Autonomous Monitoring of Line-to-Line Faults in Photovoltaic Systems by Feature Selection and Parameter Optimization of Support Vector Machine Using Genetic Algorithms

Autonomous Monitoring of Line-to-Line Faults in Photovoltaic Systems by Feature Selection and Parameter Optimization of Support Vector Machine Using Genetic Algorithms

Photovoltaic (PV) monitoring and fault detection are very crucial to enhance the service life and reliability of PV systems. It is difficult to detect and classify the faults at the Direct Current (DC) side of PV arrays by common protection devices, especially Line-to-Line (LL) faults, because such...

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Bibliographic Details
Main Authors: Aref Eskandari, Jafar Milimonfared, Mohammadreza Aghaei, Angèle H.M.E. Reinders
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Applied Sciences
Subjects:
photovoltaic (PV) system
autonomous monitoring
support vector machine (SVM)
genetic algorithm (GA)
line-to-line (LL) faults
feature selection
Online Access:https://www.mdpi.com/2076-3417/10/16/5527

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