Monitoring Wind Turbine Loading Using Power Converter Signals

Rieg, C.A.; Smith, C.J.; Crabtree, C.J.

doi:10.1088/1742-6596/749/1/012018

Monitoring Wind Turbine Loading Using Power Converter Signals

Rieg, C.A.; Smith, C.J.; Crabtree, C.J.

Authors

C.A. Rieg

C.J. Smith

Professor Christopher Crabtree c.j.crabtree@durham.ac.uk
Professor

Abstract

The ability to detect faults and predict loads on a wind turbine drivetrain's mechanical components cost-effectively is critical to making the cost of wind energy competitive. In order to investigate whether this is possible using the readily available power converter current signals, an existing permanent magnet synchronous generator based wind energy conversion system computer model was modified to include a grid-side converter (GSC) for an improved converter model and a gearbox. The GSC maintains a constant DC link voltage via vector control. The gearbox was modelled as a 3-mass model to allow faults to be included. Gusts and gearbox faults were introduced to investigate the ability of the machine side converter (MSC) current (I q) to detect and quantify loads on the mechanical components. In this model, gearbox faults were not detectable in the I q signal due to shaft stiffness and damping interaction. However, a model that predicts the load change on mechanical wind turbine components using I q was developed and verified using synthetic and real wind data.

Citation

Rieg, C., Smith, C., & Crabtree, C. (2016). Monitoring Wind Turbine Loading Using Power Converter Signals. Journal of Physics: Conference Series, 749(1), Article 012018. https://doi.org/10.1088/1742-6596/749/1/012018

Journal Article Type	Article
Acceptance Date	Aug 10, 2016
Online Publication Date	Sep 14, 2016
Publication Date	Sep 14, 2016
Deposit Date	Aug 11, 2016
Publicly Available Date	Aug 15, 2016
Journal	Journal of Physics: Conference Series
Print ISSN	1742-6588
Electronic ISSN	1742-6596
Publisher	IOP Publishing
Peer Reviewed	Peer Reviewed
Volume	749
Issue	1
Article Number	012018
DOI	https://doi.org/10.1088/1742-6596/749/1/012018

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