Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources

Multilayer inverters (MLIs) play an important role in their efficiency and effec-tiveness. This study proposes a new MLI that is optimally adapted using DQZcontrol and a vague neurological approach for tracking the single maximumpower point of a hybrid renewable energy source. This MLI has a bidirec...

Full description

Saved in:
Bibliographic Details
Main Authors: Akharakit Chaithanakulwat, Teerawut Savangboon, Nuttee Thungsuk, Taweesak Tanaram, Papol Sardyong
Format: Article
Language:English
Published: Electronics and Telecommunications Research Institute (ETRI) 2025-08-01
Series:ETRI Journal
Subjects:
Online Access:https://doi.org/10.4218/etrij.2024-0170
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849224619200872448
author Akharakit Chaithanakulwat
Teerawut Savangboon
Nuttee Thungsuk
Taweesak Tanaram
Papol Sardyong
author_facet Akharakit Chaithanakulwat
Teerawut Savangboon
Nuttee Thungsuk
Taweesak Tanaram
Papol Sardyong
author_sort Akharakit Chaithanakulwat
collection DOAJ
description Multilayer inverters (MLIs) play an important role in their efficiency and effec-tiveness. This study proposes a new MLI that is optimally adapted using DQZcontrol and a vague neurological approach for tracking the single maximumpower point of a hybrid renewable energy source. This MLI has a bidirectionalfixed switch, the purpose of which is to reduce harmonics and increase thevoltage level. The maximum power point tracking (MPPT) method proposedhere is the only MPPT method that uses neuro-fuzzy control algorithms, mak-ing it superior to other methods. The proposed inverter consists of 12 powersemiconductor switches (IGBTs) connected to three DC power sources—thatis, photovoltaic, wind, and tidal energy power sources. The switching angle forpulse-width modulation can be calculated using the DQZ principle in the pro-posed MLI. Evaluation of the effectiveness of the proposed method usesMATLAB/Simulink simulations, the results being compared to those of theprototype mechanism. We also compare the performance of the MPPT algo-rithm and prototype mechanism, which is connected to a single-phase micro-grid. The proposed method achieves total harmonic distortion (THD)efficiency with a satisfactory performance increase.
format Article
id doaj-art-0ba6c4ea5fbf4ebc985babfc1fc7e2c6
institution Kabale University
issn 1225-6463
2233-7326
language English
publishDate 2025-08-01
publisher Electronics and Telecommunications Research Institute (ETRI)
record_format Article
series ETRI Journal
spelling doaj-art-0ba6c4ea5fbf4ebc985babfc1fc7e2c62025-08-25T07:00:07ZengElectronics and Telecommunications Research Institute (ETRI)ETRI Journal1225-64632233-73262025-08-0147465767110.4218/etrij.2024-0170Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sourcesAkharakit ChaithanakulwatTeerawut SavangboonNuttee ThungsukTaweesak TanaramPapol SardyongMultilayer inverters (MLIs) play an important role in their efficiency and effec-tiveness. This study proposes a new MLI that is optimally adapted using DQZcontrol and a vague neurological approach for tracking the single maximumpower point of a hybrid renewable energy source. This MLI has a bidirectionalfixed switch, the purpose of which is to reduce harmonics and increase thevoltage level. The maximum power point tracking (MPPT) method proposedhere is the only MPPT method that uses neuro-fuzzy control algorithms, mak-ing it superior to other methods. The proposed inverter consists of 12 powersemiconductor switches (IGBTs) connected to three DC power sources—thatis, photovoltaic, wind, and tidal energy power sources. The switching angle forpulse-width modulation can be calculated using the DQZ principle in the pro-posed MLI. Evaluation of the effectiveness of the proposed method usesMATLAB/Simulink simulations, the results being compared to those of theprototype mechanism. We also compare the performance of the MPPT algo-rithm and prototype mechanism, which is connected to a single-phase micro-grid. The proposed method achieves total harmonic distortion (THD)efficiency with a satisfactory performance increase.https://doi.org/10.4218/etrij.2024-0170dqz controlharmonic distortionhybrid renewablemaximum power point trackingmultilayer inverterneuro-fuzzy
spellingShingle Akharakit Chaithanakulwat
Teerawut Savangboon
Nuttee Thungsuk
Taweesak Tanaram
Papol Sardyong
Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources
ETRI Journal
dqz control
harmonic distortion
hybrid renewable
maximum power point tracking
multilayer inverter
neuro-fuzzy
title Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources
title_full Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources
title_fullStr Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources
title_full_unstemmed Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources
title_short Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources
title_sort multilayer inverter with dqz and neuro fuzzy control for single maximum power point tracking of hybrid renewable sources
topic dqz control
harmonic distortion
hybrid renewable
maximum power point tracking
multilayer inverter
neuro-fuzzy
url https://doi.org/10.4218/etrij.2024-0170
work_keys_str_mv AT akharakitchaithanakulwat multilayerinverterwithdqzandneurofuzzycontrolforsinglemaximumpowerpointtrackingofhybridrenewablesources
AT teerawutsavangboon multilayerinverterwithdqzandneurofuzzycontrolforsinglemaximumpowerpointtrackingofhybridrenewablesources
AT nutteethungsuk multilayerinverterwithdqzandneurofuzzycontrolforsinglemaximumpowerpointtrackingofhybridrenewablesources
AT taweesaktanaram multilayerinverterwithdqzandneurofuzzycontrolforsinglemaximumpowerpointtrackingofhybridrenewablesources
AT papolsardyong multilayerinverterwithdqzandneurofuzzycontrolforsinglemaximumpowerpointtrackingofhybridrenewablesources