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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Bibliographic Details
Main Author: Tukeman, Zalifah
Format: Thesis
Language:English
English
English
Published: 2012
Subjects:
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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Summary: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.