Journal ArticleDOI
A novel fault diagnosis technique for photovoltaic systems based on artificial neural networks
TLDR
In this article, a fault diagnostic technique for photovoltaic systems based on Artificial Neural Networks (ANN) is proposed for a given set of working conditions -i.e., solar irradiance and PV module's temperature -a number of attributes such as current, voltage, and number of peaks in the current voltage characteristics of the PV strings are calculated using a simulation model.About:Â
This article is published in Renewable Energy.The article was published on 2016-05-01. It has received 392 citations till now. The article focuses on the topics: Photovoltaic system & Fault detection and isolation.read more
Citations
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Journal ArticleDOI
Fault detection and diagnosis methods for photovoltaic systems: A review
TL;DR: The types and causes of PV systems (PVS) failures are presented, then different methods proposed in literature for FDD of PVS are reviewed and discussed; particularly faults occurring in PV arrays (PVA).
Journal ArticleDOI
Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing
TL;DR: A novel method called improved convolutional deep belief network (CDBN) with compressed sensing (CS) is developed for feature learning and fault diagnosis of rolling bearing and results confirm that the developed method is more effective than the traditional methods.
Journal ArticleDOI
A comprehensive review on protection challenges and fault diagnosis in PV systems
Dhanup S. Pillai,N. Rajasekar +1 more
TL;DR: An in depth analysis of various fault occurrences, protection challenges and ramifications due to undetected faults in PV systems is carried out.
Journal ArticleDOI
Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristics
TL;DR: Both the simulation and experimental results show that the optimized KELM based fault diagnosis model can achieve high accuracy, reliability, and good generalization performance.
Journal ArticleDOI
A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals
TL;DR: A conversion method converting vibration signals from multiple sensors to images is proposed that can integrate information to get richer features than vibration signal from single sensor by this method feature maps of different fault types can be obtained without tedious parameter adjustments.
References
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Proceedings ArticleDOI
PV panel model based on datasheet values
TL;DR: A PV panel model is built and tested, which is able to predict the panel behavior in different temperature and irradiance conditions, based on the single-diode five-parameters model.
Journal ArticleDOI
Automatic supervision and fault detection of PV systems based on power losses analysis
Aissa Chouder,Santiago Silvestre +1 more
TL;DR: In this paper, an automatic supervision and fault detection procedure for PV systems, based on the power losses analysis, has been presented, which includes parameter extraction techniques to calculate main PV system parameters from monitoring data, taking into account the environmental irradiance and module temperature evolution.
Journal ArticleDOI
Monitoring and remote failure detection of grid-connected PV systems based on satellite observations
Anja Drews,A. de Keizer,Hans Georg Beyer,Elke Lorenz,Jethro Betcke,W.G.J.H.M. van Sark,W. Heydenreich,E. Wiemken,S. Stettler,Peter Toggweiler,S. Bofinger,M. Schneider,G. Heilscher,Detlev Heinemann +13 more
TL;DR: A fully automated performance check has been developed to assure maximum energy yields and to optimize system maintenance for small grid-connected PV systems within the EU project PVSAT-2 and presents results of an 8-months test phase with 100 PV systems in three European countries.
Journal ArticleDOI
Modeling and fault diagnosis of a photovoltaic system
TL;DR: In this paper, a circuit-based simulation model of a photovoltaic (PV) panel by PSIM software package is developed, firstly, a 3-kW PV arrays established by using the proposed PSIM model with series and parallel connection is not only employed to carry out the fault analysis, but also to represent its I-V and P-V characteristics at variable surface temperatures and isolations under normal operation.
Proceedings ArticleDOI
Decision tree-based fault detection and classification in solar photovoltaic arrays
TL;DR: In this paper, a fault detection and classification method based on decision trees (DT) was proposed to detect and classify faults in PV arrays, such as PV array voltage, current, operating temperature and irradiance.
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Automatic supervision and fault detection of PV systems based on power losses analysis
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