Discrimination of high impedance fault in microgrid power network using semi-supervised machine learning algorithm

Discrimination of high impedance fault in microgrid power network using semi-supervised machine learning algorithm

This work proposes a semi-supervised classification approach for discriminating high-impedance (HI) faults and other transients in a photovoltaic (PV) interconnected microgrid (MG) network. The suggested classifier combines unsupervised K-means clustering with the supervised multi-layer perceptron n...

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Bibliographic Details
Main Authors: Arangarajan Vinayagam, S.T. Suganthi, C.B. Venkatramanan, Ayoob Alateeq, Abdullah Alassaf, Nur Fadilah Ab Aziz, Mohd Helmi Mansor, Saad Mekhilef
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Ain Shams Engineering Journal
Subjects:
Photovoltaic
High impedance fault
K-means clustering
Multi-layer perceptron
Microgrid
Energy
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447924005689
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