Hybrid ML Algorithm for Fault Classification in Transmission Lines Using Multi-Target Ensemble Classifier with Limited Data
Fault detection and classification in transmission lines are critical for maintaining the reliability and stability of electrical power systems. Quick and accurate fault detection allows for timely intervention, minimizing equipment damage, and reducing downtime. This study addresses the challenge o...
Saved in:
Main Author: | Abdallah El Ghaly |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Eng |
Subjects: | |
Online Access: | https://www.mdpi.com/2673-4117/6/1/4 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Robust fault detection and classification in power transmission lines via ensemble machine learning models
by: Tahir Anwar, et al.
Published: (2025-01-01) -
Detection and classification of single-circuit and intra-circuit faults based on analysis of current signals of near-end terminal in double-circuit transmission lines
by: Mahyar Abasi, et al.
Published: (2025-03-01) -
Graph Theory-Based Fault Location Method for Transmission Systems With Renewable Energy Sources
by: Victor Gonzalez, et al.
Published: (2024-01-01) -
Transmission line trip faults under extreme snow and ice conditions: a case study
by: Guojun Zhang
Published: (2025-01-01) -
Non-unit protection scheme for flexible DC transmission lines based on fitting the rate of change of line-mode voltage reverse traveling waves
by: Qixuan Zhang, et al.
Published: (2025-03-01)