An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems
This paper is motivated by the growing penetration of renewable power plants in electrical systems worldwide and the scarcity of studies evaluating fault detection, classification, and localization tasks when applied within wind farms, i.e., their collector systems. In this context, the performance...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10770198/ |
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| author | Moises J. B. B. Davi Mario Oleskovicz Felipe V. Lopes |
| author_facet | Moises J. B. B. Davi Mario Oleskovicz Felipe V. Lopes |
| author_sort | Moises J. B. B. Davi |
| collection | DOAJ |
| description | This paper is motivated by the growing penetration of renewable power plants in electrical systems worldwide and the scarcity of studies evaluating fault detection, classification, and localization tasks when applied within wind farms, i.e., their collector systems. In this context, the performance of existing fault detection and classification methods is assessed using single or multiple measurement points based on a measurement management approach presented in this work. For the studies, a system with a realistic topology of onshore wind farm collectors is modeled in the PSCAD software, and several fault scenarios varying fault type, resistance, inception angle, and location are represented, besides variations in the wind farm’s generation level. As the main contributions and novelties to the state-of-the-art, this paper provides: 1) pioneering insights about atypical faulty phase current behaviors in wind farm collector systems, 2) recommendations about conventional fault detection and classification methods that are most suitable for application in onshore wind farm collectors, and 3) an integrated methodology for fault detection, fault classification, and fault region identification in onshore wind farm collector systems. |
| format | Article |
| id | doaj-art-84d7c3d141d64ce3ac07d690bb44d020 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-84d7c3d141d64ce3ac07d690bb44d0202024-12-10T00:02:27ZengIEEEIEEE Access2169-35362024-01-011217951617952810.1109/ACCESS.2024.350857510770198An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector SystemsMoises J. B. B. Davi0https://orcid.org/0000-0002-9383-4615Mario Oleskovicz1https://orcid.org/0000-0002-0387-8930Felipe V. Lopes2https://orcid.org/0000-0001-6465-8045Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, BrazilDepartment of Electrical and Computer Engineering, University of São Paulo, São Carlos, BrazilDepartment of Electrical Engineering, Federal University of Paraíba, João Pessoa, BrazilThis paper is motivated by the growing penetration of renewable power plants in electrical systems worldwide and the scarcity of studies evaluating fault detection, classification, and localization tasks when applied within wind farms, i.e., their collector systems. In this context, the performance of existing fault detection and classification methods is assessed using single or multiple measurement points based on a measurement management approach presented in this work. For the studies, a system with a realistic topology of onshore wind farm collectors is modeled in the PSCAD software, and several fault scenarios varying fault type, resistance, inception angle, and location are represented, besides variations in the wind farm’s generation level. As the main contributions and novelties to the state-of-the-art, this paper provides: 1) pioneering insights about atypical faulty phase current behaviors in wind farm collector systems, 2) recommendations about conventional fault detection and classification methods that are most suitable for application in onshore wind farm collectors, and 3) an integrated methodology for fault detection, fault classification, and fault region identification in onshore wind farm collector systems.https://ieeexplore.ieee.org/document/10770198/Fault classificationfault detectionfault section identificationinverter-based resourcesrenewable generationwind farm collectors |
| spellingShingle | Moises J. B. B. Davi Mario Oleskovicz Felipe V. Lopes An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems IEEE Access Fault classification fault detection fault section identification inverter-based resources renewable generation wind farm collectors |
| title | An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems |
| title_full | An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems |
| title_fullStr | An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems |
| title_full_unstemmed | An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems |
| title_short | An Integrated Fault Detection, Classification, and Region Identification Methodology Applied to Onshore Wind Farm Collector Systems |
| title_sort | integrated fault detection classification and region identification methodology applied to onshore wind farm collector systems |
| topic | Fault classification fault detection fault section identification inverter-based resources renewable generation wind farm collectors |
| url | https://ieeexplore.ieee.org/document/10770198/ |
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