An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system

Maximum power point tracking (MPPT) has become a central focus of recent industrial application advancements due to the high cost of the PV cell, low efficiency, and variable power production. Adaptive control techniques found widespread application in time-varying or nonlinear systems due to their...

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Main Authors: Md. Naiem-Ur-Rahman, Md. Mahmudul Hasan, Afsana Mimi Raka, Md. Fayzur Rahman, Md. Masud Rana, Ahmed Al Mansur, Md. Abdur Razzak
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Energy Conversion and Management: X
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590174525000340
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author Md. Naiem-Ur-Rahman
Md. Mahmudul Hasan
Afsana Mimi Raka
Md. Fayzur Rahman
Md. Masud Rana
Ahmed Al Mansur
Md. Abdur Razzak
author_facet Md. Naiem-Ur-Rahman
Md. Mahmudul Hasan
Afsana Mimi Raka
Md. Fayzur Rahman
Md. Masud Rana
Ahmed Al Mansur
Md. Abdur Razzak
author_sort Md. Naiem-Ur-Rahman
collection DOAJ
description Maximum power point tracking (MPPT) has become a central focus of recent industrial application advancements due to the high cost of the PV cell, low efficiency, and variable power production. Adaptive control techniques found widespread application in time-varying or nonlinear systems due to their capacity to respond to unexpected changes in inputs or system dynamics. This research presents an innovative approach to designing a self-tuned MPPT controller for a grid-connected photovoltaic (PV) system. Unlike other available controllers, the proposed fuzzy-based PSO controller uses PV array voltage and power as inputs. The controller generates the duty cycle for boost converters, removing the need for intermediate controllers like PID, ultimately simplifying system control and effectively managing environmental and PV system uncertainties. To validate the robustness of the controller, MATLAB/Simulink is utilized to compare the performance of the proposed controller with other conventional and advanced controllers based on extracted power, convergence time, and tracking efficiency. Moreover, this article presents a fuzzy-based self-tuned PSO-optimized MPPT controller for grid-connected PV systems, with performance validation through simulations and experiments under varying atmospheric conditions. The proposed controller demonstrates a remarkable average power tracking efficiency of around 99 %, significantly higher than conventional MPPT techniques. The system efficiently captures the maximum power point (MPP) within 0.06 s. In fixed conditions (1000 W/m2 and 25 ℃), the controller extracts a maximum power of 100.7 kWatt, while during partial shading, it consistently extracts up to an average of 98.08 % of the optimum power. Simulation results show that the system extracts 1070.71 W under uniform shading, and under non-uniform shading, it extracts 455.1 W. Experimental results align with the simulations, confirming the controller’s performance. In cases of variable irradiation, the controller successfully tracks power outputs of 99.96 % efficiency at 708 W/m2 and 34.9 ℃, and 99.69 % efficiency at 567 W/m2 and 43.2 ℃. The experimental setup validates the simulation outcomes, showcasing the adaptability and robustness of the controller.
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publisher Elsevier
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spelling doaj-art-eac9d16f345a46fdbdda7a2bdc7360b32025-08-20T01:51:03ZengElsevierEnergy Conversion and Management: X2590-17452025-04-012610090210.1016/j.ecmx.2025.100902An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic systemMd. Naiem-Ur-Rahman0Md. Mahmudul Hasan1Afsana Mimi Raka2Md. Fayzur Rahman3Md. Masud Rana4Ahmed Al Mansur5Md. Abdur Razzak6Department of Electrical and Electronic Engineering, Green University of Bangladesh, Purbachol American City, Kanchan, Rupganj, Narayanganj-1461, Dhaka, Bangladesh; Corresponding author.Department of Electrical & Electronic Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204, BangladeshDepartment of Electrical and Electronic Engineering, Green University of Bangladesh, Purbachol American City, Kanchan, Rupganj, Narayanganj-1461, Dhaka, BangladeshDepartment of Electrical and Electronic Engineering, Green University of Bangladesh, Purbachol American City, Kanchan, Rupganj, Narayanganj-1461, Dhaka, BangladeshDepartment of Electrical & Electronic Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204, BangladeshDepartment of Electrical and Electronic Engineering, Green University of Bangladesh, Purbachol American City, Kanchan, Rupganj, Narayanganj-1461, Dhaka, BangladeshDepartment of Electrical and Electronic Engineering, Independent University, Plot 16, Block B, Aftabuddin Ahmed Road Bashundhara Residential Area, Dhaka 1245, BangladeshMaximum power point tracking (MPPT) has become a central focus of recent industrial application advancements due to the high cost of the PV cell, low efficiency, and variable power production. Adaptive control techniques found widespread application in time-varying or nonlinear systems due to their capacity to respond to unexpected changes in inputs or system dynamics. This research presents an innovative approach to designing a self-tuned MPPT controller for a grid-connected photovoltaic (PV) system. Unlike other available controllers, the proposed fuzzy-based PSO controller uses PV array voltage and power as inputs. The controller generates the duty cycle for boost converters, removing the need for intermediate controllers like PID, ultimately simplifying system control and effectively managing environmental and PV system uncertainties. To validate the robustness of the controller, MATLAB/Simulink is utilized to compare the performance of the proposed controller with other conventional and advanced controllers based on extracted power, convergence time, and tracking efficiency. Moreover, this article presents a fuzzy-based self-tuned PSO-optimized MPPT controller for grid-connected PV systems, with performance validation through simulations and experiments under varying atmospheric conditions. The proposed controller demonstrates a remarkable average power tracking efficiency of around 99 %, significantly higher than conventional MPPT techniques. The system efficiently captures the maximum power point (MPP) within 0.06 s. In fixed conditions (1000 W/m2 and 25 ℃), the controller extracts a maximum power of 100.7 kWatt, while during partial shading, it consistently extracts up to an average of 98.08 % of the optimum power. Simulation results show that the system extracts 1070.71 W under uniform shading, and under non-uniform shading, it extracts 455.1 W. Experimental results align with the simulations, confirming the controller’s performance. In cases of variable irradiation, the controller successfully tracks power outputs of 99.96 % efficiency at 708 W/m2 and 34.9 ℃, and 99.69 % efficiency at 567 W/m2 and 43.2 ℃. The experimental setup validates the simulation outcomes, showcasing the adaptability and robustness of the controller.http://www.sciencedirect.com/science/article/pii/S2590174525000340Fuzzy logicMaximum power point trackingMembership functionParticle swarm optimizationPV arraySolar energy
spellingShingle Md. Naiem-Ur-Rahman
Md. Mahmudul Hasan
Afsana Mimi Raka
Md. Fayzur Rahman
Md. Masud Rana
Ahmed Al Mansur
Md. Abdur Razzak
An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system
Energy Conversion and Management: X
Fuzzy logic
Maximum power point tracking
Membership function
Particle swarm optimization
PV array
Solar energy
title An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system
title_full An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system
title_fullStr An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system
title_full_unstemmed An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system
title_short An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system
title_sort asymmetric fuzzy based self tuned pso optimized mppt controller for grid connected solar photovoltaic system
topic Fuzzy logic
Maximum power point tracking
Membership function
Particle swarm optimization
PV array
Solar energy
url http://www.sciencedirect.com/science/article/pii/S2590174525000340
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