A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations

The reliability of systems and components is a fundamental need for the efficient development of a smart distribution grid. In fact, the presence of a fault in one component of the grid could potentially lead to a service interruption and loss of profit. Since faults cannot be avoided, the introduct...

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Autores principales:	Giovanni Betta, Domenico Capriglione, Luigi Ferrigno, Marco Laracca, Gianfranco Miele, Nello Polese, Silvia Sangiovanni
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	FDI IFDI predictive maintenance AC/DC converter fault diagnosis Technology T
Acceso en línea:	https://doaj.org/article/9bf6257d2c454db49f1746fce05bb745
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spelling	oai:doaj.org-article:9bf6257d2c454db49f1746fce05bb7452021-11-25T17:27:43ZA Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations10.3390/en142276681996-1073https://doaj.org/article/9bf6257d2c454db49f1746fce05bb7452021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7668https://doaj.org/toc/1996-1073The reliability of systems and components is a fundamental need for the efficient development of a smart distribution grid. In fact, the presence of a fault in one component of the grid could potentially lead to a service interruption and loss of profit. Since faults cannot be avoided, the introduction of a diagnostic scheme could predict the fault of a component in order to carry out predictive maintenance. In this framework, this paper proposes a novel Fault Detection and Isolation (FDI) scheme for AC/DC converters in MV/LV substations. In order to improve the reliability of the FDI procedure, the system architecture includes also an Instrument Fault Detection and Isolation section for identifying faults that could occur on the instruments and sensors involved in the monitoring process of the AC/DC converter. The proposed architecture is scalable, easily upgradable, and uses cost-effective sensors. Tests, carried out on a real test site, have demonstrated the efficacy of the proposal showing very good IFDI diagnostic performance for the 12 types of faults tested. Furthermore, as the FDI diagnostic performance regards, it shows a detection rate close to 100%.Giovanni BettaDomenico CapriglioneLuigi FerrignoMarco LaraccaGianfranco MieleNello PoleseSilvia SangiovanniMDPI AGarticleFDIIFDIpredictive maintenanceAC/DC converterfault diagnosisTechnologyTENEnergies, Vol 14, Iss 7668, p 7668 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	FDI IFDI predictive maintenance AC/DC converter fault diagnosis Technology T
spellingShingle	FDI IFDI predictive maintenance AC/DC converter fault diagnosis Technology T Giovanni Betta Domenico Capriglione Luigi Ferrigno Marco Laracca Gianfranco Miele Nello Polese Silvia Sangiovanni A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations
description	The reliability of systems and components is a fundamental need for the efficient development of a smart distribution grid. In fact, the presence of a fault in one component of the grid could potentially lead to a service interruption and loss of profit. Since faults cannot be avoided, the introduction of a diagnostic scheme could predict the fault of a component in order to carry out predictive maintenance. In this framework, this paper proposes a novel Fault Detection and Isolation (FDI) scheme for AC/DC converters in MV/LV substations. In order to improve the reliability of the FDI procedure, the system architecture includes also an Instrument Fault Detection and Isolation section for identifying faults that could occur on the instruments and sensors involved in the monitoring process of the AC/DC converter. The proposed architecture is scalable, easily upgradable, and uses cost-effective sensors. Tests, carried out on a real test site, have demonstrated the efficacy of the proposal showing very good IFDI diagnostic performance for the 12 types of faults tested. Furthermore, as the FDI diagnostic performance regards, it shows a detection rate close to 100%.
format	article
author	Giovanni Betta Domenico Capriglione Luigi Ferrigno Marco Laracca Gianfranco Miele Nello Polese Silvia Sangiovanni
author_facet	Giovanni Betta Domenico Capriglione Luigi Ferrigno Marco Laracca Gianfranco Miele Nello Polese Silvia Sangiovanni
author_sort	Giovanni Betta
title	A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations
title_short	A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations
title_full	A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations
title_fullStr	A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations
title_full_unstemmed	A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations
title_sort	fault diagnostic scheme for predictive maintenance of ac/dc converters in mv/lv substations
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9bf6257d2c454db49f1746fce05bb745
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A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations

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