LAPSE:2023.6287
Published Article
LAPSE:2023.6287
A Fuzzy Logic Control for Maximum Power Point Tracking Algorithm Validated in a Commercial PV System
February 23, 2023
Photovoltaic (PV) panels are devices capable of transforming solar energy into electricity without emissions. They are still a trending technology in the market not only because of the renewable features but also due to the avoidance of movable parts, which makes them an option with low maintenance. If the output voltage is insufficient or needs to be regulated, a boost converter is commonly connected to a PV panel. In this article, a commercial PV with a boost converter is controlled through a dSPACE platform for a maximum power point tracking (MPPT) task. Due to previous related experience, a fuzzy logic technique is designed and tested in real-time. The results are compared with an incremental conductance (IncCond) algorithm because it is a feasible and reliable tool for MPPT purposes. The outcomes show enhancement (in comparison with IncCond) in the steady-state oscillation, response time and overshoot values, which are 73.2%, 81.5% and 52.9%, respectively.
Keywords
fuzzy logic, fuzzy set, incremental conductance, maximum power point tracking, photovoltaic, power converters control
Suggested Citation
Derbeli M, Napole C, Barambones O. A Fuzzy Logic Control for Maximum Power Point Tracking Algorithm Validated in a Commercial PV System. (2023). LAPSE:2023.6287
Author Affiliations
Derbeli M: System Engineering and Automation Deparment, Faculty of Engineering of Vitoria-Gasteiz, Basque Country University (UPV/EHU), 01006 Vitoria-Gasteiz, Spain [ORCID]
Napole C: System Engineering and Automation Deparment, Faculty of Engineering of Vitoria-Gasteiz, Basque Country University (UPV/EHU), 01006 Vitoria-Gasteiz, Spain [ORCID]
Barambones O: System Engineering and Automation Deparment, Faculty of Engineering of Vitoria-Gasteiz, Basque Country University (UPV/EHU), 01006 Vitoria-Gasteiz, Spain [ORCID]
Journal Name
Energies
Volume
16
Issue
2
First Page
748
Year
2023
Publication Date
2023-01-09
Published Version
ISSN
1996-1073
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Original Submission
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PII: en16020748, Publication Type: Journal Article
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LAPSE:2023.6287
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doi:10.3390/en16020748
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Feb 23, 2023
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