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...

Full description

Saved in:

Bibliographic Details
Main Author:	Tukeman, Zalifah
Format:	Thesis
Language:	English English English
Published:	2012
Subjects:	QA Mathematics QA299.6-433 Analysis
Online Access:	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
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uthm-ep.2473
record_format	uketd_dc
spelling	my-uthm-ep.24732021-11-01T02:11:40Z Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system 2012-07 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 http://eprints.uthm.edu.my/2473/ http://eprints.uthm.edu.my/2473/2/24p%20ZALIFAH%20TUKEMAN.pdf text en public http://eprints.uthm.edu.my/2473/1/ZALIFAH%20TUKEMAN%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/2473/3/ZALIFAH%20TUKEMAN%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA Mathematics QA299.6-433 Analysis
spellingShingle	QA Mathematics QA299.6-433 Analysis Tukeman, Zalifah Fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
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.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Tukeman, Zalifah
author_facet	Tukeman, Zalifah
author_sort	Tukeman, Zalifah
title	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_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_sort	fuzzy logic – genetic algorithm based maximum power point tracking in photovoltaic system
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2012
url	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
_version_	1747830960988094464

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

Similar Items