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Reseach Article

Maximum Power Point Tracking of Solar Photovoltaic system using Artificial Neural Networks

Published on July 2015 by Sanjay Yadav, Manoj Kumar, Ranjana Arora
Innovations in Computing and Information Technology (Cognition 2015)
Foundation of Computer Science USA
COGNITION2015 - Number 4
July 2015
Authors: Sanjay Yadav, Manoj Kumar, Ranjana Arora
56c56375-3d96-4421-a91b-4251faf56ef5

Sanjay Yadav, Manoj Kumar, Ranjana Arora . Maximum Power Point Tracking of Solar Photovoltaic system using Artificial Neural Networks. Innovations in Computing and Information Technology (Cognition 2015). COGNITION2015, 4 (July 2015), 1-5.

@article{
author = { Sanjay Yadav, Manoj Kumar, Ranjana Arora },
title = { Maximum Power Point Tracking of Solar Photovoltaic system using Artificial Neural Networks },
journal = { Innovations in Computing and Information Technology (Cognition 2015) },
issue_date = { July 2015 },
volume = { COGNITION2015 },
number = { 4 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /proceedings/cognition2015/number4/21905-2151/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Innovations in Computing and Information Technology (Cognition 2015)
%A Sanjay Yadav
%A Manoj Kumar
%A Ranjana Arora
%T Maximum Power Point Tracking of Solar Photovoltaic system using Artificial Neural Networks
%J Innovations in Computing and Information Technology (Cognition 2015)
%@ 0975-8887
%V COGNITION2015
%N 4
%P 1-5
%D 2015
%I International Journal of Computer Applications
Abstract

Solar energy is clean and renewable source of energy and its decentralized property is appropriate well at the scattered state of the zones with low density of population. The cost of electricity from the solar array system is comparatively more than the electricity from the utility grid. Therefore, it make sense to operate the PV system at maximum efficiency by maximum power point tracking (MPPT)at any given environmental condition. In this work, the neural network (NN) back propagation algorithm is used to control the operation of the PV array for maximum power point extraction. Two error functions are used. The first is classical error function and the second is a modified error function which takes into consideration the derivative of the error function also. The results obtained are compared and discussed in the current study.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Neural Network Mppt Technique Solar Photovoltaic System