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A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]

RESOURCE

Publicly Accessible Repository
https://github.com/openEDI/oedisi-hif-identification
https://doi.org/10.11578/dc.20240426.2
Documentation
https://www.semanticscholar.org/paper/A-Data-Driven-Approach-for-High-Impedance-Fault-in-Zhou-Dong/c5428e751d1c82c2e8694096ef06c81e4e56eb7e

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Abstract

This software provides a data-driven approach for efficiently identifying high impedance faults (HIFs) in distribution systems. To tackle the nonlinearity of the voltage current trajectory of HIFs, we first formulate linear least squares problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations.
Developers:
Zhou, Yuqi [1] ;  Yang, Rui [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Release Date:
2024-04-23
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
126377
Site Accession Number:
NREL SWR-24-13
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/openEDI/oedisi-hif-identification
https://doi.org/10.11578/dc.20240426.2
Documentation
https://www.semanticscholar.org/paper/A-Data-Driven-Approach-for-High-Impedance-Fault-in-Zhou-Dong/c5428e751d1c82c2e8694096ef06c81e4e56eb7e

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Citation Formats

Zhou, Yuqi, and Yang, Rui. A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]. Computer Software. https://github.com/openEDI/oedisi-hif-identification. USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office. 23 Apr. 2024. Web. doi:10.11578/dc.20240426.2.
Zhou, Yuqi, & Yang, Rui. (2024, April 23). A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]. [Computer software]. https://github.com/openEDI/oedisi-hif-identification. https://doi.org/10.11578/dc.20240426.2.
Zhou, Yuqi, and Yang, Rui. "A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]." Computer software. April 23, 2024. https://github.com/openEDI/oedisi-hif-identification. https://doi.org/10.11578/dc.20240426.2.
@misc{ doecode_126377,
title = {A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]},
author = {Zhou, Yuqi and Yang, Rui},
abstractNote = {This software provides a data-driven approach for efficiently identifying high impedance faults (HIFs) in distribution systems. To tackle the nonlinearity of the voltage current trajectory of HIFs, we first formulate linear least squares problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations.},
doi = {10.11578/dc.20240426.2},
url = {https://doi.org/10.11578/dc.20240426.2},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240426.2}},
year = {2024},
month = {apr}
}