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Performance Comparison of Quantitative Methods for PMU Data Event Detection with Noisy Data

Comunicació de congrés presentada a: 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), organitzat per l’IEEE Power & Energy Society (PES) i la Delft University of Technology (Països Baixos), del 26 a 28 d’octubre de 2020. https://ieee-isgt-europe.org/

This article compares distinct signal-based and knowledge-based approaches often applied to process and detect events in vast amounts of data collected by phasor measurement units (PMU). The computation times and the accuracy of correct event detections are tested and evaluated in a 1-hour data file from the UT-Austin Independent Texas Synchrophasor Network with phasor quantities plus an additive noise gathered at different PMU substations. A sliding time window is considered to build a representative model of the system operating conditions on the fly and search for power system phenomena as soon as new data are available

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

IEEE

Autor: Souto, Laiz
Meléndez i Frigola, Joaquim
Herraiz Jaramillo, Sergio
Resum: Comunicació de congrés presentada a: 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), organitzat per l’IEEE Power & Energy Society (PES) i la Delft University of Technology (Països Baixos), del 26 a 28 d’octubre de 2020. https://ieee-isgt-europe.org/
This article compares distinct signal-based and knowledge-based approaches often applied to process and detect events in vast amounts of data collected by phasor measurement units (PMU). The computation times and the accuracy of correct event detections are tested and evaluated in a 1-hour data file from the UT-Austin Independent Texas Synchrophasor Network with phasor quantities plus an additive noise gathered at different PMU substations. A sliding time window is considered to build a representative model of the system operating conditions on the fly and search for power system phenomena as soon as new data are available
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
Accés al document: http://hdl.handle.net/10256/18570
Llenguatge: eng
Editor: IEEE
Col·lecció: info:eu-repo/semantics/altIdentifier/doi/10.1109/ISGT-Europe47291.2020.9248826
Versió postprint del document publicat a: 10.1109/ISGT-Europe47291.2020.9248826
info:eu-repo/grantAgreement/EC/H2020/773715
Drets: Tots els drets reservats
Matèria: Errors de sistemes (Enginyeria) -- Localització -- Congressos
System failures (Engineering) -- Location -- Congresses
Control electrònic -- Congressos
Electronic control -- Congresses
Anàlisi de components principals -- Congressos
Principal components analysis -- Congresses
Títol: Performance Comparison of Quantitative Methods for PMU Data Event Detection with Noisy Data
Tipus: info:eu-repo/semantics/conferenceObject
Repositori: DUGiDocs

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