Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/62082
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dc.contributor.authorHussain, Tanveeren
dc.contributor.authorGallego-Calderon, Juanen
dc.contributor.authorAlam, S M Shafiulen
dc.date.accessioned2024-08-10T08:58:41Z-
dc.date.available2024-08-10T08:58:41Z-
dc.date.issued2023-
dc.identifier.citationJournal of Physics: Conference Series, v.2626, p. 1-10en
dc.identifier.issn1742-6596en
dc.identifier.issn1742-6588en
dc.identifier.urihttps://hdl.handle.net/1959.11/62082-
dc.description.abstract<p>The increasing integration of renewable energy resources in evolving bulk power system (BPS) is impacting the system inertia. Type-5 wind turbine generation has the potential to behave like a traditional synchronous generator and can help mitigate the impact on system inertia. A hydraulic torque converter (TC) and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine unit. A high fidelity model of Type-5 wind turbine drivetrain is not openly and widely available for grid integration and transient stability studies. This hinders appropriate assessment of Type-5 wind power plant's contribution to bulk grid resilience. This work develops and validates a TC model based on those generally used in automobile's transmission system. Moreover, the concept of torsional coupling is leveraged to integrate the TC and gearbox system dynamics. The entire integrated model will be open sourced and publicly available for grid integration studies.<p>en
dc.languageenen
dc.publisherInstitute of Physics Publishing Ltden
dc.relation.ispartofJournal of Physics: Conference Seriesen
dc.rightsAttribution 3.0 Unported Deed*
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/*
dc.titleOpen Source High Fidelity Modeling of a Type-5 Wind Turbine Drivetrainen
dc.typeConference Publicationen
dc.relation.conferenceEERA 2023: European Research Association - DeepWind Conferenceen
dc.identifier.doi10.1088/1742-6596/2626/1/012018en
dcterms.accessRightsUNE Greenen
local.contributor.firstnameTanveeren
local.contributor.firstnameJuanen
local.contributor.firstnameS M Shafiulen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailthussai3@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference18th - 20th January, 2023en
local.conference.placeTrondheim, Norwayen
local.publisher.placeUnited Kingdomen
local.identifier.runningnumber012018en
local.format.startpage1en
local.format.endpage10en
local.peerreviewedYesen
local.identifier.volume2626en
local.access.fulltextYesen
local.contributor.lastnameHussainen
local.contributor.lastnameGallego-Calderonen
local.contributor.lastnameAlamen
dc.identifier.staffune-id:thussai3en
local.profile.orcid0000-0003-1973-4584en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/62082en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleOpen Source High Fidelity Modeling of a Type-5 Wind Turbine Drivetrainen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsEERA 2023: European Research Association - DeepWind Conference, Trondheim, Norway, 18th - 20th January, 2023en
local.search.authorHussain, Tanveeren
local.search.authorGallego-Calderon, Juanen
local.search.authorAlam, S M Shafiulen
local.open.fileurlhttps://rune.une.edu.au/web/retrieve/40f0442d-9321-466b-8837-614722740d17en
local.uneassociationNoen
local.atsiresearchNoen
local.conference.venueRadisson Blu Royal Garden Hotelen
local.sensitive.culturalNoen
local.year.published2023en
local.fileurl.openhttps://rune.une.edu.au/web/retrieve/40f0442d-9321-466b-8837-614722740d17en
local.fileurl.openpublishedhttps://rune.une.edu.au/web/retrieve/40f0442d-9321-466b-8837-614722740d17en
local.subject.for20203407 Theoretical and computational chemistryen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-08-23en
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School of Science and Technology
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