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Distribution System Dataset Generator for AI Applications [SWR-24-75]

RESOURCE

Publicly Accessible Repository
https://github.com/NREL-Distribution-Suites/gridai
https://doi.org/10.11578/dc.20241119.1
Documentation
https://nrel-distribution-suites.github.io/gridai

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Abstract

This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.
Developers:
Duwadi, Kapil [1] ;  Latif, Aadil [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Release Date:
2024-09-03
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Version:
1.0.0
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
147712
Site Accession Number:
NREL SWR-24-75
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/NREL-Distribution-Suites/gridai
https://doi.org/10.11578/dc.20241119.1
Documentation
https://nrel-distribution-suites.github.io/gridai

SAVE / SHARE



NREL Badge

Citation Formats

Duwadi, Kapil, and Latif, Aadil. Distribution System Dataset Generator for AI Applications [SWR-24-75]. Computer Software. https://github.com/NREL-Distribution-Suites/gridai. USDOE Laboratory Directed Research and Development (LDRD) Program. 03 Sep. 2024. Web. doi:10.11578/dc.20241119.1.
Duwadi, Kapil, & Latif, Aadil. (2024, September 03). Distribution System Dataset Generator for AI Applications [SWR-24-75]. [Computer software]. https://github.com/NREL-Distribution-Suites/gridai. https://doi.org/10.11578/dc.20241119.1.
Duwadi, Kapil, and Latif, Aadil. "Distribution System Dataset Generator for AI Applications [SWR-24-75]." Computer software. September 03, 2024. https://github.com/NREL-Distribution-Suites/gridai. https://doi.org/10.11578/dc.20241119.1.
@misc{ doecode_147712,
title = {Distribution System Dataset Generator for AI Applications [SWR-24-75]},
author = {Duwadi, Kapil and Latif, Aadil},
abstractNote = {This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.},
doi = {10.11578/dc.20241119.1},
url = {https://doi.org/10.11578/dc.20241119.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20241119.1}},
year = {2024},
month = {sep}
}