Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic system
Introduction. Photovoltaic (PV) systems play a crucial role in converting solar energy into electricity, but their efficiency is highly influenced by environmental factors such as irradiance and temperature. To optimize power output, Maximum Power Point Tracking (MPPT) techniques are used. This pape...
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National Technical University "Kharkiv Polytechnic Institute"
2025-01-01
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| Series: | Electrical engineering & Electromechanics |
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| Online Access: | http://eie.khpi.edu.ua/article/view/311414/308416 |
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| author | A. Boudia S. Messalti S. Zeghlache A. Harrag |
| author_facet | A. Boudia S. Messalti S. Zeghlache A. Harrag |
| author_sort | A. Boudia |
| collection | DOAJ |
| description | Introduction. Photovoltaic (PV) systems play a crucial role in converting solar energy into electricity, but their efficiency is highly influenced by environmental factors such as irradiance and temperature. To optimize power output, Maximum Power Point Tracking (MPPT) techniques are used. This paper introduces a novel approach utilizing a Type-2 Fuzzy Logic Controller (T2FLC) for MPPT in PV systems. The novelty of the proposed work lies in the development of a T2FLC that offers enhanced adaptability by managing a higher degree of uncertainty, we introduce an original method that calculates the error between the output voltage and a dynamically derived reference voltage, which is obtained using a mathematical equation. This reference voltage adjusts in real-time based on changes in environmental conditions, allowing for more precise and stable MPPT performance. The purpose of this paper is to design and validate the effectiveness of a T2FLC-based MPPT technique for PV systems. This approach seeks to enhance power extraction efficiency in response to dynamic environmental factors such as changing irradiance and temperature. The methods used in this study involve the implementation of T2FLC to adjust the duty cycle of a DC-DC converter for continuous and precise MPPT. The system was simulated under various environmental conditions, comparing the performance of T2FLC against T1FLC. The results show that the T2FLC MPPT system significantly outperforms traditional methods in terms of tracking speed, stability, and power efficiency. T2FLC demonstrated faster convergence to the MPP, reduced oscillations, and higher accuracy in rapidly changing environmental conditions. The findings of this study confirm the practical value of T2FLC logic in improving the efficiency and stability of PV systems, making it a promising solution for enhancing renewable energy technologies. References 33, tables 4, figures 10.
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| format | Article |
| id | doaj-art-e5343aee9eee4957a2d0d8dc8ea8e289 |
| institution | Kabale University |
| issn | 2074-272X 2309-3404 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | National Technical University "Kharkiv Polytechnic Institute" |
| record_format | Article |
| series | Electrical engineering & Electromechanics |
| spelling | doaj-art-e5343aee9eee4957a2d0d8dc8ea8e2892025-01-02T18:41:43ZengNational Technical University "Kharkiv Polytechnic Institute"Electrical engineering & Electromechanics2074-272X2309-34042025-01-0120251162210.20998/2074-272X.2025.1.03Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic systemA. Boudia0https://orcid.org/0000-0001-8273-9973S. Messalti1https://orcid.org/0000-0001-5214-4434S. Zeghlache2https://orcid.org/0000-0002-3041-9473A. Harrag3https://orcid.org/0000-0002-4107-8926University of M’sila, AlgeriaUniversity of M’sila, AlgeriaUniversity of M’sila, AlgeriaFerhat Abbas University Setif 1, AlgeriaIntroduction. Photovoltaic (PV) systems play a crucial role in converting solar energy into electricity, but their efficiency is highly influenced by environmental factors such as irradiance and temperature. To optimize power output, Maximum Power Point Tracking (MPPT) techniques are used. This paper introduces a novel approach utilizing a Type-2 Fuzzy Logic Controller (T2FLC) for MPPT in PV systems. The novelty of the proposed work lies in the development of a T2FLC that offers enhanced adaptability by managing a higher degree of uncertainty, we introduce an original method that calculates the error between the output voltage and a dynamically derived reference voltage, which is obtained using a mathematical equation. This reference voltage adjusts in real-time based on changes in environmental conditions, allowing for more precise and stable MPPT performance. The purpose of this paper is to design and validate the effectiveness of a T2FLC-based MPPT technique for PV systems. This approach seeks to enhance power extraction efficiency in response to dynamic environmental factors such as changing irradiance and temperature. The methods used in this study involve the implementation of T2FLC to adjust the duty cycle of a DC-DC converter for continuous and precise MPPT. The system was simulated under various environmental conditions, comparing the performance of T2FLC against T1FLC. The results show that the T2FLC MPPT system significantly outperforms traditional methods in terms of tracking speed, stability, and power efficiency. T2FLC demonstrated faster convergence to the MPP, reduced oscillations, and higher accuracy in rapidly changing environmental conditions. The findings of this study confirm the practical value of T2FLC logic in improving the efficiency and stability of PV systems, making it a promising solution for enhancing renewable energy technologies. References 33, tables 4, figures 10. http://eie.khpi.edu.ua/article/view/311414/308416fuzzy logic controllerdc-dc boost convertermaximum power point trackingphotovoltaic system |
| spellingShingle | A. Boudia S. Messalti S. Zeghlache A. Harrag Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic system Electrical engineering & Electromechanics fuzzy logic controller dc-dc boost converter maximum power point tracking photovoltaic system |
| title | Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic system |
| title_full | Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic system |
| title_fullStr | Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic system |
| title_full_unstemmed | Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic system |
| title_short | Type-2 fuzzy logic controller-based maximum power point tracking for photovoltaic system |
| title_sort | type 2 fuzzy logic controller based maximum power point tracking for photovoltaic system |
| topic | fuzzy logic controller dc-dc boost converter maximum power point tracking photovoltaic system |
| url | http://eie.khpi.edu.ua/article/view/311414/308416 |
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