A novel hybrid machine learning classifier-based digital differential protection scheme for intertie zone of large-scale centralized DFIG-based wind farms
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 hav...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/87626/1/ABSTRACT.pdf |
| _version_ | 1796981868269142016 |
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| author | Rezaei, Nima Uddin, Mohammad Nasir Khairul Amin, Ifte Othman, Mohammad Lutfi Marsadek, Marayati Hasan, M. |
| author_facet | Rezaei, Nima Uddin, Mohammad Nasir Khairul Amin, Ifte Othman, Mohammad Lutfi Marsadek, Marayati Hasan, M. |
| author_sort | Rezaei, Nima |
| collection | UPM |
| description | 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. |
| first_indexed | 2024-03-06T10:43:56Z |
| format | Article |
| id | upm.eprints-87626 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:43:56Z |
| publishDate | 2020 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | upm.eprints-876262022-07-06T04:03:45Z http://psasir.upm.edu.my/id/eprint/87626/ A novel hybrid machine learning classifier-based digital differential protection scheme for intertie zone of large-scale centralized DFIG-based wind farms Rezaei, Nima Uddin, Mohammad Nasir Khairul Amin, Ifte Othman, Mohammad Lutfi Marsadek, Marayati Hasan, M. 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. Institute of Electrical and Electronics Engineers 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87626/1/ABSTRACT.pdf Rezaei, Nima and Uddin, Mohammad Nasir and Khairul Amin, Ifte and Othman, Mohammad Lutfi and Marsadek, Marayati and Hasan, M. (2020) A novel hybrid machine learning classifier-based digital differential protection scheme for intertie zone of large-scale centralized DFIG-based wind farms. IEEE Transactions on Industry Applications, 56 (4). 3453 - 3465. ISSN 0093-9994; ESSN: 1939-9367 https://ieeexplore.ieee.org/document/9079185 10.1109/TIA.2020.2990584 |
| spellingShingle | Rezaei, Nima Uddin, Mohammad Nasir Khairul Amin, Ifte Othman, Mohammad Lutfi Marsadek, Marayati Hasan, M. A novel hybrid machine learning classifier-based digital differential protection scheme for intertie zone of large-scale centralized DFIG-based wind farms |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/87626/1/ABSTRACT.pdf |
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