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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

National Renewable Energy Laboratory. (2018). Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS) [data set]. Retrieved from https://dx.doi.org/10.25984/1823248.
Export Citation to RIS
Hale, Elaine, Horsey, Henry, Johnson, Brandon, Muratori, Matteo, Wilson, Eric, Borlaug, Brennan, Christensen, Craig, Farthing, Amanda, Hettinger, Dylan, Parker, Andrew, Robertson, Joseph, Rossol, Michael, Stephen, Gord, Wood, Eric, and Vairamohan, Baskar. Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS). United States: N.p., 08 Jul, 2018. Web. doi: 10.25984/1823248.
Hale, Elaine, Horsey, Henry, Johnson, Brandon, Muratori, Matteo, Wilson, Eric, Borlaug, Brennan, Christensen, Craig, Farthing, Amanda, Hettinger, Dylan, Parker, Andrew, Robertson, Joseph, Rossol, Michael, Stephen, Gord, Wood, Eric, & Vairamohan, Baskar. Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS). United States. https://dx.doi.org/10.25984/1823248
Hale, Elaine, Horsey, Henry, Johnson, Brandon, Muratori, Matteo, Wilson, Eric, Borlaug, Brennan, Christensen, Craig, Farthing, Amanda, Hettinger, Dylan, Parker, Andrew, Robertson, Joseph, Rossol, Michael, Stephen, Gord, Wood, Eric, and Vairamohan, Baskar. 2018. "Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)". United States. https://dx.doi.org/10.25984/1823248. https://data.openei.org/submissions/4130.
@div{oedi_4130, title = {Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)}, author = {Hale, Elaine, Horsey, Henry, Johnson, Brandon, Muratori, Matteo, Wilson, Eric, Borlaug, Brennan, Christensen, Craig, Farthing, Amanda, Hettinger, Dylan, Parker, Andrew, Robertson, Joseph, Rossol, Michael, Stephen, Gord, 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.}, doi = {10.25984/1823248}, url = {https://data.openei.org/submissions/4130}, journal = {}, number = , volume = , place = {United States}, year = {2018}, month = {07}}

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.}, doi = {10.25984/1823248}, url = {https://data.openei.org/submissions/4130}, journal = {}, number = , volume = , place = {United States}, year = {2018}, month = {07}}" readonly />
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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