PV boost converter conditioning using neural network

This master report presents a voltage control system for DC-DC boost converter integrated with Photovoltaic (PV) array using optimized feed-forward neural network controller. A specific output voltage of a boost converter is regulated at a constant value under input voltage variations caused by a...

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Main Author:	Abd Aziz, Aizat
Format:	Thesis
Language:	English English English
Published:	2013
Subjects:	TK7800-8360 Electronics
Online Access:	http://eprints.uthm.edu.my/6627/1/24p%20AIZAT%20ABD%20AZIZ.pdf http://eprints.uthm.edu.my/6627/2/AIZAT%20ABD%20AZIZ%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6627/3/AIZAT%20ABD%20AZIZ%20WATERMARK.pdf
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id	my-uthm-ep.6627
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spelling	my-uthm-ep.66272022-03-10T03:36:55Z PV boost converter conditioning using neural network 2013-07 Abd Aziz, Aizat TK7800-8360 Electronics This master report presents a voltage control system for DC-DC boost converter integrated with Photovoltaic (PV) array using optimized feed-forward neural network controller. A specific output voltage of a boost converter is regulated at a constant value under input voltage variations caused by a sudden changes in irradiation for a purpose of supplying a stabilize dc voltage to Base Transceiver Station (BTS) telecommunication equipment that required a 48V dc input supply to be operated. For a given solar irradiance, the tracking algorithm changes the duty ratio of the converter such that the output voltage produced equals to 48V. This is done by the feed-forward loop, which generates an error signal by comparing converter output voltage and reference voltage. Depending on the error and change of error signals, the neural network controller generates a control signal for the pulse widthmodulation generator which in turn adjusts the duty ratio of the converter. The effectiveness of the proposed method is verified by developing a simulation model in MATLAB-Simulink program. Tracking performance of the proposed controller is also compared with the conventional proportional-integral-differential (PID) controller. The simulation results show that the proposed neural network controller (NNC) produce an improvement of control performance compared to the PID controller. 2013-07 Thesis http://eprints.uthm.edu.my/6627/ http://eprints.uthm.edu.my/6627/1/24p%20AIZAT%20ABD%20AZIZ.pdf text en public http://eprints.uthm.edu.my/6627/2/AIZAT%20ABD%20AZIZ%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/6627/3/AIZAT%20ABD%20AZIZ%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TK7800-8360 Electronics
spellingShingle	TK7800-8360 Electronics Abd Aziz, Aizat PV boost converter conditioning using neural network
description	This master report presents a voltage control system for DC-DC boost converter integrated with Photovoltaic (PV) array using optimized feed-forward neural network controller. A specific output voltage of a boost converter is regulated at a constant value under input voltage variations caused by a sudden changes in irradiation for a purpose of supplying a stabilize dc voltage to Base Transceiver Station (BTS) telecommunication equipment that required a 48V dc input supply to be operated. For a given solar irradiance, the tracking algorithm changes the duty ratio of the converter such that the output voltage produced equals to 48V. This is done by the feed-forward loop, which generates an error signal by comparing converter output voltage and reference voltage. Depending on the error and change of error signals, the neural network controller generates a control signal for the pulse widthmodulation generator which in turn adjusts the duty ratio of the converter. The effectiveness of the proposed method is verified by developing a simulation model in MATLAB-Simulink program. Tracking performance of the proposed controller is also compared with the conventional proportional-integral-differential (PID) controller. The simulation results show that the proposed neural network controller (NNC) produce an improvement of control performance compared to the PID controller.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Abd Aziz, Aizat
author_facet	Abd Aziz, Aizat
author_sort	Abd Aziz, Aizat
title	PV boost converter conditioning using neural network
title_short	PV boost converter conditioning using neural network
title_full	PV boost converter conditioning using neural network
title_fullStr	PV boost converter conditioning using neural network
title_full_unstemmed	PV boost converter conditioning using neural network
title_sort	pv boost converter conditioning using neural network
granting_institution	Universiti Tun Hussein Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2013
url	http://eprints.uthm.edu.my/6627/1/24p%20AIZAT%20ABD%20AZIZ.pdf http://eprints.uthm.edu.my/6627/2/AIZAT%20ABD%20AZIZ%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6627/3/AIZAT%20ABD%20AZIZ%20WATERMARK.pdf
_version_	1747831076725719040

PV boost converter conditioning using neural network

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