SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS
The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the datasets.
This dataset contains synthetic detailed electrical distribution network models, and connected timeseries loads for the greater San Francisco (SFO), Greensboro, and Austin areas. It is intended to provide researchers with very realistic and complete models that can be used for extensive powerflow simulations under a variety of scenarios. The data is synthetic, but has been validated against thousands of utility feeders to ensure statistical and operational similarity to electrical distribution networks in the US.
The OpenDSS data is partitioned into several regions (each zipped separately). After unzipping these files, each region has a folder for each substation, and subsequent folders for each feeder within the substation. This allows users to simulate smaller sections of the full dataset. Each of these folders (region, substation and feeder) has a folder titled "analysis" which contains CSV files listing voltages and overloads throughout the network for the peak loading time in the year. It also contains .png files showing the loading of residential and commercial loads on the network for every day of the year, and daily breakdowns of loads for commercial building categories. Time series data is provided in the "profiles" folder including real and reactive power at 15 minute resolution along with parquet files in the "endues" folder with breakdowns of building end-uses.
Citation Formats
TY - DATA
AB - The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the datasets.
This dataset contains synthetic detailed electrical distribution network models, and connected timeseries loads for the greater San Francisco (SFO), Greensboro, and Austin areas. It is intended to provide researchers with very realistic and complete models that can be used for extensive powerflow simulations under a variety of scenarios. The data is synthetic, but has been validated against thousands of utility feeders to ensure statistical and operational similarity to electrical distribution networks in the US.
The OpenDSS data is partitioned into several regions (each zipped separately). After unzipping these files, each region has a folder for each substation, and subsequent folders for each feeder within the substation. This allows users to simulate smaller sections of the full dataset. Each of these folders (region, substation and feeder) has a folder titled "analysis" which contains CSV files listing voltages and overloads throughout the network for the peak loading time in the year. It also contains .png files showing the loading of residential and commercial loads on the network for every day of the year, and daily breakdowns of loads for commercial building categories. Time series data is provided in the "profiles" folder including real and reactive power at 15 minute resolution along with parquet files in the "endues" folder with breakdowns of building end-uses.
AU - Palmintier, Bryan
A2 - Mateo Domingo, Carlos
A3 - Postigo Marcos, Fernando Emilio
A4 - Gomez San Roman, Tomas
A5 - de Cuadra, Fernando
A6 - Gensollen, Nicolas
A7 - Elgindy, Tarek
A8 - Duenas, Pablo
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO -
KW - energy
KW - power
KW - distribution system
KW - big data
KW - load timeseries
KW - synthetic
KW - electrical network
KW - energy systems integration
KW - grid modernization
KW - solar power
KW - solar
KW - grid
KW - SMART-DS
KW - OpenDSS
KW - powerflow
KW - distribution
KW - parquet
KW - SFO
KW - GSO
KW - AUS
KW - electrical
KW - realistic
KW - scenario
KW - system
KW - testing
LA - English
DA - 2020/12/18
PY - 2020
PB - National Renewable Energy Laboratory (NREL)
T1 - SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS
UR - https://data.openei.org/submissions/2981
ER -
Palmintier, Bryan, et al. SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS. National Renewable Energy Laboratory (NREL), 18 December, 2020, Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/2981.
Palmintier, B., Mateo Domingo, C., Postigo Marcos, F., Gomez San Roman, T., de Cuadra, F., Gensollen, N., Elgindy, T., & Duenas, P. (2020). SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS. [Data set]. Open Energy Data Initiative (OEDI). National Renewable Energy Laboratory (NREL). https://data.openei.org/submissions/2981
Palmintier, Bryan, Carlos Mateo Domingo, Fernando Emilio Postigo Marcos, Tomas Gomez San Roman, Fernando de Cuadra, Nicolas Gensollen, Tarek Elgindy, and Pablo Duenas. SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS. National Renewable Energy Laboratory (NREL), December, 18, 2020. Distributed by Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/2981
@misc{OEDI_Dataset_2981,
title = {SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS},
author = {Palmintier, Bryan and Mateo Domingo, Carlos and Postigo Marcos, Fernando Emilio and Gomez San Roman, Tomas and de Cuadra, Fernando and Gensollen, Nicolas and Elgindy, Tarek and Duenas, Pablo},
abstractNote = {The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the datasets.
This dataset contains synthetic detailed electrical distribution network models, and connected timeseries loads for the greater San Francisco (SFO), Greensboro, and Austin areas. It is intended to provide researchers with very realistic and complete models that can be used for extensive powerflow simulations under a variety of scenarios. The data is synthetic, but has been validated against thousands of utility feeders to ensure statistical and operational similarity to electrical distribution networks in the US.
The OpenDSS data is partitioned into several regions (each zipped separately). After unzipping these files, each region has a folder for each substation, and subsequent folders for each feeder within the substation. This allows users to simulate smaller sections of the full dataset. Each of these folders (region, substation and feeder) has a folder titled "analysis" which contains CSV files listing voltages and overloads throughout the network for the peak loading time in the year. It also contains .png files showing the loading of residential and commercial loads on the network for every day of the year, and daily breakdowns of loads for commercial building categories. Time series data is provided in the "profiles" folder including real and reactive power at 15 minute resolution along with parquet files in the "endues" folder with breakdowns of building end-uses. },
url = {https://data.openei.org/submissions/2981},
year = {2020},
howpublished = {Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory (NREL), https://data.openei.org/submissions/2981},
note = {Accessed: 2025-05-08}
}
Details
Data from Dec 18, 2020
Last updated Jan 2, 2024
Submitted Apr 12, 2023
Organization
National Renewable Energy Laboratory (NREL)
Contact
Tarek Elgindy
Authors
Research Areas
Keywords
energy, power, distribution system, big data, load timeseries, synthetic, electrical network, energy systems integration, grid modernization, solar power, solar, grid, SMART-DS, OpenDSS, powerflow, distribution, parquet, SFO, GSO, AUS, electrical, realistic, scenario, system, testingDOE Project Details
Project Name SMART-DS
Project Number CJ0000703