Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations

Fossil fuels and other conventional energy sources used to generate electricity are finite. Therefore, alternative energy sources should be pursued to meet present and future energy demands. The photovoltaic (PV) is a promising renewable energy source, especially for the remote areas. The PV is a DC...

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Main Authors: Hannan, M.A., Ghani, Z.A., Hoque, M.M., Ker, P.J., Hussain, A., Mohamed, A.
Format: Article
Language:English
Published: 2020
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spelling my.uniten.dspace-133532020-08-17T06:10:40Z Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations Hannan, M.A. Ghani, Z.A. Hoque, M.M. Ker, P.J. Hussain, A. Mohamed, A. Fossil fuels and other conventional energy sources used to generate electricity are finite. Therefore, alternative energy sources should be pursued to meet present and future energy demands. The photovoltaic (PV) is a promising renewable energy source, especially for the remote areas. The PV is a DC power source that needs to be converted into usable AC power using an inverter. However, its nonlinearity and output fluctuation pose challenges in the design of PV based inverter. In this paper, a PV inverter controller system with the fundamentals of a fuzzy logic controller (FLC) and its applications and execution are reviewed. The different fuzzy controllers, inverter control algorithms, and switching techniques are studied. The findings indicate that the fuzzy logic controls have been gaining attention in the area of power control engineering, especially in inverter controller design for PV applications and generation. The FLC has a flexible and intelligent design, expedient user interface, easy computation and learning system, and combinations of different control algorithms. The FLC is also verifiable for completeness, redundancy, and consistency. However, finding the boundaries of membership functions and other rules of FLC requires manual tuning, long computation time, and considerable effort. This paper comprehensively reviews the FLC-based inverter control system to minimize PV output fluctuations, which cause inverter issues related to output harmonics, power factor, switching schemes, losses, and system implementation. The inverter system and its control strategy for future PV applications and generation require further research and development. Consequently, this review focuses on many factors and challenges and provides recommendations for designing capable and efficient inverter control systems for converting PV power to usable AC power. All the highlighted insights of this review will hopefully lead to increased efforts toward the development of the advanced inverter control systems for PV applications for AC loads and the utility grid. © 2013 IEEE. 2020-02-03T03:32:02Z 2020-02-03T03:32:02Z 2019-03 Article 10.1109/ACCESS.2019.2899610 en
institution Universiti Tenaga Nasional
building UNITEN Library
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country Malaysia
content_provider Universiti Tenaga Nasional
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language English
description Fossil fuels and other conventional energy sources used to generate electricity are finite. Therefore, alternative energy sources should be pursued to meet present and future energy demands. The photovoltaic (PV) is a promising renewable energy source, especially for the remote areas. The PV is a DC power source that needs to be converted into usable AC power using an inverter. However, its nonlinearity and output fluctuation pose challenges in the design of PV based inverter. In this paper, a PV inverter controller system with the fundamentals of a fuzzy logic controller (FLC) and its applications and execution are reviewed. The different fuzzy controllers, inverter control algorithms, and switching techniques are studied. The findings indicate that the fuzzy logic controls have been gaining attention in the area of power control engineering, especially in inverter controller design for PV applications and generation. The FLC has a flexible and intelligent design, expedient user interface, easy computation and learning system, and combinations of different control algorithms. The FLC is also verifiable for completeness, redundancy, and consistency. However, finding the boundaries of membership functions and other rules of FLC requires manual tuning, long computation time, and considerable effort. This paper comprehensively reviews the FLC-based inverter control system to minimize PV output fluctuations, which cause inverter issues related to output harmonics, power factor, switching schemes, losses, and system implementation. The inverter system and its control strategy for future PV applications and generation require further research and development. Consequently, this review focuses on many factors and challenges and provides recommendations for designing capable and efficient inverter control systems for converting PV power to usable AC power. All the highlighted insights of this review will hopefully lead to increased efforts toward the development of the advanced inverter control systems for PV applications for AC loads and the utility grid. © 2013 IEEE.
format Article
author Hannan, M.A.
Ghani, Z.A.
Hoque, M.M.
Ker, P.J.
Hussain, A.
Mohamed, A.
spellingShingle Hannan, M.A.
Ghani, Z.A.
Hoque, M.M.
Ker, P.J.
Hussain, A.
Mohamed, A.
Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations
author_facet Hannan, M.A.
Ghani, Z.A.
Hoque, M.M.
Ker, P.J.
Hussain, A.
Mohamed, A.
author_sort Hannan, M.A.
title Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations
title_short Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations
title_full Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations
title_fullStr Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations
title_full_unstemmed Fuzzy logic inverter controller in photovoltaic applications: Issues and recommendations
title_sort fuzzy logic inverter controller in photovoltaic applications: issues and recommendations
publishDate 2020
_version_ 1678595901175627776
score 13.222552