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Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)

Publicly accessible License 

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 -
Export Citation to RIS
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

Elaine Hale

National Renewable Energy Laboratory

Henry Horsey

National Renewable Energy Laboratory

Brandon Johnson

Electric Power Research Institute

Matteo Muratori

National Renewable Energy Laboratory

Eric Wilson

tional Renewable Energy

Brennan Borlaug

National Renewable Energy Laboratory

Craig Christensen

National Renewable Energy Laboratory

Amanda Farthing

National Renewable Energy Laboratory

Dylan Hettinger

National Renewable Energy Laboratory

Andrew Parker

National Renewable Energy Laboratory

Joseph Robertson

National Renewable Energy Laboratory

Michael Rossol

National Renewable Energy Laboratory

Gord Stephen

National Renewable Energy Laboratory

Eric Wood

National Renewable Energy Laboratory

Baskar Vairamohan

Electric Power Research Institute

DOE Project Details

Project Name Integrated Nuclear Renewable Energy Systems Analysis

Project Number FY17 AOP 2.4.0.3

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