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Fault Location in Low Voltage Smart Grids Based on Similarity Criteria in the Principal Component Subspace

Comunicació de congrés presentada a: The Eleventh Conference on Innovative Smart Grid Technologies (ISGT 2020), sponsored by the IEEE Power & Energy Society (PES), will be held February 17-20, 2020 at the Grand Hyatt Washington, Washington D.C.

This paper presents a new strategy based on multivariate statistical analysis for fault location and classification in power distribution networks with distributed energy resources, variable loads, and switches enabling grid reconfiguration. The statistical method relies on impedance measurements acquired at the substation buses to build a data-driven model of the network operating conditions with dimensionality reduction, and considers a few reference scenarios representing standard operating conditions and short-circuit operation to perform fault location and classification with use of similarity criteria in the principal component subspace. Moreover, this paper includes a case study with a real-based low voltage power distribution network to test and validate the methodology

This research was supported by the European Union’s Horizon 2020 research and innovation programme, call LCE-01-2016-2017, under the auspices of the project Renewable penetration levered by Efficient Low Voltage Distribution grids, grant agreement number 773715, and University of Girona scholarship

© 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2020, p. 1-5

IEEE

Autor: Souto, Laiz
Meléndez i Frigola, Joaquim
Herraiz Jaramillo, Sergio
Data: 17 febrer 2020
Resum: Comunicació de congrés presentada a: The Eleventh Conference on Innovative Smart Grid Technologies (ISGT 2020), sponsored by the IEEE Power & Energy Society (PES), will be held February 17-20, 2020 at the Grand Hyatt Washington, Washington D.C.
This paper presents a new strategy based on multivariate statistical analysis for fault location and classification in power distribution networks with distributed energy resources, variable loads, and switches enabling grid reconfiguration. The statistical method relies on impedance measurements acquired at the substation buses to build a data-driven model of the network operating conditions with dimensionality reduction, and considers a few reference scenarios representing standard operating conditions and short-circuit operation to perform fault location and classification with use of similarity criteria in the principal component subspace. Moreover, this paper includes a case study with a real-based low voltage power distribution network to test and validate the methodology
This research was supported by the European Union’s Horizon 2020 research and innovation programme, call LCE-01-2016-2017, under the auspices of the project Renewable penetration levered by Efficient Low Voltage Distribution grids, grant agreement number 773715, and University of Girona scholarship
Format: application/pdf
Cita: https://doi.org/10.1109/ISGT45199.2020.9087707
Accés al document: http://hdl.handle.net/10256/17787
Llenguatge: eng
Editor: IEEE
Col·lecció: Versió postprint del document publicat a: 10.1109/ISGT45199.2020.9087707
Contribucions a Congressos (D-EEEiA)
info:eu-repo/grantAgreement/EC/H2020/773715
És part de: © 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2020, p. 1-5
Drets: Tots els drets reservats
Matèria: Baixa tensió -- Congressos
Low voltage systems -- Congresses
Enginyeria elèctrica -- Congressos
Electrical engineering -- Congresses
Errors de sistemes (Enginyeria) -- Localització -- Congressos
System failures (Engineering) -- Location -- Congresses
Electric power distribution -- Low voltage systems -- Congresos
Energia elèctrica -- Distribució -- Baixa tensió -- Congresses
Control electrònic -- Congressos
Electronic control -- Congresses
Anàlisi de components principals -- Congressos
Principal components analysis -- Congresses
Títol: Fault Location in Low Voltage Smart Grids Based on Similarity Criteria in the Principal Component Subspace
Tipus: info:eu-repo/semantics/conferenceObject
Repositori: DUGiDocs

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