Gusts detection in a horizontal wind turbine by monitoring of innovations error of an extended Kalman filter

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Abstract

This paper presents a novel model-based detection scheme capable of detecting and diagnosing gusts. Detection is achieved by monitoring the innovations error (i.e., the difference between the estimated and measured outputs) of an extended discrete Kalman filter. It is designed to trigger a detection/confirmation alarm in the presence of wind anomalies. Simulation results are presented to demonstrate that both operating and coherent extreme wind gusts can successfully be detected. The wind anomaly is identified in magnitude and shape through maximum likelihood ratio and goodness of fit, respectively. The detector is capable of isolating extreme wind gusts before the turbine over speeds.
Original languageEnglish
Article number052010
Number of pages10
JournalJournal of Physics: Conference Series
Volume753
DOIs
Publication statusPublished - 3 Oct 2016
EventThe Science of Making Torque from Wind 2016 - Technische Universität München (TUM), Campus Garching, MUNICH, Germany
Duration: 5 Oct 20167 Oct 2016
Conference number: 6
https://torque2016.conferenceseries.iop.org/

Keywords

  • wind gusts
  • anomaly detection
  • control

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  • Projects

    WINDTRUST

    Leithead, B., Katebi, R., Hur, S. H. & Recalde Camacho, L.

    European Commission - FP7 - Cooperation only

    1/09/1331/08/16

    Project: Research

    Research Output

    Anomaly detection of a horizontal wind turbine using an extended Kalman filter

    Hur, S., Recalde, L. F. & Leithead, W. E., 19 Nov 2015. 10 p.

    Research output: Contribution to conferencePaper

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