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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.
|Number of pages||10|
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 3 Oct 2016|
|Event||The Science of Making Torque from Wind 2016 - Technische Universität München (TUM), Campus Garching, MUNICH, Germany|
Duration: 5 Oct 2016 → 7 Oct 2016
Conference number: 6
- wind gusts
- anomaly detection
FingerprintDive into the research topics of 'Gusts detection in a horizontal wind turbine by monitoring of innovations error of an extended Kalman filter'. Together they form a unique fingerprint.
- 2 Finished
- 1 Paper
Hur, S., Recalde, L. F. & Leithead, W. E., 19 Nov 2015. 10 p.
Research output: Contribution to conference › Paper › peer-review