Artigao, E.; Sapena-Bano, A.; Honrubia-Escribano, A.; Martinez-Roman, J.; Puche-Panadero, R.; Gómez-Lázaro, E. (2019). Long-Term Operational Data Analysis of an In-Service Wind Turbine DFIG. IEEE Access. 7:17896-17906. https://doi.org/10.1109/ACCESS.2019.2895999
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/141971
Título:
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Long-Term Operational Data Analysis of an In-Service Wind Turbine DFIG
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Autor:
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Artigao, Estefania
Sapena-Bano, Angel
Honrubia-Escribano, Andrés
Martinez-Roman, Javier
Puche-Panadero, Rubén
Gómez-Lázaro, Emilio
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Entidad UPV:
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Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica
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Fecha difusión:
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Resumen:
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[EN] While wind turbine (WT) power capacities continue to increase and new offshore developments are being deployed, operation and maintenance (O&M) costs continue to rise, becoming the center of attention in the wind ...[+]
[EN] While wind turbine (WT) power capacities continue to increase and new offshore developments are being deployed, operation and maintenance (O&M) costs continue to rise, becoming the center of attention in the wind energy sector. The electric generator is among the top three contributors to failure rates and downtime of WTs, where the doubly fed induction generator (DFIG) is the dominant technology among variable speed WTs. Thus, the early detection of generator faults, which can be achieved through predictive maintenance, is vital in order to reduce O&M costs. The goal of this paper is to analyze a long-term monitoring campaign of an in-service WT equipped with a DFIG. A novel method named the harmonic order tracking analysis is used with two main objectives: first, to facilitate the data interpretation for non-trained maintenance personnel, and second, to reduce the amount of data that must be stored and transferred for the diagnosis of the DFIG. This method is applied and validated for the first time on an operating WT.
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Palabras clave:
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Doubly fed induction generators
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Harmonic analysis
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Stators
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Maintenance engineering
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Rotors
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Current measurement
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Wind turbines
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Condition monitoring
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Current signature analysis
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DFIG
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HOTA
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Wind turbine
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Derechos de uso:
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Reserva de todos los derechos
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Fuente:
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IEEE Access. (eissn:
2169-3536
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DOI:
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10.1109/ACCESS.2019.2895999
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Editorial:
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Institute of Electrical and Electronics Engineers
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Versión del editor:
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https://doi.org/10.1109/ACCESS.2019.2895999
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Código del Proyecto:
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info:eu-repo/grantAgreement/EC/H2020/642108/EU/Advanced Wind Energy Systems Operation and Maintenance Expertise/
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Descripción:
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(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
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Agradecimientos:
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This work was supported in part by the Agreement signed between the UCLM and the Council of Albacete to promote research in the
Campus of Albacete, and in part by the European Union Horizon 2020 Research and Innovation ...[+]
This work was supported in part by the Agreement signed between the UCLM and the Council of Albacete to promote research in the
Campus of Albacete, and in part by the European Union Horizon 2020 Research and Innovation Programme through the Marie
Sklodowska-Curie Grant (AWESOME Project) under Grant 642108. The authors would like to thank Ingeteam Power Technology S.A. UP Service, part of the AWESOME Project Consortium providing the wind turbine data.
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Tipo:
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Artículo
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