Integrating fault detection and classification in microgrids using supervised machine learning considering fault resistance uncertainty

Integrating fault detection and classification in microgrids using supervised machine learning considering fault resistance uncertainty

Abstract Microgrids (MGs) can enhance the consumers’ reliability. Nevertheless, besides significant outcomes, some challenges arise. Regarding the intermittent nature of Renewable Energy Resources (RESs), MGs are not operated radially. Accordingly, the reliable protection of MGs considering uncertai...

Full description

Saved in:
Bibliographic Details
Main Authors: Morteza Barkhi, Javad Pourhossein, Seyed Ali Hosseini
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Adaptive protection
Grid-connected mode
Islanded mode
Data analysis
Uncertainty modeling
Online Access:https://doi.org/10.1038/s41598-024-77982-7
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-024-77982-7

Similar Items