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Reseach Article

New Algorithm for Fault Diagnosis of Photovoltaic Energy Systems

by A.h.mohamed, A.m.nassar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 9
Year of Publication: 2015
Authors: A.h.mohamed, A.m.nassar

A.h.mohamed, A.m.nassar . New Algorithm for Fault Diagnosis of Photovoltaic Energy Systems. International Journal of Computer Applications. 114, 9 ( March 2015), 26-31. DOI=10.5120/20008-1959

@article{ 10.5120/20008-1959,
author = { A.h.mohamed, A.m.nassar },
title = { New Algorithm for Fault Diagnosis of Photovoltaic Energy Systems },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 9 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 26-31 },
numpages = {9},
url = { },
doi = { 10.5120/20008-1959 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:52:16.328187+05:30
%A A.h.mohamed
%A A.m.nassar
%T New Algorithm for Fault Diagnosis of Photovoltaic Energy Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 9
%P 26-31
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

In the recent years, Artificial Neural Networks (ANNs) have proved their great success for fault diagnosis in many applications. The performance of the ANN depends on its topology. So, optimizing the ANN's topology is an essential task to improve its efficiency. On another side, genetic algorithms (GAs) are becoming a main optimization methodology used in solving the engineering problems. However, the proposed system introduces a new algorithm that uses genetic algorithm to optimize the topology of the ANN. It has been used for diagnosis and repairing the Photovoltaic (PV) energy systems dynamically online as a case of study. Recently, PV systems have a great attention and concerning by the researchers to solve the power problems all over the world. Many diagnostic systems have been developed to diagnose the PV faults, but they are very expensive and sometimes are unmanaged especially for complex and critical PV systems. The proposed system enables the PV systems can overcome these limitations. Its obtained results are compared with fuzzy-based and traditional neural network-based diagnostic PV systems. It is found that, the proposed system has proved its goodness for the practical applications.

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Index Terms

Computer Science
Information Sciences


Neural Network Genetic Algorithm Photovoltaic Systems Fault Diagnosis and Fault Repairing.