Hybrid fuzzy logic approach for enhanced MPPT control in PV systems

This paper provides an in-depth analysis of photovoltaic (PV) system control within the MATLAB/Simulink environment, focusing on optimizing Maximum Power Point Tracking (MPPT) algorithms for enhanced efficiency under dynamic conditions. While conventional algorithms are widely used, their performance is limited under fluctuating conditions. To address this, we propose a novel hybrid approach combining Incremental Conductance with Fuzzy Logic Control (FLC), utilizing two innovative input variables: the sum of Conductance and Incremental Conductance (SInC) and its rate of change (CSI). The performance of the proposed algorithm, in comparison to other hybrid FLC methods, is evaluated through simulations using a boost converter under dynamic conditions, including abrupt irradiance changes and load variations. The results demonstrate that the proposed hybrid algorithm achieves superior performance, with an average MPPT efficiency of 97.7%, a convergence time of 53.5 ms, and an RMS of 97.8%, outperforming both conventional and other hybrid techniques. This work advances PV system control by providing a robust and adaptive solution for maximizing power extraction under diverse operating conditions.

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Publication Details

Journal
Scientific Reports
Published
2025-06-02
DOI
https://doi.org/10.1038/s41598-025-03154-w
Citations
20
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
7.27
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article

Hybrid fuzzy logic approach for enhanced MPPT control in PV systems

Kamal Hirech, Mohamed Oukili, Mishari Metab Almalki, Thamer A. H. Alghamdi et al.
20 citations
Scientific Reports
Photovoltaic System Optimization Techniques
7.27
article

Hybrid fuzzy logic approach for enhanced MPPT control in PV systems

Kamal Hirech, Mohamed Oukili, Mishari Metab Almalki, Thamer A. H. Alghamdi, Mohammed Rhiat, Badre Bossoufi, Ilias Atmane, Mustapha Melhaoui, Mohammed Alenezi
article en
20 citations

Abstract

This paper provides an in-depth analysis of photovoltaic (PV) system control within the MATLAB/Simulink environment, focusing on optimizing Maximum Power Point Tracking (MPPT) algorithms for enhanced efficiency under dynamic conditions. While conventional algorithms are widely used, their performance is limited under fluctuating conditions. To address this, we propose a novel hybrid approach combining Incremental Conductance with Fuzzy Logic Control (FLC), utilizing two innovative input variables: the sum of Conductance and Incremental Conductance (SInC) and its rate of change (CSI). The performance of the proposed algorithm, in comparison to other hybrid FLC methods, is evaluated through simulations using a boost converter under dynamic conditions, including abrupt irradiance changes and load variations. The results demonstrate that the proposed hybrid algorithm achieves superior performance, with an average MPPT efficiency of 97.7%, a convergence time of 53.5 ms, and an RMS of 97.8%, outperforming both conventional and other hybrid techniques. This work advances PV system control by providing a robust and adaptive solution for maximizing power extraction under diverse operating conditions.

Scientific ReportsVol. 15(1)
Cadi Ayyad University (MA), Mohamed I University (MA), Al Baha University (SA), Premier University (BD), Cardiff University (GB)
Affordable and clean energy
Openalex Percentile: Top 2%
Photovoltaic System Optimization Techniques
7.27
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Hybrid fuzzy logic approach for enhanced MPPT control in PV systems — Kamal Hirech, Mohamed Oukili, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS