A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
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.
- Site Accession Number:
- NREL SWR-24-13
- Software Type:
- Scientific
- License(s):
- BSD 3-clause "New" or "Revised" License
- Programming Language(s):
- Python
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies OfficePrimary Award/Contract Number:AC36-08GO28308
- DOE Contract Number:
- AC36-08GO28308
- Code ID:
- 126377
- OSTI ID:
- code-126377
- Country of Origin:
- United States
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