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Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system

Photovoltaic systems (PV) are becoming more popular as a way to make electricity because they offer so many benefits, such as free solar irradiation to harvest and low maintenance costs. Moreover, the system is environmentally friendly because it neither emits noxious gases nor generates environment...

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Main Authors: Magaji, Nuraddeen, Mustafa, Mohd. Wazir, Lawan, Abdulrahman Umar, Tukur, Alliyu, Abdullahi, Ibrahim, Mohd. Marwan, Mohd. Marwan
Format: Article
Language:English
Published: MDPI 2022
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/103878/1/MohdWazirMustafa2022_ApplicationofType2FuzzyforMaximum.pdf
http://eprints.utm.my/103878/
http://dx.doi.org/10.3390/pr10081530
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spelling my.utm.1038782023-12-04T06:11:45Z http://eprints.utm.my/103878/ Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system Magaji, Nuraddeen Mustafa, Mohd. Wazir Lawan, Abdulrahman Umar Tukur, Alliyu Abdullahi, Ibrahim Mohd. Marwan, Mohd. Marwan TK Electrical engineering. Electronics Nuclear engineering Photovoltaic systems (PV) are becoming more popular as a way to make electricity because they offer so many benefits, such as free solar irradiation to harvest and low maintenance costs. Moreover, the system is environmentally friendly because it neither emits noxious gases nor generates environmental noise. Consequently, during the operation of a PV system, the working environment is free of all types of pollution. Despite the aforementioned advantages, a photovoltaic (PV) system’s performance is significantly impacted by the fluctuation in electrical charges from the panel, such as shading conditions (PSC), weather conditions, and others, which significantly lowers the system’s efficiency. To operate the PV modules at their peak power, maximum-power point tracking (MPPT) is employed. As a result of the various peaks present during fluctuating irradiance, the P-V curves become complex. Traditional methods, such as Perturb and Observe (P and O) have also failed to monitor the Global Maximum Power Point (GMPP), therefore they usually live in the Local Maximum Power Point (LMPP), which drastically lowers the efficiency of the PV systems. This study compares type 2 fuzzy logic (T2-FLC) with the traditional Perturb and Observe Method (P and O) in three different scenarios of irradiance, temperature, and environmental factors, in order to track the maximum power point of photovoltaics. Type 1 fuzzy logic (T1-FLC) is not appropriate for systems with a high level of uncertainty (complex and non-linear systems). By modelling the vagueness and unreliability of information, type 2 fuzzy logic is better equipped to deal with linguistic uncertainties, thereby reducing the ambiguity in a system. The result for three conditions in terms of four variables; efficiency, settling time, tracking time, and overshoot, proves that this strategy offers high efficiency, dependability, and resilience. The performance of the proposed algorithm is further validated and compared to the other three tracking techniques, which include the Perturb and Observe methods (P and O). The particle swarm algorithm (PSO) and incremental conductance method results show that type 2 fuzzy (IT2FLC) is better than the three methods mentioned above. MDPI 2022-08 Article PeerReviewed application/pdf en http://eprints.utm.my/103878/1/MohdWazirMustafa2022_ApplicationofType2FuzzyforMaximum.pdf Magaji, Nuraddeen and Mustafa, Mohd. Wazir and Lawan, Abdulrahman Umar and Tukur, Alliyu and Abdullahi, Ibrahim and Mohd. Marwan, Mohd. Marwan (2022) Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system. Processes, 10 (8). pp. 1-25. ISSN 2227-9717 http://dx.doi.org/10.3390/pr10081530 DOI:10.3390/pr10081530
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Magaji, Nuraddeen
Mustafa, Mohd. Wazir
Lawan, Abdulrahman Umar
Tukur, Alliyu
Abdullahi, Ibrahim
Mohd. Marwan, Mohd. Marwan
Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system
description Photovoltaic systems (PV) are becoming more popular as a way to make electricity because they offer so many benefits, such as free solar irradiation to harvest and low maintenance costs. Moreover, the system is environmentally friendly because it neither emits noxious gases nor generates environmental noise. Consequently, during the operation of a PV system, the working environment is free of all types of pollution. Despite the aforementioned advantages, a photovoltaic (PV) system’s performance is significantly impacted by the fluctuation in electrical charges from the panel, such as shading conditions (PSC), weather conditions, and others, which significantly lowers the system’s efficiency. To operate the PV modules at their peak power, maximum-power point tracking (MPPT) is employed. As a result of the various peaks present during fluctuating irradiance, the P-V curves become complex. Traditional methods, such as Perturb and Observe (P and O) have also failed to monitor the Global Maximum Power Point (GMPP), therefore they usually live in the Local Maximum Power Point (LMPP), which drastically lowers the efficiency of the PV systems. This study compares type 2 fuzzy logic (T2-FLC) with the traditional Perturb and Observe Method (P and O) in three different scenarios of irradiance, temperature, and environmental factors, in order to track the maximum power point of photovoltaics. Type 1 fuzzy logic (T1-FLC) is not appropriate for systems with a high level of uncertainty (complex and non-linear systems). By modelling the vagueness and unreliability of information, type 2 fuzzy logic is better equipped to deal with linguistic uncertainties, thereby reducing the ambiguity in a system. The result for three conditions in terms of four variables; efficiency, settling time, tracking time, and overshoot, proves that this strategy offers high efficiency, dependability, and resilience. The performance of the proposed algorithm is further validated and compared to the other three tracking techniques, which include the Perturb and Observe methods (P and O). The particle swarm algorithm (PSO) and incremental conductance method results show that type 2 fuzzy (IT2FLC) is better than the three methods mentioned above.
format Article
author Magaji, Nuraddeen
Mustafa, Mohd. Wazir
Lawan, Abdulrahman Umar
Tukur, Alliyu
Abdullahi, Ibrahim
Mohd. Marwan, Mohd. Marwan
author_facet Magaji, Nuraddeen
Mustafa, Mohd. Wazir
Lawan, Abdulrahman Umar
Tukur, Alliyu
Abdullahi, Ibrahim
Mohd. Marwan, Mohd. Marwan
author_sort Magaji, Nuraddeen
title Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system
title_short Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system
title_full Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system
title_fullStr Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system
title_full_unstemmed Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system
title_sort application of type 2 fuzzy for maximum power point tracker for photovoltaic system
publisher MDPI
publishDate 2022
url http://eprints.utm.my/103878/1/MohdWazirMustafa2022_ApplicationofType2FuzzyforMaximum.pdf
http://eprints.utm.my/103878/
http://dx.doi.org/10.3390/pr10081530
_version_ 1784511514719289344
score 13.211869

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