On the use of high-frequency SCADA data for improved wind turbine performance monitoring
Financiación H2020 / H2020 Funds
Resumen: SCADA-based condition monitoring of wind turbines facilitates the move from costly corrective repairs towards more proactive maintenance strategies. In this work, we advocate the use of high-frequency SCADA data and quantile regression to build a cost effective performance monitoring tool. The benefits of the approach are demonstrated through the comparison between state-of-the-art deterministic power curve modelling techniques and the suggested probabilistic model. Detection capabilities are compared for low and high-frequency SCADA data, providing evidence for monitoring at higher resolutions. Operational data from healthy and faulty turbines are used to provide a practical example of usage with the proposed tool, effectively achieving the detection of an incipient gearbox malfunction at a time horizon of more than one month prior to the actual occurrence of the failure.
Idioma: Inglés
DOI: 10.1088/1742-6596/926/1/012009
Año: 2017
Publicado en: Journal of physics. Conference series 926 (2017), 012009 [14 pp]
ISSN: 1742-6588

Factor impacto SCIMAGO: 0.241 - Physics and Astronomy (miscellaneous) (Q3)

Financiación: info:eu-repo/grantAgreement/EC/H2020/642108/EU/Advanced Wind Energy Systems Operation and Maintenance Expertise/AWESOME
Tipo y forma: Article (Published version)
Área (Departamento): Área Ingeniería Eléctrica (Dpto. Ingeniería Eléctrica)

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 Record created 2017-12-13, last modified 2019-07-09

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