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A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms

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dc.citedby17
dc.contributor.authorRezaei N.en_US
dc.contributor.authorUddin M.N.en_US
dc.contributor.authorAmin I.K.en_US
dc.contributor.authorOthman M.L.en_US
dc.contributor.authorMarsadek M.B.en_US
dc.contributor.authorHasan M.M.en_US
dc.contributor.authorid57216077273en_US
dc.contributor.authorid55663372800en_US
dc.contributor.authorid10040907100en_US
dc.contributor.authorid55153333400en_US
dc.contributor.authorid26423183000en_US
dc.contributor.authorid57220989460en_US
dc.date.accessioned2023-05-29T08:08:55Z
dc.date.available2023-05-29T08:08:55Z
dc.date.issued2020
dc.descriptionAsynchronous generators; Clustering algorithms; E-learning; Electric equipment protection; Electric fault currents; Electric power system interconnection; Electric power system protection; Electric transformers; Electric utilities; Learning systems; Storms; Support vector machines; Wind; Wind power; Differential protection; Doubly fed induction generators; Dynamic behaviors; Hybrid machine learning; Impedance measurement; Laboratory environment; Renewable energies; Supervised machine learning; Electric power transmission networksen_US
dc.description.abstractThe protection of intertie zone between wind farm and grid line is critical for stable and safe operation of both the grid line and wind farm in the event of fault within or outside the intertie zone. As a reliable source of renewable energy doubly fed induction generator (DFIG)-based wind farms have been increasingly integrated to the power grid over the last two decades. Nowadays with the enormous penetration of large-scale DFIG wind farms, the commonly used distance relays are no longer reliable due to their incapability of providing accurate impedance measurement during internal and external faults. Thus, it results in maloperation, false tripping, and/or delayed operation. Therefore, in this article a digital differential-based protective relay (DBPR) scheme is designed and developed to provide reliable protection for wind farm intertie zone. Additionally, a new Bayesian-based optimized support vector machine (SVM), as a supervised machine learning classifier approach, is developed to take into account both the dynamic behaviors of wind speed and the current measured by the current transformers. Thus, the proposed hybrid SVM-DBPR scheme can distinguish among the normal operation, internal and external faults correctly that helps to avoid any false tripping. In a laboratory environment the proposed DBPR is implemented in realtime using FPGA DE2-115 board equipped with Cyclone IV-E device (EP4CE115F29C7). It is found from both simulation and experimental results that the proposed hybrid SVM-DBPR is able to provide reliable, efficient, and robust protection for the intertie zone of wind farms with 97.5% accuracy rate. � 1972-2012 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9079185
dc.identifier.doi10.1109/TIA.2020.2990584
dc.identifier.epage3465
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85089197866
dc.identifier.spage3453
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85089197866&doi=10.1109%2fTIA.2020.2990584&partnerID=40&md5=efcb93647011a70f9ce4109dd86617bc
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25396
dc.identifier.volume56
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Green
dc.sourceScopus
dc.sourcetitleIEEE Transactions on Industry Applications
dc.titleA Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farmsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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