Data-driven modelling, control, and fault detection of wind turbine systems
by Young-Man Kim
International Journal of System Control and Information Processing (IJSCIP), Vol. 1, No. 3, 2014

Abstract: In this paper, data-driven system modelling, control, and fault detection technique for wind turbine systems are researched. The developed algorithm is to recursively update system parameters using predictor-based system identification (SID) technique. Updated system parameters are used to design subspace predictive controller for wind turbine systems with constraint on pitch angle and generator torque. The usefulness of this application is highlighted through simulation on a benchmark example, 5 MW NREL/Upwind reference turbine. It shows that developed algorithm which streamlines controller design process from identification to fault detection is useful for making wind turbine systems being tolerant to faults.

Online publication date: Thu, 06-Mar-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of System Control and Information Processing (IJSCIP):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com