End-Use Load Profiles for the U.S. Building Stock
NREL and its research partners have developed a database of end-use load profiles (EULP) representing all major end uses, building types, and climate regions in the U.S. commercial and residential building stock.
End-use load profiles are critically important to understanding the time-sensitive value of energy efficiency, demand response, and other distributed energy resources. This foundational dataset can help electric utilities, grid operators, manufacturers, government entities, and research organizations make critical decisions about prioritizing research and development, utility resource and distribution system planning, and state and local energy planning and regulation.
The team, which includes Lawrence Berkeley National Laboratory (LBNL) and Argonne National Laboratory, used an innovative approach that benefited from the reach, cost-effectiveness, and granularity of physics-based building stock modeling using the ResStock™ and ComStock™ capabilities developed by NREL for the U.S. Department of Energy. These stock models have been informed by and validated against the best-available ground-truth data—from whole-building interval meter data, submetering studies, and other data sources. The resulting public database was generated using the stock models and does not contain the ground-truth data used to develop and calibrate the models.
Foundational Dataset of ~1 Million End-Use Load Profiles for the U.S. Residential and Commercial Building Stock
Building stock models calibrated through 70+ model updates, supported by data:
- Electric load data from 11 utilities and 2.3 million meters
- 15 end-use metering datasets
Example: Texas Residential Load (modeled end-uses)
At the most fundamental level, this dataset is the output of approximately 900,000 (550,000 ResStock plus 350,000 ComStock) building energy models. The output of each building energy model is 1 year of energy consumption in 15-minute intervals, separated into end-use categories. The dataset has also been formatted to be accessible in three ways—via pre-aggregated load profiles in downloadable spreadsheets, a web viewer, and a detailed format that can be queried with big data tools—to meet the needs of many different users and use cases.
Many users seek end-use load profiles that reflect the sum or average of all buildings of a given type in a given geographic area. These are referred to as "aggregate'' load profiles. To support many use cases, aggregates for the following geographic resolutions were created:
- 16 ASHRAE/International Energy Conservation Code climate zones
- 5 U.S. Department of Energy Building America climate zones
- 8 Electric System independent system operator and regional transmission organization regions
- 2,400+ U.S. Census Public Use Microdata Areas
- 3,000+ U.S. counties.
Each aggregate load profile is represented by a single comma-separated value file, which can be opened using common data analysis tools, such as Microsoft Excel. There is a column for each end-use category and fuel type and a row for each 15-minute time period. In addition to the timeseries data, a file contains a list of identifiers for all the building energy models included in each aggregate. These identifiers can be cross-referenced against a separate tab-separated value file, which contains the characteristics (age, type, height, etc.) of each building energy model. In this manner, it is possible to understand the characteristics of the building stock for each aggregate.
County-level aggregates are primarily provided to facilitate further aggregation to larger geographic areas, such as utility service territories. ResStock and ComStock model buildings in proportion to how real buildings are distributed. Heavily populated urban counties contain many buildings, so ResStock and ComStock include many models in these areas, and the aggregate load profiles for these areas are robust. However, rural counties in sparsely populated areas do not contain many buildings. Thus, ResStock and ComStock do not include many building energy models in these areas, and the aggregate load profiles for these areas are less robust. The team highly recommends rolling up aggregates to include a minimum of 1,000 models to increase the robustness of the load profiles.
A full dataset of individual building/dwelling unit load profiles is available at data.openei.org. See the README.md file for details.
The raw dataset is a group of several hundred thousand files, each containing the outputs of an individual building energy model, totaling 17 terabytes. Although processing these results using conventional desktop computing is impractical, several cloud service providers make the required computing power and querying technology available to those with the technical skill set. Additionally, some users may have in-house access to advanced computing resources or want to download a small subset of individual building load profiles for their own custom use cases. To facilitate these use cases, the raw individual building results, along with the corresponding building characteristics, have been published to a public website. They may be downloaded directly from this website or queried in place using big data technologies.
The large number of building energy models used by ResStock and ComStock to represent the building stock makes it impractical for most organizations to run the full set themselves. However, some users expressed the desire to have access to the models for other use cases, such as modeling a smaller geographic area using a subset of the models or serving as a starting point for other modeling efforts. For these reasons, the individual building energy models have been published online. These models are available in the OpenStudio® format, to allow for simulations with EnergyPlus™. A file of building characteristics allows users to identify buildings with a target set of properties to download and use.
Led by NREL's end-use load profiles research team, End-Use Load Profiles for the U.S. Building Stock: Applications Methodology and Results of Model Calibration, Validation, and Uncertainty Quantification, is accessible through the NREL library, free and open to the public.
Stay tuned for End-Use Load Profiles for the U.S. Building Stock: Applications and Opportunities, which will be published by LBNL to detail deployment opportunities for general users.
This technical report documents the EULP dataset, including detailed description of model improvements made for calibration, along with an explanation of validation and uncertainty of results.
An executive summary of End-Use Load Profiles for the U.S. Building Stock: Applications Methodology and Results of Model Calibration, Validation, and Uncertainty Quantification is available as a separate document.
End-Use Load Profiles for the U.S. Building Stock: Market Needs, Use Cases, and Data Gaps highlights first-year project accomplishments including the formation of a technical advisory group, identification of market needs and data gaps, and next steps to verify the accuracy of calibrated model outputs.
End-Use Load Profiles Dataset Access Demonstration provides step-by-step instructions, showing several ways to access the EULP dataset. (October 2021)
Three Years in the Making: Calibrated, Validated, and Publicly Available End Use Load Profiles for the U.S. Building Stock, presented by Eric Wilson and Andrew Parker from NREL and Natalie Mims Frick from LBNL, provides an overview of the project, details options to access the end-use load profiles, and shares information on two forthcoming reports. (Oct. 28, 2021)
End-Use Load Profiles for the U.S. Building Stock: Market Needs, Use Cases, and Data Gaps, presented by LBNL and NREL, details the project's first year. (Dec. 10, 2019)
Building on the success of the EULP project, continued research will produce national datasets of measure impact profiles (also known as savings shapes) to empower analysts to tackle a broad range of questions concerning the potential of building electrification measures and more. The initial focus will be on a limited set of residential sector efficiency and electrification measures and may be extended to additional measures, demand flexibility, and commercial building measures in future years.
Technical Advisory Group
A technical advisory group guided the dataset development to ensure that the direction and outcomes of the work were aligned with market needs. The technical advisory group included roughly 100 representatives from organizations that were likely to use the resulting load profiles in their work, including utility companies, utility program implementers, grid operators, consultancies, research centers, state regulatory agencies, and regional energy efficiency organizations.
Technical advisory group presentations are available for the dates below:
Frequently Asked Questions
Wilson et al. 2021. End-Use Load Profiles for the U.S. Building Stock: Methodology and Results of Model Calibration, Validation, and Uncertainty Quantification. NREL/TP-5500-80889. https://www.nrel.gov/docs/fy22osti/80889.pdf.
Data Sharing Partner Acknowledgments
We are grateful to the data sharing partners who shared anonymized data with the project team or helped the team find data. Future users of the load profiles created by this project owe these partners a debt of gratitude; without their significant effort and contributions, the project would not have been possible.
Northwest Energy Efficiency Alliance, Pecan Street, Florida Solar Energy Center, Southern Company, and Massachusetts Energy Efficiency Advisory Council deserve special mention for their leadership and foresight into end-use load research, as do ComEd and ecobee for making anonymized data broadly available to researchers.
- Adams 12 Five Star Schools
- AES Indiana
- Alliance Center
- Ameren Missouri
- Bert Brains
- Bonneville Power Administration
- Center for Energy and Environment
- Center for the Built Environment
- Cherryland Electric Cooperative
- City of Fort Collins Utilities/Colorado State University
- City of Tallahassee Utilities
- Clarkson University
- Efficiency Maine
- Horry Electric Cooperative
- Hot Water Research
- kW Engineering
- Los Angeles Department of Water and Power
- Massachusetts Program Administrators
- National Rural Electric Cooperative Association
- New City Energy
- New York State Energy Research and Development Authority
- Northeast Energy Efficiency Partnerships
- NV Energy
- Portland General Electric
- Powerhouse Dynamics
- Resource Central
- Seattle City Light
- Southern Company
- Vermont Energy Investment Corporation/Green Mountain Power
- Xcel Energy.
We want to hear from you! How are you using EULP datasets?
To share your use case or for more information, contact email@example.com.