Investigating machine learning capabilities for fault classification and fault region identification in onshore wind farm collectors (2025)
- Authors:
- USP affiliated authors: OLESKOVICZ, MARIO - EESC ; VIEIRA JÚNIOR, JOSÉ CARLOS DE MELO - EESC ; CUNHA, TALITA MITSUE ONOSE ARAUJO - EESC ; SILVA, MAURÍCIO PAVANI DA - EESC ; DAVI, MOISÉS JUNIOR BATISTA BORGES - EESC
- Unidade: EESC
- DOI: 10.1109/PowerTech59965.2025.11180434
- Assunto: ENGENHARIA ELÉTRICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway, NJ, USA
- Date published: 2025
- Conference titles: IEEE Kiel PowerTech - PowerTech 2025
- Status:
- Nenhuma versão em acesso aberto identificada
-
ABNT
DAVI, Moisés Junior Batista Borges et al. Investigating machine learning capabilities for fault classification and fault region identification in onshore wind farm collectors. 2025, Anais.. Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2025. Disponível em: http://dx.doi.org/10.1109/PowerTech59965.2025.11180434. Acesso em: 07 maio 2026. -
APA
Davi, M. J. B. B., Silva, M. P. da, Lopes, G. N., Cunha, T. M. O. A., Oleskovicz, M., & Vieira Júnior, J. C. de M. (2025). Investigating machine learning capabilities for fault classification and fault region identification in onshore wind farm collectors. In . Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1109/PowerTech59965.2025.11180434 -
NLM
Davi MJBB, Silva MP da, Lopes GN, Cunha TMOA, Oleskovicz M, Vieira Júnior JC de M. Investigating machine learning capabilities for fault classification and fault region identification in onshore wind farm collectors [Internet]. 2025 ;[citado 2026 maio 07 ] Available from: http://dx.doi.org/10.1109/PowerTech59965.2025.11180434 -
Vancouver
Davi MJBB, Silva MP da, Lopes GN, Cunha TMOA, Oleskovicz M, Vieira Júnior JC de M. Investigating machine learning capabilities for fault classification and fault region identification in onshore wind farm collectors [Internet]. 2025 ;[citado 2026 maio 07 ] Available from: http://dx.doi.org/10.1109/PowerTech59965.2025.11180434 - An improved directional protection element for onshore wind farm collector systems
- Enhancing power grid reliability: evaluating machine learning algorithms for fault classification in inverter-based generators interconnection lines
- Insights and recommendations for the assessment and design of fault diagnosis methods applied to modern distribution systems
- Exploring machine learning-based solutions for fault classification and region identification in onshore wind farm collector systems
- Exploring machine learning techniques for fault classification in wind farm collectors
- A feature selection and generalization analysis for high impedance fault classification based on Support Vector Machine
- Impacts of frequency estimation methods on the non-detection zone of anti-islanding protections in systems with inverter-based resources
- Insights and challenges on the protection of grid-forming converter interconnection lines
- Pseudo-incremental normalized quantity-based phase selection method for systems with conventional and inverter-based resources
- A novel high-sensitivity time-domain fault classifier applied to inverter-based resource interconnection lines
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| PROD_28053_SYSNO_3274983.... |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
