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

The Science of Making Torque from Wind

Recalde, L.F.^1 ; Hur, S.^1 ; Leithead, W.E.^1

Wind Energy and Control, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow

G1 1RD, United Kingdom^1

关键词: Detection scheme;    Discrete Kalman filters;    Extreme winds;    Goodness of fit;    Horizontal winds;    Maximum likelihood ratios;    Model-based OPC;    Wind anomalies;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/753/5/052010/pdf
DOI  :  10.1088/1742-6596/753/5/052010

来源: IOP

【 摘 要 】

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.