| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | A tensor decomposition approach for contingency screening and coherency identification in power systems |
| Autor/-in: | Sandoval, Betsy Korba, Petr Segundo Sevilla, Felix Rafael Barocio Espejo, Emilio |
| et. al: | No |
| DOI: | 10.1109/PowerTech46648.2021.9494922 |
| Tagungsband: | 2021 IEEE Madrid PowerTech |
| Angaben zur Konferenz: | PowerTech 2021, Madrid (online), 28 June - 2 July 2021 |
| Erscheinungsdatum: | 2021 |
| Verlag / Hrsg. Institution: | IEEE |
| ISBN: | 978-1-6654-3597-0 |
| Sprache: | Englisch |
| Schlagwörter: | Coherency identification; PARAFAC2; Screening contingency; Tensor decomposition |
| Fachgebiet (DDC): | 621.3: Elektro-, Kommunikations-, Steuerungs- und Regelungstechnik |
| Zusammenfassung: | Contingency Screening and Coherent Identification are two fundamental parts of power system planning and operation. A common characteristic among these two methods is the need to analyze multiples contingencies. However, most of the current work existing in the literature is based on the paradigm of analyzing one contingency at a time, using 2D arrays (matrices) for the event representation. The drawback with this type of representations is the impossibility to consider multiple contingencies simultaneously. In this paper a reformulation of the problem using 3D arrays (tensors) is presented. Then, the extraction of the information is carried out using PARAFAC2. With this information, a severity index for contingency screening is proposed and identification of the coherent areas is accomplished. The approach is validated in the IEEE NETSNYPS test system. The results confirm that the proposed approach allows to extract more information than in the traditional form. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/23805 |
| Volltext Version: | Publizierte 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 |
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Sandoval, B., Korba, P., Segundo Sevilla, F. R., & Barocio Espejo, E. (2021). A tensor decomposition approach for contingency screening and coherency identification in power systems. 2021 IEEE Madrid PowerTech. https://doi.org/10.1109/PowerTech46648.2021.9494922
Sandoval, B. et al. (2021) ‘A tensor decomposition approach for contingency screening and coherency identification in power systems’, in 2021 IEEE Madrid PowerTech. IEEE. Available at: https://doi.org/10.1109/PowerTech46648.2021.9494922.
B. Sandoval, P. Korba, F. R. Segundo Sevilla, and E. Barocio Espejo, “A tensor decomposition approach for contingency screening and coherency identification in power systems,” in 2021 IEEE Madrid PowerTech, 2021. doi: 10.1109/PowerTech46648.2021.9494922.
SANDOVAL, Betsy, Petr KORBA, Felix Rafael SEGUNDO SEVILLA und Emilio BAROCIO ESPEJO, 2021. A tensor decomposition approach for contingency screening and coherency identification in power systems. In: 2021 IEEE Madrid PowerTech. Conference paper. IEEE. 2021. ISBN 978-1-6654-3597-0
Sandoval, Betsy, Petr Korba, Felix Rafael Segundo Sevilla, and Emilio Barocio Espejo. 2021. “A Tensor Decomposition Approach for Contingency Screening and Coherency Identification in Power Systems.” Conference paper. In 2021 IEEE Madrid PowerTech. IEEE. https://doi.org/10.1109/PowerTech46648.2021.9494922.
Sandoval, Betsy, et al. “A Tensor Decomposition Approach for Contingency Screening and Coherency Identification in Power Systems.” 2021 IEEE Madrid PowerTech, IEEE, 2021, https://doi.org/10.1109/PowerTech46648.2021.9494922.
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