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

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)
Exportado de SIDERAL (2019-04-26-09:27:24)

Este artículo se encuentra en las siguientes colecciones:

 Notice créée le 2017-12-13, modifiée le 2019-04-26

Versión publicada:
Évaluer ce document:

Rate this document:
(Pas encore évalué)