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https://doi.org/10.21256/zhaw-19544| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Abstract) |
| Titel: | Data analytic tool for clustering identification based on dimensionality reduction of frequency measurements |
| Autor/-in: | Segundo Sevilla, Felix Rafael Korba, Petr Barocio Espejo, Emilio Chavez, Hector Sattinger, Walter |
| et. al: | No |
| DOI: | 10.1109/SGSMA.2019.8784626 10.21256/zhaw-19544 |
| Tagungsband: | 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA) |
| Angaben zur Konferenz: | 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), College Station, Texas, USA, 20-23 May 2019 |
| Erscheinungsdatum: | 2019 |
| Verlag / Hrsg. Institution: | IEEE |
| ISBN: | 978-1-7281-1607-5 |
| Sprache: | Englisch |
| Schlagwörter: | Power system dynamics; Data analytics; Coherency group; Frequency problem |
| Fachgebiet (DDC): | 621.3: Elektro-, Kommunikations-, Steuerungs- und Regelungstechnik |
| Zusammenfassung: | This work presents a data analytic tool for clustering analysis based on Dimensionality Reduction (DR) of power system measurements. The proposed method is applied to frequency measurements of the ENTSO-E dynamic model of continental Europe and the results are compared with other conventional DR approaches. After considerable reduction of the raw measurements, a phasor metric for identification of coherency groups of generators is proposed. The recommended measure stands for its simple implementation, interpretation and fast computation. To illustrate the effectiveness of the clustering approach and the coherency of the metrics, a particular study case following the outage of a representative generation unit in France is presented. |
| Weitere Angaben: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/19544 |
| Volltext Version: | Akzeptierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Energiesysteme und Fluid-Engineering (IEFE) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2019_Segundo-Sevilla-etal_Data-Analytic-Tool.pdf | Accepted Version | 838.37 kB | Adobe PDF |  Öffnen/Anzeigen |
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Segundo Sevilla, F. R., Korba, P., Barocio Espejo, E., Chavez, H., & Sattinger, W. (2019). Data analytic tool for clustering identification based on dimensionality reduction of frequency measurements. 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA). https://doi.org/10.1109/SGSMA.2019.8784626
Segundo Sevilla, F.R. et al. (2019) ‘Data analytic tool for clustering identification based on dimensionality reduction of frequency measurements’, in 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA). IEEE. Available at: https://doi.org/10.1109/SGSMA.2019.8784626.
F. R. Segundo Sevilla, P. Korba, E. Barocio Espejo, H. Chavez, and W. Sattinger, “Data analytic tool for clustering identification based on dimensionality reduction of frequency measurements,” in 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), 2019. doi: 10.1109/SGSMA.2019.8784626.
SEGUNDO SEVILLA, Felix Rafael, Petr KORBA, Emilio BAROCIO ESPEJO, Hector CHAVEZ und Walter SATTINGER, 2019. Data analytic tool for clustering identification based on dimensionality reduction of frequency measurements. In: 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA). Conference paper. IEEE. 2019. ISBN 978-1-7281-1607-5
Segundo Sevilla, Felix Rafael, Petr Korba, Emilio Barocio Espejo, Hector Chavez, and Walter Sattinger. 2019. “Data Analytic Tool for Clustering Identification Based on Dimensionality Reduction of Frequency Measurements.” Conference paper. In 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA). IEEE. https://doi.org/10.1109/SGSMA.2019.8784626.
Segundo Sevilla, Felix Rafael, et al. “Data Analytic Tool for Clustering Identification Based on Dimensionality Reduction of Frequency Measurements.” 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), IEEE, 2019, https://doi.org/10.1109/SGSMA.2019.8784626.
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