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Hybrid fuzzy logic approach for enhanced MPPT control in PV systems

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

2025Scientific Reports27 citationsDOIOpen Access PDF

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.

Topics & Concepts

Maximum power point trackingPhotovoltaic systemComputer scienceControl theory (sociology)Maximum power principleConvergence (economics)Fuzzy logicMATLABHybrid systemBoost converterPower (physics)Control (management)Artificial intelligenceEngineeringMachine learningInverterEconomic growthPhysicsElectrical engineeringQuantum mechanicsOperating systemEconomicsPhotovoltaic System Optimization Techniquessolar cell performance optimizationSolar Radiation and Photovoltaics
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