TY - GEN
T1 - End-Use Load Profiles for the U.S. Building Stock: Methodology and Results of Model Calibration, Validation, and Uncertainty Quantification
T2 - U.S. Department of Energy (DOE), Energy Efficiency & Renewable Energy (EERE)
AU - Wilson, Eric
AU - Parker, Andrew
AU - Fontanini, Anthony
AU - Present, Elaina
AU - Reyna, Janet
AU - Adhikari, Rajendra
AU - Bianchi, Carlo
AU - CaraDonna, Christopher
AU - Dahlhausen, Matthew
AU - Kim, Janghyun
AU - LeBar, Amy
AU - Liu, Lixi
AU - Praprost, Marlena
AU - Zhang, Liang
AU - DeWitt, Peter
AU - Merket, Noel
AU - Speake, Andrew
AU - Hong, Tianzhen
AU - Li, Han
AU - Mims Frick, Natalie
AU - Wang, Zhe
AU - Blair, Aileen
AU - Horsey, Henry
AU - Roberts, David
AU - Trenbath, Kim
AU - Adekanye, Oluwatobi
AU - Bonnema, Eric
AU - El Kontar, Rawad
AU - Gonzalez, Jonathan
AU - Horowitz, Scott
AU - Jones, Dalton
AU - Muehleisen, Ralph
AU - Platthotam, Siby
AU - Reynolds, Matthew
AU - Robertson, Joseph
AU - Sayers, Kevin
AU - Li, Qu
N1 - See NREL/TP-5500-82689 for executive summary
PY - 2022
Y1 - 2022
N2 - The United States is embarking on an ambitious transition to a 100% clean energy economy by 2050, which will require improving the flexibility of electric grids. One way to achieve grid flexibility is to shed or shift demand to align with changing grid needs. To facilitate this, it is critical to understand how and when energy is used. High- quality end-use load profiles (EULPs) provide this information, and can help cities, states, and utilities understand the time-sensitive value of energy efficiency, demand response, and distributed energy resources. Publicly available EULPs have traditionally had limited application because of age and incomplete geographic representation (Frick, Eckman, and Goldman 2017; Frick 2019). To help fill this gap, the U.S. Department of Energy (DOE) funded a three-year project - End-Use Load Profiles for the U.S. Building Stock - that culminated in the release of a publicly available dataset1 of simulated EULPs representing residential and commercial buildings across the contiguous United States. The motivation for this work is further detailed in a November 2019 report: Market Needs, Use Cases, and Data Gaps (Mims Frick et al. 2019). This Methodology and Results report provides detailed descriptions of how the dataset was developed, intended for an audience of dataset and model users interested in the technical details. These details include descriptions of all of the model improvements made for calibration and the final comparisons to empirical data sources. A companion report, End-Use Load Profiles for the U.S. Building Stock: Applications and Opportunities, will be published subsequently and will describe example applications and considerations for using the dataset, intended for an audience of general dataset users.
AB - The United States is embarking on an ambitious transition to a 100% clean energy economy by 2050, which will require improving the flexibility of electric grids. One way to achieve grid flexibility is to shed or shift demand to align with changing grid needs. To facilitate this, it is critical to understand how and when energy is used. High- quality end-use load profiles (EULPs) provide this information, and can help cities, states, and utilities understand the time-sensitive value of energy efficiency, demand response, and distributed energy resources. Publicly available EULPs have traditionally had limited application because of age and incomplete geographic representation (Frick, Eckman, and Goldman 2017; Frick 2019). To help fill this gap, the U.S. Department of Energy (DOE) funded a three-year project - End-Use Load Profiles for the U.S. Building Stock - that culminated in the release of a publicly available dataset1 of simulated EULPs representing residential and commercial buildings across the contiguous United States. The motivation for this work is further detailed in a November 2019 report: Market Needs, Use Cases, and Data Gaps (Mims Frick et al. 2019). This Methodology and Results report provides detailed descriptions of how the dataset was developed, intended for an audience of dataset and model users interested in the technical details. These details include descriptions of all of the model improvements made for calibration and the final comparisons to empirical data sources. A companion report, End-Use Load Profiles for the U.S. Building Stock: Applications and Opportunities, will be published subsequently and will describe example applications and considerations for using the dataset, intended for an audience of general dataset users.
KW - building stock modeling
KW - buildings
KW - electricity demand
KW - energy models
KW - load profiles
U2 - 10.2172/1854582
DO - 10.2172/1854582
M3 - Technical Report
ER -