Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/94315
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dc.contributorDepartment of Electrical Engineering-
dc.creatorAbusalah, A-
dc.creatorSaad, O-
dc.creatorMahseredjian, J-
dc.creatorKaraagac, U-
dc.creatorKocar, I-
dc.date.accessioned2022-08-11T02:01:50Z-
dc.date.available2022-08-11T02:01:50Z-
dc.identifier.urihttp://hdl.handle.net/10397/94315-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/en_US
dc.rightsThe following publication Abusalah, A., Saad, O., Mahseredjian, J., Karaagac, U., & Kocar, I. (2020). Accelerated Sparse Matrix-Based Computation of Electromagnetic Transients. IEEE Open Access Journal of Power and Energy, 7, 13-21 is available at https://doi.org/10.1109/OAJPE.2019.2952776en_US
dc.subjectElectromagnetic transientsen_US
dc.subjectKLUen_US
dc.subjectModified-augmented-nodal-analysisen_US
dc.subjectParallelizationen_US
dc.subjectSparse matrix solveren_US
dc.titleAccelerated sparse matrix-based computation of electromagnetic transientsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage13-
dc.identifier.epage21-
dc.identifier.volume7-
dc.identifier.doi10.1109/OAJPE.2019.2952776-
dcterms.abstractThis paper is related to research on parallelization methods for the simulation of electromagnetic transients (EMTs). It presents an automatic parallelization approach based on the solution of sparse matrices resulting from the formulation of network equations. Modified-augmented-nodal analysis is used to formulate network equations. The selected sparse matrix solver is parallelized and adapted to improve performance by pivot validity testing and partial refactorization. Refactorization is needed when dealing with varying topology networks and nonlinear models. The EMT solver employs a fully iterative method for nonlinear functions. Conventional computer CPU-based parallelization is achieved and does not require any user intervention for given arbitrary network topologies. The presented approach is tested on real networks with complex models, including nonlinearities and power-electronics converters for wind generator applications.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE open access journal of power and energy, 2020, v. 7, p. 13-21-
dcterms.isPartOfIEEE open access journal of power and energy-
dcterms.issued2020-
dc.identifier.scopus2-s2.0-85102815182-
dc.identifier.eissn2687-7910-
dc.description.validate202207 bckw-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera1479en_US
dc.identifier.SubFormID45104en_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNatural Sciences and Engineering Research Council of Canadaen_US
dc.description.pubStatusPublisheden_US
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