Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)
This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api and through PyPI (pip install NREL-dsgrid-legacy-efs-api). The data format is HDF5. The API is written in Python.
This initial dsgrid data set, whose description was originally published in 2018, covers electricity demand in the contiguous United States (CONUS) for the historical year of 2012. It is a proof-of-concept demonstrating the feasibility of reconciling bottom-up demand modeling results with top-down information about electricity demand to create a more detailed description than is possible with either type of data source on its own. The result is demand data that is more highly resolved along geographic, temporal, sectoral, and end-use dimensions as may be helpful for conducting electricity sector-wide "what-if" analysis of, e.g., energy efficiency, electrification, and/or demand flexibility.
Although we conducted bottom-up versus top-down validation, the final residuals were significant, especially at higher geographic and temporal resolution. Please see the Executive Summary and/or Section 3 of the report to obtain an understanding of the data set limitations before deciding whether these data are suitable for any particular use case.
New dsgrid datasets are under development. Please visit https://www.nrel.gov/analysis/dsgrid.html for the latest information which is also linked in the data resources.
Citation Formats
TY - DATA
AB - This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api and through PyPI (pip install NREL-dsgrid-legacy-efs-api). The data format is HDF5. The API is written in Python.
This initial dsgrid data set, whose description was originally published in 2018, covers electricity demand in the contiguous United States (CONUS) for the historical year of 2012. It is a proof-of-concept demonstrating the feasibility of reconciling bottom-up demand modeling results with top-down information about electricity demand to create a more detailed description than is possible with either type of data source on its own. The result is demand data that is more highly resolved along geographic, temporal, sectoral, and end-use dimensions as may be helpful for conducting electricity sector-wide "what-if" analysis of, e.g., energy efficiency, electrification, and/or demand flexibility.
Although we conducted bottom-up versus top-down validation, the final residuals were significant, especially at higher geographic and temporal resolution. Please see the Executive Summary and/or Section 3 of the report to obtain an understanding of the data set limitations before deciding whether these data are suitable for any particular use case.
New dsgrid datasets are under development. Please visit https://www.nrel.gov/analysis/dsgrid.html for the latest information which is also linked in the data resources.
AU - Hale, Elaine
A2 - Horsey, Henry
A3 - Johnson, Brandon
A4 - Muratori, Matteo
A5 - Wilson, Eric
A6 - Borlaug, Brennan
A7 - Christensen, Craig
A8 - Farthing, Amanda
A9 - Hettinger, Dylan
A10 - Parker, Andrew
A11 - Robertson, Joseph
A12 - Rossol, Michael
A13 - Stephen, Gord
A14 - Wood, Eric
A15 - Vairamohan, Baskar
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.25984/1823248
KW - energy
KW - power
KW - demand
KW - Electrification Futures Study
KW - dsgrid
KW - historial year
KW - modeled data
KW - high-resolution
KW - electricity demand
KW - demand-side
KW - demand side
KW - model
KW - analysis
KW - processed data
KW - electrification
KW - demand flexibility
KW - validation
KW - grid
KW - electrical
KW - PyPl
KW - python
KW - contiguous United States
KW - load
KW - data
KW - electricity
LA - English
DA - 2018/07/08
PY - 2018
PB - National Renewable Energy Laboratory
T1 - Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)
UR - https://doi.org/10.25984/1823248
ER -
Hale, Elaine, et al. Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS). National Renewable Energy Laboratory, 8 July, 2018, Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1823248.
Hale, E., Horsey, H., Johnson, B., Muratori, M., Wilson, E., Borlaug, B., Christensen, C., Farthing, A., Hettinger, D., Parker, A., Robertson, J., Rossol, M., Stephen, G., Wood, E., & Vairamohan, B. (2018). Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS). [Data set]. Open Energy Data Initiative (OEDI). National Renewable Energy Laboratory. https://doi.org/10.25984/1823248
Hale, Elaine, Henry Horsey, Brandon Johnson, Matteo Muratori, Eric Wilson, Brennan Borlaug, Craig Christensen, Amanda Farthing, Dylan Hettinger, Andrew Parker, Joseph Robertson, Michael Rossol, Gord Stephen, Eric Wood, and Baskar Vairamohan. Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS). National Renewable Energy Laboratory, July, 8, 2018. Distributed by Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1823248
@misc{OEDI_Dataset_4130,
title = {Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)},
author = {Hale, Elaine and Horsey, Henry and Johnson, Brandon and Muratori, Matteo and Wilson, Eric and Borlaug, Brennan and Christensen, Craig and Farthing, Amanda and Hettinger, Dylan and Parker, Andrew and Robertson, Joseph and Rossol, Michael and Stephen, Gord and Wood, Eric and Vairamohan, Baskar},
abstractNote = {This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api and through PyPI (pip install NREL-dsgrid-legacy-efs-api). The data format is HDF5. The API is written in Python.
This initial dsgrid data set, whose description was originally published in 2018, covers electricity demand in the contiguous United States (CONUS) for the historical year of 2012. It is a proof-of-concept demonstrating the feasibility of reconciling bottom-up demand modeling results with top-down information about electricity demand to create a more detailed description than is possible with either type of data source on its own. The result is demand data that is more highly resolved along geographic, temporal, sectoral, and end-use dimensions as may be helpful for conducting electricity sector-wide "what-if" analysis of, e.g., energy efficiency, electrification, and/or demand flexibility.
Although we conducted bottom-up versus top-down validation, the final residuals were significant, especially at higher geographic and temporal resolution. Please see the Executive Summary and/or Section 3 of the report to obtain an understanding of the data set limitations before deciding whether these data are suitable for any particular use case.
New dsgrid datasets are under development. Please visit https://www.nrel.gov/analysis/dsgrid.html for the latest information which is also linked in the data resources.},
url = {https://data.openei.org/submissions/4130},
year = {2018},
howpublished = {Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory, https://doi.org/10.25984/1823248},
note = {Accessed: 2025-04-24},
doi = {10.25984/1823248}
}
https://dx.doi.org/10.25984/1823248
Details
Data from Jul 8, 2018
Last updated Jan 2, 2024
Submitted Jul 21, 2021
Organization
National Renewable Energy Laboratory
Contact
Elaine T. Hale
303.384.7812
Authors
Research Areas
Keywords
energy, power, demand, Electrification Futures Study, dsgrid, historial year, modeled data, high-resolution, electricity demand, demand-side, demand side, model, analysis, processed data, electrification, demand flexibility, validation, grid, electrical, PyPl, python, contiguous United States, load, data, electricityDOE Project Details
Project Name Integrated Nuclear Renewable Energy Systems Analysis
Project Number FY17 AOP 2.4.0.3