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dc.contributor.authorGonzalez-Longatt, Francisco
dc.contributor.authorMontalvo, Martha Nohemi
dc.contributor.authorAndrade, Manuel A.
dc.contributor.authorVazquez, Ernesto
dc.contributor.authorChamorro, Harold R.
dc.contributor.authorSood, Vijay K.
dc.date.accessioned2021-08-05T10:09:51Z
dc.date.available2021-08-05T10:09:51Z
dc.date.created2021-01-27T21:31:28Z
dc.date.issued2020
dc.identifier.citationGonzalez-Longatt, F., Acosta, M. N., Andrade, M., Vazquez, E., Chamorro, H. R., & Sood, V. K. (2020). Multi-Core Platform of Admittance Matrix Formation of Power Systems: Computational Time Assessment. In 2020 IEEE Electric Power and Energy Conference (EPEC)en_US
dc.identifier.isbn978-1-7281-6489-2
dc.identifier.urihttps://hdl.handle.net/11250/2766445
dc.description.abstractThis paper presents a comparison of computational time required to build the admittance matrix of five test systems (ranging from 200 to 70,000 nodes) considering two formation approaches: element-by-element and matrix approach. The algorithms have been implemented in MATLAB ™ and tested in four multi-core platforms. Implementations include sparse and dense matrix representation and parallel/non-parallel computing. Results show the matrix approach considering sparse representation and parallel computing is the best approach in computing time.en_US
dc.language.isoengen_US
dc.relation.ispartofProceedings of the Electric Power and Energy Conference (EPEC), 2020 IEEE
dc.titleMulti-Core Platform of Admittance Matrix Formation of Power Systems: Computational Time Assessmenten_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2020 IEEE.en_US
dc.source.journal2020 IEEE Electric Power and Energy Conference (EPEC)en_US
dc.identifier.doihttps://doi.org/10.1109/EPEC48502.2020.9320060
dc.identifier.cristin1880776
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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