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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| Format: | Thesis |
| Language: | en en en |
| Published: |
2012
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| 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 http://eprints.uthm.edu.my/2473/ |
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| _version_ | 1833417076580024320 |
|---|---|
| author | Tukeman, Zalifah |
| author_facet | Tukeman, Zalifah |
| author_sort | Tukeman, Zalifah |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my.uthm.eprints-2473 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en en en |
| publishDate | 2012 |
| record_format | eprints |
| spelling | my.uthm.eprints-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/2473/2/24p%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 http://eprints.uthm.edu.my/2473/ |
| url_provider | http://eprints.uthm.edu.my/ |