PV boost converter conditioning using neural network

Abd Aziz, Aizat (2013) PV boost converter conditioning using neural network. Masters thesis, Universiti Tun Hussein Malaysia.

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Abstract

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.

Item Type:	Thesis (Masters)
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Electrical and Electronic Engineering > Department of Electrical Engineering
Depositing User:	Mrs. Sabarina Che Mat
Date Deposited:	10 Mar 2022 03:36
Last Modified:	10 Mar 2022 03:36
URI:	http://eprints.uthm.edu.my/id/eprint/6627

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