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Open phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECS

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dc.citedby0
dc.contributor.authorHamoudi Y.en_US
dc.contributor.authorAbdolrasol M.G.M.en_US
dc.contributor.authorAmimeur H.en_US
dc.contributor.authorHassaini F.en_US
dc.contributor.authorKer P.J.en_US
dc.contributor.authorUstun T.S.en_US
dc.contributor.authorid58420428800en_US
dc.contributor.authorid35796848700en_US
dc.contributor.authorid24528376900en_US
dc.contributor.authorid59484176200en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid43761679200en_US
dc.date.accessioned2025-03-03T07:46:14Z
dc.date.available2025-03-03T07:46:14Z
dc.date.issued2024
dc.description.abstractWind energy systems are often located in remote areas or offshore, making maintenance and repair both expensive and logistically challenging. Fault-tolerant systems can assist in minimizing the frequency and urgency of maintenance, ultimately reducing operational costs. This study aims to design a simple and efficient Open-Phase Fault Tolerant (OPFT) control for a wind power system (WPS) based on an asymmetric six-phase induction generator using Finite-Set Predictive Power Control (FS-PPC). The suggested technique involves three key steps. Firstly, the current harmonics in the (x, y) plane are analyzed to discover faults. Then, open-phase localization is achieved using the Support Vector Machine (SVM) with hyperparameter Bayesian Optimization (BO). Finally, the phase that forms 90 degrees with the faulty phase is opened to restore the system?s stability. Importantly, this approach does not require reconfiguring the control algorithm while preserving the system?s effective performance. Simulation results demonstrate the effectiveness of the OPFT-SVM-PPC control strategy in preserving control over the machine while ensuring high energy quality for the grid with a THD of 2.71%. By implementing this fault tolerance control, the system can operate reliably and deliver high-quality power, even in the presence of open-phase faults. ? The Author(s) 2024.en_US
dc.description.natureArticle in pressen_US
dc.identifier.doi10.1177/01445987241291180
dc.identifier.scopus2-s2.0-85212843047
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85212843047&doi=10.1177%2f01445987241291180&partnerID=40&md5=112800e994367c6423214e5c668c225d
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36972
dc.publisherSAGE Publications Inc.en_US
dc.relation.ispartofAll Open Access; Gold Open Access
dc.sourceScopus
dc.sourcetitleEnergy Exploration and Exploitation
dc.subjectDC generators
dc.subjectFault tolerance
dc.subjectOutages
dc.subjectPredictive control systems
dc.subjectSpeed regulators
dc.subjectVector control (Electric machinery)
dc.subjectWindmill
dc.subjectAsymmetric six-phase induction generator
dc.subjectBayesian optimization
dc.subjectCurrent harmonics
dc.subjectEnergy conversion systems
dc.subjectFault tolerance control
dc.subjectFaults detection
dc.subjectHyper-parameter
dc.subjectHyper-parameter bayesian optimization
dc.subjectOpen phase
dc.subjectOpen-phase fault tolerance control
dc.subjectPhase faults
dc.subjectPower
dc.subjectPredictive power controls
dc.subjectSix-phase
dc.subjectSupport vectors machine
dc.subjectWind energy conversion
dc.subjectWind energy conversion system
dc.subjectAsynchronous generators
dc.titleOpen phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECSen_US
dc.typeArticleen_US
dspace.entity.typePublication
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