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dc.contributor.authorBouzekri, Amina
dc.contributor.authorAllaoui, Tayeb
dc.contributor.authorDenai, Mouloud
dc.date.accessioned2018-02-07T17:42:20Z
dc.date.available2018-02-07T17:42:20Z
dc.date.issued2017-02-03
dc.identifier.citationBouzekri , A , Allaoui , T & Denai , M 2017 , ' Intelligent Open Switch Fault Detection for Power Converter in Wind Energy System ' , Applied Artifical Intelligence , vol. 30 , no. 9 , pp. 886-898 . https://doi.org/10.1080/08839514.2016.1277294
dc.identifier.issn0883-9514
dc.identifier.otherPURE: 11149556
dc.identifier.otherPURE UUID: efe17943-79b7-4ad2-8bf2-2a0fb4fd54d3
dc.identifier.otherScopus: 85011554743
dc.identifier.urihttp://hdl.handle.net/2299/19741
dc.descriptionThis is an Accepted Manuscript of an article published by Taylor & Francis in Applied Artificial Intelligence, Vol. 30 (9): 886-898 on 3 February 2017. The Version of Record is available online at: http://www.tandfonline.com/doi/full/10.1080/08839514.2016.1277294.
dc.description.abstractThis paper proposes a simple and fast fuzzy logic-based open switch fault detection method for rotor side converter (RSC) in doubly fed induction generator (DFIG) wind turbine system. In the proposed scheme, only the mean values of the three-phase rotor currents are used to identify the power switch in which the open-circuit fault has occurred. The wind energy conversion system model developed for the design and evaluation of the proposed fault detection technique including three principal controls. the first control ensure the regulation of the electromagnetic torque and the reactive stator power (named Rotor Side Converter (RSC) control), the second regulates the DC-link voltage at the desired level (named Grid Side Converter (GSC) control) and in order to achieve maximum power at any wind speed condition a maximum power point tracking (MPPT) control strategy has been used. The simulation model was developed in MATLAB/Simulink environment. The results show that the proposed fault detection scheme is able to rapidly and effectively identify open switch faults among other fault types in a time less than one period.en
dc.format.extent13
dc.language.isoeng
dc.relation.ispartofApplied Artifical Intelligence
dc.rightsEmbargoed
dc.titleIntelligent Open Switch Fault Detection for Power Converter in Wind Energy Systemen
dc.contributor.institutionSchool of Engineering and Technology
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionSmart Electronics Devices and Networks
dc.description.statusPeer reviewed
dc.date.embargoedUntil2018-02-03
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2017-02-03
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1080/08839514.2016.1277294
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeEmbargoed


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