Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System

<p dir="ltr">Currently, providing water in developing countries, especially in dry and hot rural areas, is a significant challenge. However, creating new electric grids is often expensive. Therefore, the use of low-cost photovoltaic (PV) panels in water pumping systems, without chemi...

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Main Author: B. Rouabah (17947820) (author)
Other Authors: H. Toubakh (17947823) (author), M. Djemai (17947826) (author), L. Ben-Brahim (17947829) (author), Raymond Ghandour (17947832) (author)
Published: 2023
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_version_ 1864513527563157504
author B. Rouabah (17947820)
author2 H. Toubakh (17947823)
M. Djemai (17947826)
L. Ben-Brahim (17947829)
Raymond Ghandour (17947832)
author2_role author
author
author
author
author_facet B. Rouabah (17947820)
H. Toubakh (17947823)
M. Djemai (17947826)
L. Ben-Brahim (17947829)
Raymond Ghandour (17947832)
author_role author
dc.creator.none.fl_str_mv B. Rouabah (17947820)
H. Toubakh (17947823)
M. Djemai (17947826)
L. Ben-Brahim (17947829)
Raymond Ghandour (17947832)
dc.date.none.fl_str_mv 2023-04-12T03:00:00Z
dc.identifier.none.fl_str_mv 10.1109/access.2023.3266522
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Fault_Diagnosis_Based_Machine_Learning_and_Fault_Tolerant_Control_of_Multicellular_Converter_Used_in_Photovoltaic_Water_Pumping_System/25204223
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Electrical engineering
Electronics, sensors and digital hardware
Materials engineering
Photovoltaic systems
Capacitors
DC motors
Topology
Mathematical models
Torque
Maximum power point trackers
Photovoltaic water pumping system
multicellular converter
fault diagnosis based machine learning
fault tolerant control (FTC)
dc.title.none.fl_str_mv Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">Currently, providing water in developing countries, especially in dry and hot rural areas, is a significant challenge. However, creating new electric grids is often expensive. Therefore, the use of low-cost photovoltaic (PV) panels in water pumping systems, without chemical energy storage, based on high-performance and more efficient power converters with increased time life and lower maintenance interventions is needed. In this study, a photovoltaic water pumping system with two power converters, the first is used to extract the maximum power using the maximum power point tracking (MPPT) algorithm, and the second is a three-cell multicellular power converter used to control the DC motor with a submerged pump. Meanwhile, the serial connection and redundant topology of multicellular converters render the system more vulnerable to failure. fault diagnosis-based machine learning approach and fault tolerant control (FTC) are proposed for multicellular power converters. Simulation results with MATLAB show the effectiveness and practicability of the proposed structure and control to isolate the faulty capacitor, increase the sustainability of the system, assure the supply of water under faulty conditions, minimize the mechanical vibrations in electric DC motors, and avoid PV system shutdown.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2023.3266522" target="_blank">https://dx.doi.org/10.1109/access.2023.3266522</a></p>
eu_rights_str_mv openAccess
id Manara2_cb2f14c4faedc23c46fd09e76aa9fc60
identifier_str_mv 10.1109/access.2023.3266522
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/25204223
publishDate 2023
repository.mail.fl_str_mv
repository.name.fl_str_mv
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rights_invalid_str_mv CC BY 4.0
spelling Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping SystemB. Rouabah (17947820)H. Toubakh (17947823)M. Djemai (17947826)L. Ben-Brahim (17947829)Raymond Ghandour (17947832)EngineeringElectrical engineeringElectronics, sensors and digital hardwareMaterials engineeringPhotovoltaic systemsCapacitorsDC motorsTopologyMathematical modelsTorqueMaximum power point trackersPhotovoltaic water pumping systemmulticellular converterfault diagnosis based machine learningfault tolerant control (FTC)<p dir="ltr">Currently, providing water in developing countries, especially in dry and hot rural areas, is a significant challenge. However, creating new electric grids is often expensive. Therefore, the use of low-cost photovoltaic (PV) panels in water pumping systems, without chemical energy storage, based on high-performance and more efficient power converters with increased time life and lower maintenance interventions is needed. In this study, a photovoltaic water pumping system with two power converters, the first is used to extract the maximum power using the maximum power point tracking (MPPT) algorithm, and the second is a three-cell multicellular power converter used to control the DC motor with a submerged pump. Meanwhile, the serial connection and redundant topology of multicellular converters render the system more vulnerable to failure. fault diagnosis-based machine learning approach and fault tolerant control (FTC) are proposed for multicellular power converters. Simulation results with MATLAB show the effectiveness and practicability of the proposed structure and control to isolate the faulty capacitor, increase the sustainability of the system, assure the supply of water under faulty conditions, minimize the mechanical vibrations in electric DC motors, and avoid PV system shutdown.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2023.3266522" target="_blank">https://dx.doi.org/10.1109/access.2023.3266522</a></p>2023-04-12T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2023.3266522https://figshare.com/articles/journal_contribution/Fault_Diagnosis_Based_Machine_Learning_and_Fault_Tolerant_Control_of_Multicellular_Converter_Used_in_Photovoltaic_Water_Pumping_System/25204223CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/252042232023-04-12T03:00:00Z
spellingShingle Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
B. Rouabah (17947820)
Engineering
Electrical engineering
Electronics, sensors and digital hardware
Materials engineering
Photovoltaic systems
Capacitors
DC motors
Topology
Mathematical models
Torque
Maximum power point trackers
Photovoltaic water pumping system
multicellular converter
fault diagnosis based machine learning
fault tolerant control (FTC)
status_str publishedVersion
title Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
title_full Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
title_fullStr Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
title_full_unstemmed Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
title_short Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
title_sort Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
topic Engineering
Electrical engineering
Electronics, sensors and digital hardware
Materials engineering
Photovoltaic systems
Capacitors
DC motors
Topology
Mathematical models
Torque
Maximum power point trackers
Photovoltaic water pumping system
multicellular converter
fault diagnosis based machine learning
fault tolerant control (FTC)