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Електротехніка і Електромеханіка
Article . 2023 . Peer-reviewed
License: CC BY NC
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Fault diagnosis of power converters in a grid connected photovoltaic system using artificial neural networks

Authors: A. Mimouni; S. Laribi; M. Sebaa; T. Allaoui; A. A. Bengharbi;

Fault diagnosis of power converters in a grid connected photovoltaic system using artificial neural networks

Abstract

Introduction. The widespread use of photovoltaic systems in various applications has spotlighted the pressing requirement for reliability, efficiency and continuity of service. The main impediment to a more effective implementation has been the reliability of the power converters. Indeed, the presence of faults in power converters that can cause malfunctions in the photovoltaic system, which can reduce its performance. Novelty. This paper presents a technique for diagnosing open circuit failures in the switches (IGBTs) of power converters (DC-DC converters and three-phase inverters) in a grid-connected photovoltaic system. Purpose. To ensure supply continuity, a fault-diagnosis process is required throughout all phases of energy production, transfer, and conversion. Methods. The diagnostic approach is based on artificial neural networks and the extraction of features corresponding to the open circuit fault of the IGBT switch. This approach is based on the Clarke transformation of the three-phase currents of the inverter output as well as the calculation of the average value of these currents to determine the exact angle of the open circuit fault. Results. This method is able to effectively identify and localize single or multiple open circuit faults of the DC-DC converter IGBT switch or the three-phase inverter IGBT switches.

Keywords

силові перетворювачі, фотогальванічна система, відмова IGBT при обриві кола, power converters, open circuit failure of igbt, виявлення несправностей, штучна нейронна мережа, fault detection, TK1-9971, open circuit failure of IGBT, grid connected photovoltaic system, Electrical engineering. Electronics. Nuclear engineering, підключена до мережі, фотогальванічна система, підключена до мережі, artificial neural network

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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