Complete ML-based methodology for fault classification in onshore wind farm collector networks (2025)
- Authors:
- USP affiliated authors: OLESKOVICZ, MARIO - EESC ; OLIVEIRA, EMANUEL PERCINIO GONCALVES DE - EESC E ICMC ; DAVI, MOISÉS JUNIOR BATISTA BORGES - EESC
- Unidades: EESC; EESC E ICMC
- DOI: 10.1109/ACCESS.2025.3626243
- Subjects: APRENDIZADO COMPUTACIONAL; ENERGIA EÓLICA; FONTES RENOVÁVEIS DE ENERGIA; FALHAS COMPUTACIONAIS; INTERCEPTORES
- Keywords: Fault classification; inverter-based resources; renewable generation; wind farm collectors
- Agências de fomento:
- Language: Inglês
- Objetivos de Desenvolvimento Sustentável (ODS):
07. Energia limpa e acessível
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway, NJ
- Date published: 2025
- Source:
- Título: IEEE Access
- Volume/Número/Paginação/Ano: v. 13, p. 184409-184418, 2025
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
OLIVEIRA, Emanuel Percinio Gonçalves de e DAVI, Moisés Junior Batista Borges e OLESKOVICZ, Mario. Complete ML-based methodology for fault classification in onshore wind farm collector networks. IEEE Access, v. 13, p. 184409-184418, 2025Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2025.3626243. Acesso em: 28 jan. 2026. -
APA
Oliveira, E. P. G. de, Davi, M. J. B. B., & Oleskovicz, M. (2025). Complete ML-based methodology for fault classification in onshore wind farm collector networks. IEEE Access, 13, 184409-184418. doi:10.1109/ACCESS.2025.3626243 -
NLM
Oliveira EPG de, Davi MJBB, Oleskovicz M. Complete ML-based methodology for fault classification in onshore wind farm collector networks [Internet]. IEEE Access. 2025 ; 13 184409-184418.[citado 2026 jan. 28 ] Available from: https://doi.org/10.1109/ACCESS.2025.3626243 -
Vancouver
Oliveira EPG de, Davi MJBB, Oleskovicz M. Complete ML-based methodology for fault classification in onshore wind farm collector networks [Internet]. IEEE Access. 2025 ; 13 184409-184418.[citado 2026 jan. 28 ] Available from: https://doi.org/10.1109/ACCESS.2025.3626243 - Exploring machine learning-based solutions for fault classification and region identification in onshore wind farm collector systems
- Exploring the potential of a machine learning-based methodology for fault classification in inverter-based resource interconnection lines
- An impedance-multi-method-based fault location methodology for transmission lines connected to inverter-based resources
- Assessment of traveling wave-based functions in inverter-based resource interconnecting lines
- Classificação de faltas em linhas de interconexão de gerações baseadas em inversores: desvendando o potencial dos métodos de machine learning
- Parametric analysis of phasor-based fault location methods applied to inverter-based resource interconnection lines
- A case study-based review of the impacts of inverter-interfaced wind power plants on distance protections
- Importance of EMT-type simulations for protection studies in power systems with inverter-based resources
- Impacts of advances in standards for inverter-based resources controls on distance protection
- Impacts of inverter-interfaced wind power plants in the phase-selection and directional protection functions
Informações sobre o DOI: 10.1109/ACCESS.2025.3626243 (Fonte: oaDOI API)
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