On the use of high-frequency SCADA data for improved wind turbine performance monitoring

E Gonzales, B Stephen, D Infield, J Melero

Research output: Contribution to journalArticle

14 Citations (Scopus)
142 Downloads (Pure)

Abstract

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 eective performance monitoring tool. The benets 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, eectively 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.
Original languageEnglish
Article number012009
Number of pages14
JournalJournal of Physics: Conference Series
Volume926
DOIs
Publication statusPublished - 23 Nov 2017
EventWindEurope Conference & Exhibition 2017 - Amsterdam, Netherlands
Duration: 28 Nov 201730 Nov 2017
https://windeurope.org/confex2017/

Keywords

  • Operation & Maintenance
  • Wind Turbine
  • Power Curve
  • Performance Monitoring
  • SCADA
  • High-frequency data
  • Fault Detection

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