U.S. Department of EnergyOffice of Scientific and Technical Information
ResStock: Annual Baseline Results with Component Loads
Abstract
The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and high-performance computing. This combination achieves unprecedented granularity and accuracy in modeling the diversity of the housing stock and the distributional impacts of building technologies in different communities. The annual baseline energy results from a national-scale ResStock run use typical meteorological year 3 (TMY3) files for energy simulations. Results include heating and cooling loads for individual components of each building. Component loads describe the heating/cooling load that can be attributed to specific elements of a home, such as heat transfer through walls or internal gains. Additionally, these results include the standard ResStock outputs for housing characteristics and numerous energy outputs by end-use and fuel. A snapshot of the ResStock version used to produce this data, including a configuration file for the run can be found using the Source Code resource link.
- Publication Date:
- Other Number(s):
- 5959
- Research Org.:
- DOE Open Energy Data Initiative (OEDI); National Renewable Energy Lab
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)
- Collaborations:
- National Renewable Energy Lab
- Subject:
- Array; ResStock; United States; building stock; building stock modeling; buildings; buildings efficiency; component load; cooling load; energy; energy efficiency; energy modeling; heat transfer; heating load; housing stock; modeling; power; residential
- OSTI Identifier:
- 2001060
- DOI:
- https://doi.org/10.25984/2001060
Citation Formats
Speake, Andrew, Wilson, Eric, Zhou, Yueyue, and Horowitz, Scott. ResStock: Annual Baseline Results with Component Loads. United States: N. p., 2023.
Web. doi:10.25984/2001060.
Speake, Andrew, Wilson, Eric, Zhou, Yueyue, & Horowitz, Scott. ResStock: Annual Baseline Results with Component Loads. United States. doi:https://doi.org/10.25984/2001060
Speake, Andrew, Wilson, Eric, Zhou, Yueyue, and Horowitz, Scott. 2023.
"ResStock: Annual Baseline Results with Component Loads". United States. doi:https://doi.org/10.25984/2001060. https://www.osti.gov/servlets/purl/2001060. Pub date:Thu Mar 02 23:00:00 EST 2023
@article{osti_2001060,
title = {ResStock: Annual Baseline Results with Component Loads},
author = {Speake, Andrew and Wilson, Eric and Zhou, Yueyue and Horowitz, Scott},
abstractNote = {The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and high-performance computing. This combination achieves unprecedented granularity and accuracy in modeling the diversity of the housing stock and the distributional impacts of building technologies in different communities. The annual baseline energy results from a national-scale ResStock run use typical meteorological year 3 (TMY3) files for energy simulations. Results include heating and cooling loads for individual components of each building. Component loads describe the heating/cooling load that can be attributed to specific elements of a home, such as heat transfer through walls or internal gains. Additionally, these results include the standard ResStock outputs for housing characteristics and numerous energy outputs by end-use and fuel. A snapshot of the ResStock version used to produce this data, including a configuration file for the run can be found using the Source Code resource link.},
doi = {10.25984/2001060},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Mar 02 23:00:00 EST 2023},
month = {Thu Mar 02 23:00:00 EST 2023}
}