1. ZHAW digitalcollection
  2. School of Engineering
  3. Publikationen
  4. Publikationen School of Engineering
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRamirez Gonzalez, Miguel-
dc.contributor.authorNösberger, Lukas-
dc.contributor.authorSegundo Sevilla, Felix Rafael-
dc.contributor.authorKorba, Petr-
dc.date.accessioned2023-01-13T14:50:14Z-
dc.date.available2023-01-13T14:50:14Z-
dc.date.issued2022-12-07-
dc.identifier.isbn978-1-6654-6318-8de_CH
dc.identifier.issn2381-2842de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/26641-
dc.description.abstractAn approach for the small-signal stability assessment (SSSA) of power systems using a Convolutional Neural Network (CNN) model with transfer learning is presented in this paper. The concept of permutation feature importance (PFI) is included in model development to identify and drop the most irrelevant features in a given dataset, which minimizes the input information required by the model to achieve a certain performance and reduces the set of measurement locations for the related application. Then, a transfer learning approach using weight initialization and feature extraction is applied to leverage the knowledge of a pretrained model when a new independent dataset (obtained from the integration of converter-interfaced generation) is considered. Simulation results demonstrate that the transfer learning-based CNN model is able to exploit previous knowledge and provide a superior performance, as compared to the traditional rebuilt-from-scratch model.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectPower systemde_CH
dc.subjectSmall-signal stabilityde_CH
dc.subjectConvolutional neural networkde_CH
dc.subjectTransfer learningde_CH
dc.subjectFeature importancede_CH
dc.subject.ddc621.3: Elektro-, Kommunikations-, Steuerungs- und Regelungstechnikde_CH
dc.titleSmall-signal stability assessment with transfer learning-based convolutional neural networksde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Energiesysteme und Fluid-Engineering (IEFE)de_CH
dc.identifier.doi10.1109/EPEC56903.2022.9999738de_CH
zhaw.conference.details2022 IEEE Electrical Power and Energy Conference (EPEC), online, 5-7 December 2022de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end391de_CH
zhaw.pages.start386de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedings2022 IEEE Electrical Power and Energy Conference (EPEC)de_CH
zhaw.webfeedElektrische Energiesysteme und Smart Gridsde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Engineering

Files in This Item:
There are no files associated with this item.
Show simple item record
Ramirez Gonzalez, M., Nösberger, L., Segundo Sevilla, F. R., & Korba, P. (2022). Small-signal stability assessment with transfer learning-based convolutional neural networks [Conference paper]. 2022 IEEE Electrical Power and Energy Conference (EPEC), 386–391. https://doi.org/10.1109/EPEC56903.2022.9999738
Ramirez Gonzalez, M. et al. (2022) ‘Small-signal stability assessment with transfer learning-based convolutional neural networks’, in 2022 IEEE Electrical Power and Energy Conference (EPEC). IEEE, pp. 386–391. Available at: https://doi.org/10.1109/EPEC56903.2022.9999738.
M. Ramirez Gonzalez, L. Nösberger, F. R. Segundo Sevilla, and P. Korba, “Small-signal stability assessment with transfer learning-based convolutional neural networks,” in 2022 IEEE Electrical Power and Energy Conference (EPEC), Dec. 2022, pp. 386–391. doi: 10.1109/EPEC56903.2022.9999738.
RAMIREZ GONZALEZ, Miguel, Lukas NÖSBERGER, Felix Rafael SEGUNDO SEVILLA und Petr KORBA, 2022. Small-signal stability assessment with transfer learning-based convolutional neural networks. In: 2022 IEEE Electrical Power and Energy Conference (EPEC). Conference paper. IEEE. 7 Dezember 2022. S. 386–391. ISBN 978-1-6654-6318-8
Ramirez Gonzalez, Miguel, Lukas Nösberger, Felix Rafael Segundo Sevilla, and Petr Korba. 2022. “Small-Signal Stability Assessment with Transfer Learning-Based Convolutional Neural Networks.” Conference paper. In 2022 IEEE Electrical Power and Energy Conference (EPEC), 386–91. IEEE. https://doi.org/10.1109/EPEC56903.2022.9999738.
Ramirez Gonzalez, Miguel, et al. “Small-Signal Stability Assessment with Transfer Learning-Based Convolutional Neural Networks.” 2022 IEEE Electrical Power and Energy Conference (EPEC), IEEE, 2022, pp. 386–91, https://doi.org/10.1109/EPEC56903.2022.9999738.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.