysts to explore residential decarbonization scenarios and evaluate the impact of residential energy-efficiency and electrification measure packages on energy consumption, energy bills, and greenhouse gas (GHG) emissions. | ||||
Resource | Results Format | Publish Date | Audience | Use Case |
2024.2 | Timeseries and annual | March 2024 | Utilities, analysts, implementers, regional energy-efficiency organizations | Use 15 measure packages in this dataset (and 16 in 2022.1) for long-term load forecasting, electrification planning, and distribution system planning to evaluate multiple residential decarbonization scenarios to gain insights on bill savings, GHG reductions, and energy savings. |
2024.1 | Annual | February 2024 | State and local planners, energy-efficiency research organizations, analysts | Use 260 energy-efficiency and electrification measure packages to synthesize residential decarbonization scenarios and analyze state- or county-wide (if applicable) results. |
2022.1 | Timeseries and annual | September 2022 | Utilities, analysts, implementers, regional energy-efficiency organizations, state and local planners, and implementers | Analyze "what-if" scenarios using 16 energy-efficiency and electrification measure packages, with results for different household income groups (percentage of area median income). |
State Impacts Dashboard | Annual | |||
Example analysis questions these resources can answer:
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Supplementary Resource | ||||
Time series data can be paired with Lawrence Berkeley National Laboratory’s Time-Sensitive Value Calculator to estimate hourly electricity system costs. | ||||
Instruction | ||||
ResStock Training Video - State Impacts Dashboard (youtube.com) | ||||
ResStock Training Video - Timeseries Data Viewer and Downloader (youtube.com) | ||||
ResStock Training Video - Accessing Raw Annual and Timeseries Data (youtube.com) | ||||
ResStock 2022.1 Dataset Public Webinar | ||||
ResStock 2024.2 Dataset Public Webinar |
Examples of End-Use Load Profiles for Utility Planning
Lawrence Berkeley National Lab (Berkeley Lab), with funding from the U.S. DOE, published a report, Practical Guidance on Using End-Use Load Profile Data, highlighting multiple use cases for the ResStock and ComStock end-use load profiles. Examples include forecasting electricity demand growth from building electrification, integrated resource planning, transmission planning, and distribution system planning. More recently, Berkeley Lab used ResStock and ComStock data to provide technical assistance to two municipal utilities. The analysis focuses on evaluating the potential impact of varying levels of energy-efficiency adoption on mitigating peak demand growth from building and transportation electrification.
Resource Managing changes in peak demand from building and transportation electrification with energy efficiency: Final Report for Sacramento Municipal Utility District (SMUD) | |
Publish Date | Author |
May 2024 | Lawrence Berkeley Lab (LBL) |
Geographic Area of Focus | |
SMUD (California) | |
Summary | |
In collaboration with SMUD, Berkeley Lab developed three research questions to explore emerging issues of interest to the utility:
To answer these questions, Berkeley Lab modeled baseline electrification, high-efficiency electrification, and cold snap scenarios. The analysis outputs include an hourly net demand forecast, provided in five-year increments, for the study period 2025-2040. LBL used ResStock and ComStock data calibrated with historical SMUD load data to develop the forecasts. Findings from the analysis include that summer and winter peak demand significantly increased over the study period due to policy-driven electric vehicle and building electrification adoption. In the cold snap scenario, the system becomes winter peaking. However, in the high-efficiency building electrification scenario, residential envelope upgrades and high-efficiency heat pumps significantly reduce increases in summer and winter peak demand from electrification and new construction. |
Resource Managing changes in peak demand from building and transportation electrification with energy efficiency and demand flexibility: Final Report for Fort Collins Utilities | |
Publish Date | Author |
May 2024 | Lawrence Berkeley Lab (LBL) |
Geographic Area of Focus | |
Fort Collins Utilities (Colorado) | |
Summary | |
Berkeley Lab’s analysis for Fort Collins Utilities explored the peak demand impacts of residential building and transportation electrification on 15 distribution feeders using ResStock end-use load profiles. Forecast scenarios consider two levels of building electrification efficiency (baseline and high) and three levels of electrification technology adoption (low, medium, and high). The study finds that electrification technology adoption increases net peak demand (both summer and winter) through 2040 across the selected feeders but not substantially enough to cause violations of the thermal limits of the circuits. The study also shows that high-efficiency electrification significantly reduces both summer and winter net peak demand relative to the baseline scenario, with heat pump and envelope upgrades driving most of the reductions. |
Impacts of Heating Electrification
Heat Pumps for All? The Distributional Costs and Benefits of Residential Air-Source Heat Pumps in the United StatesElectrifying heating in buildings with air-source heat pumps and related upgrades yields positive greenhouse gas reductions across all U.S. states, with varying impacts on household energy bills and consumer net present value, suggesting the potential need for incentives and innovations to bring down the upfront cost, especially for high-performance, cold-climate heat pumps. | ||
Resources | ||
Publish Date | Audience | Use Case |
August 2023 | Analysts, state energy offices, program implementers | View emissions and cost impacts of varying heat pump efficiency levels by state to inform policy making and discern best practices. |
Example analysis questions these resources can answer:
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Advanced Building Construction Initiative
Accelerating Residential Building Decarbonization: Market Guidance to Scale Zero-Carbon-Aligned (ZCA) Buildings | |
Publish Date | Audience |
January 2024 | Building industry stakeholders, including integrated solution providers, industrialized fabricators of building assemblies, design professionals, building owners, real estate developers, policymakers. |
Definition of Zero-Carbon Aligned | |
Zero-carbon aligned: No on-site fossil fuel use, low power and thermal loads, obtains all energy from a carbon-neutral grid and/or carbon-neutral local resources currently or before 2050 under a planned scenario, and reduces impact on the grid through peak and general demand reduction and grid interactivity (or, alternatively, through off-grid operation), with the aim of a decarbonized US building stock before 2050. | |
Summary | |
This report provides technical information and guidance on how to achieve zero-carbon new and existing residential buildings at scale. It offers guidance and cost targets for new construction and retrofit packages in priority residential building segments and analysis on market trends, regulations, volume, and costs for new construction. In retrofitting, specific ZCA packages are assigned to building segments, prioritizing them by geography and type for estimates of the market size. |
Interactive Dashboard and Data Reviewer for the Accelerating Residential Building Decarbonization: Market Guidance to Scale ZCA Buildings | ||
Resource: Data viewer and dashboard | ||
Publish Date | Audience | Use Case |
February 2023 | Various building industry stakeholders including manufacturers, analysts, architects, and design professionals | Interact with and visualize the technical performance guidance and estimated cost targets for retrofit packages based on the underlying report’s analysis that of specific ZCA retrofit packages to existing building segments. |
Example analysis questions this resource can answer:
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Supplementary Resource | ||
This report assesses energy savings, utility bill impacts, and carbon emissions of four simulated upgrade packages, aiming to set performance and cost targets for advancing industrialized construction innovations to achieve ZCA residential buildings. |
Retrofit Decision Tool (RDT) | ||
Publish Date | Audience | Use Case |
June 2023 | Homeowners, energy auditors, homeowners, analysts, architects, remodelers | Through ten simple questions, the RDT assists users with identifying which of the four model packages is the likely pathway to become zero carbon aligned. |
Example analysis questions this resource can answer:
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