Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system

This project is about to carried out the optimization and implementation a fuzzy logic controller (FLC) used as a maximum-power-point tracker for a PV system, are presented. Maximum power point tracking (MPPT) are used to integrate with photovoltaic (PV) power systems so that the photovoltaic...

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Main Author: Tukeman, Zalifah
Format: Thesis
Language:English
English
English
Published: 2012
Subjects:
Online Access:http://eprints.uthm.edu.my/2473/
http://eprints.uthm.edu.my/2473/2/24p%20ZALIFAH%20TUKEMAN.pdf
http://eprints.uthm.edu.my/2473/1/ZALIFAH%20TUKEMAN%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/2473/3/ZALIFAH%20TUKEMAN%20WATERMARK.pdf
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author Tukeman, Zalifah
author_facet Tukeman, Zalifah
author_sort Tukeman, Zalifah
building UTHM Institutional Repository
collection Online Access
description This project is about to carried out the optimization and implementation a fuzzy logic controller (FLC) used as a maximum-power-point tracker for a PV system, are presented. Maximum power point tracking (MPPT) are used to integrate with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver the maximum power available. The near optimum design membership functions and control rules were found simultaneously by genetic algorithms (GAs) which are search algorithms based the mechanism of natural selection and genetics. These are easy to implement and efficient for multivariable optimization problems such as in fuzzy controller design that consist large number. The FLC designed and the implementation of photovoltaic model using Matlab/Simulink software package which can representative of PV cell module. Taking effect of sunlight irradiance and cell temperature into consideration, the output power and current characteristics of PV model are simulated and optimized.
first_indexed 2025-11-15T19:59:18Z
format Thesis
id uthm-2473
institution Universiti Tun Hussein Onn Malaysia
institution_category Local University
language English
English
English
last_indexed 2025-11-15T19:59:18Z
publishDate 2012
recordtype eprints
repository_type Digital Repository
spelling uthm-24732021-11-01T02:11:40Z http://eprints.uthm.edu.my/2473/ Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system Tukeman, Zalifah QA Mathematics QA299.6-433 Analysis This project is about to carried out the optimization and implementation a fuzzy logic controller (FLC) used as a maximum-power-point tracker for a PV system, are presented. Maximum power point tracking (MPPT) are used to integrate with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver the maximum power available. The near optimum design membership functions and control rules were found simultaneously by genetic algorithms (GAs) which are search algorithms based the mechanism of natural selection and genetics. These are easy to implement and efficient for multivariable optimization problems such as in fuzzy controller design that consist large number. The FLC designed and the implementation of photovoltaic model using Matlab/Simulink software package which can representative of PV cell module. Taking effect of sunlight irradiance and cell temperature into consideration, the output power and current characteristics of PV model are simulated and optimized. 2012-07 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/2473/2/24p%20ZALIFAH%20TUKEMAN.pdf text en http://eprints.uthm.edu.my/2473/1/ZALIFAH%20TUKEMAN%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/2473/3/ZALIFAH%20TUKEMAN%20WATERMARK.pdf Tukeman, Zalifah (2012) Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system. Masters thesis, Universiti Tun Hussein Onn Malaysia.
spellingShingle QA Mathematics
QA299.6-433 Analysis
Tukeman, Zalifah
Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
title Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
title_full Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
title_fullStr Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
title_full_unstemmed Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
title_short Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
title_sort fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
topic QA Mathematics
QA299.6-433 Analysis
url http://eprints.uthm.edu.my/2473/
http://eprints.uthm.edu.my/2473/2/24p%20ZALIFAH%20TUKEMAN.pdf
http://eprints.uthm.edu.my/2473/1/ZALIFAH%20TUKEMAN%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/2473/3/ZALIFAH%20TUKEMAN%20WATERMARK.pdf