Graph-Variational Convolutional Autoencoder-Based Fault Detection and Diagnosis for Photovoltaic Arrays

Graph-Variational Convolutional Autoencoder-Based Fault Detection and Diagnosis for Photovoltaic Arrays

Solar energy is a critical renewable energy source, with solar arrays or photovoltaic systems widely used to convert solar energy into electrical energy. However, solar array systems can develop faults and may exhibit poor performance. Diagnosing and resolving faults within these systems promptly is...

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Bibliographic Details
Main Authors: Murshedul Arifeen, Andrei Petrovski, Md Junayed Hasan, Khandaker Noman, Wasib Ul Navid, Auwal Haruna
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Machines
Subjects:
solar array
photovoltaic array
fault detection
fault diagnosis
graph convolutional network
variational autoencoder
Online Access:https://www.mdpi.com/2075-1702/12/12/894
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