PV Maximum Power-Point Tracking by Using Artificial Neural Network

PV Maximum Power-Point Tracking by Using Artificial Neural Network

In this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to...

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Main Authors: Farzad Sedaghati, Ali Nahavandi, Mohammad Ali Badamchizadeh, Sehraneh Ghaemi, Mehdi Abedinpour Fallah
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2012/506709
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spelling doaj-9666a2a7f8a842688c8b1258dcf089f52020-11-24T20:51:52ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/506709506709PV Maximum Power-Point Tracking by Using Artificial Neural NetworkFarzad Sedaghati0Ali Nahavandi1Mohammad Ali Badamchizadeh2Sehraneh Ghaemi3Mehdi Abedinpour Fallah4Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, IranFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, IranFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, IranFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, IranDepartment of Mechanical and Industrial Engineering, Concordia University, Montreal, QC, CanadaIn this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under different atmospheric conditions. By properly controling of dc-dc boost converter, tracking of maximum power point is feasible. To verify theory analysis, simulation result is obtained by using MATLAB/SIMULINK.http://dx.doi.org/10.1155/2012/506709
collection DOAJ
language English
format Article
sources DOAJ
author Farzad Sedaghati
Ali Nahavandi
Mohammad Ali Badamchizadeh
Sehraneh Ghaemi
Mehdi Abedinpour Fallah
spellingShingle Farzad Sedaghati
Ali Nahavandi
Mohammad Ali Badamchizadeh
Sehraneh Ghaemi
Mehdi Abedinpour Fallah
PV Maximum Power-Point Tracking by Using Artificial Neural Network
Mathematical Problems in Engineering
author_facet Farzad Sedaghati
Ali Nahavandi
Mohammad Ali Badamchizadeh
Sehraneh Ghaemi
Mehdi Abedinpour Fallah
author_sort Farzad Sedaghati
title PV Maximum Power-Point Tracking by Using Artificial Neural Network
title_short PV Maximum Power-Point Tracking by Using Artificial Neural Network
title_full PV Maximum Power-Point Tracking by Using Artificial Neural Network
title_fullStr PV Maximum Power-Point Tracking by Using Artificial Neural Network
title_full_unstemmed PV Maximum Power-Point Tracking by Using Artificial Neural Network
title_sort pv maximum power-point tracking by using artificial neural network
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2012-01-01
description In this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under different atmospheric conditions. By properly controling of dc-dc boost converter, tracking of maximum power point is feasible. To verify theory analysis, simulation result is obtained by using MATLAB/SIMULINK.
url http://dx.doi.org/10.1155/2012/506709
work_keys_str_mv AT farzadsedaghati pvmaximumpowerpointtrackingbyusingartificialneuralnetwork
AT alinahavandi pvmaximumpowerpointtrackingbyusingartificialneuralnetwork
AT mohammadalibadamchizadeh pvmaximumpowerpointtrackingbyusingartificialneuralnetwork
AT sehranehghaemi pvmaximumpowerpointtrackingbyusingartificialneuralnetwork
AT mehdiabedinpourfallah pvmaximumpowerpointtrackingbyusingartificialneuralnetwork
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