Fault Diagnosis Based on Machine Learning for the High Frequency Link of a Grid-Tied Photovoltaic Converter for a Wide Range of Irradiance Conditions

Fault Diagnosis Based on Machine Learning for the High Frequency Link of a Grid-Tied Photovoltaic Converter for a Wide Range of Irradiance Conditions

The objective of this work is to select a Machine Learning Technique (MLT) to develop a fault diagnosis scheme for the power switching devices of the High Frequency link (HF link) in a grid-tied Photovoltaic (PV) system, without increasing the total number of sensors, and being capable to operate on...

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Bibliographic Details
Main Authors: Yuniel Leon-Ruiz, Mario Gonzalez-Garcia, Ricardo Alvarez-Salas, Juan Cuevas-Tello, Victor Cardenas
Format: article
Language:EN
Published: IEEE 2021
Subjects:
Fault diagnosis
high frequency link
machine learning
photovoltaic systems
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Online Access:https://doaj.org/article/92bcd048bbb1438eb82ee41b2c6b3d6a
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https://doaj.org/article/92bcd048bbb1438eb82ee41b2c6b3d6a

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