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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

Asynchronous 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;...

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Main Authors: Rezaei N., Uddin M.N., Amin I.K., Othman M.L., Marsadek M.B., Hasan M.M.
Other Authors: 57216077273
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-253962023-05-29T16:08:55Z A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms Rezaei N. Uddin M.N. Amin I.K. Othman M.L. Marsadek M.B. Hasan M.M. 57216077273 55663372800 10040907100 55153333400 26423183000 57220989460 Asynchronous 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 networks The 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. Final 2023-05-29T08:08:55Z 2023-05-29T08:08:55Z 2020 Article 10.1109/TIA.2020.2990584 2-s2.0-85089197866 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089197866&doi=10.1109%2fTIA.2020.2990584&partnerID=40&md5=efcb93647011a70f9ce4109dd86617bc https://irepository.uniten.edu.my/handle/123456789/25396 56 4 9079185 3453 3465 All Open Access, Green Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Asynchronous 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 networks
author2 57216077273
author_facet 57216077273
Rezaei N.
Uddin M.N.
Amin I.K.
Othman M.L.
Marsadek M.B.
Hasan M.M.
format Article
author Rezaei N.
Uddin M.N.
Amin I.K.
Othman M.L.
Marsadek M.B.
Hasan M.M.
spellingShingle Rezaei N.
Uddin M.N.
Amin I.K.
Othman M.L.
Marsadek M.B.
Hasan M.M.
A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms
author_sort Rezaei N.
title A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms
title_short A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms
title_full A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms
title_fullStr A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms
title_full_unstemmed A Novel Hybrid Machine Learning Classifier-Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG-Based Wind Farms
title_sort novel hybrid machine learning classifier-based digital differential protection scheme for intertie zone of large-scale centralized dfig-based wind farms
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806426005987917824
score 13.214268

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