The full text of this article
Model identification and analysis of small-power wind turbines
by Magdi Sadek Mahmoud; Amin-ud-din Qureshi
International Journal of Modelling, Identification and Control (IJMIC), Vol. 17, No. 1, 2012
Abstract: In this paper, we present complete results for model identification methods and analysis of a small-power wind turbine in the prospect of designing efficient controllers for obtaining maximum electrical power output and devising the fault detection and diagnosis schemes. The system has been identified using three different model structures: ARX, ARMAX and state-space models. The techniques used for their estimation are least-squares, prediction-error and subspace-based N4SID methods, respectively. Identification and validations are performed on actual measurements of a wind turbine installed at West Michigan University (WMU). It is concluded that the identified ARX model gives the best results in terms of minimum value of Akaike's information criterion (AIC) and maximum percentage of fitness when validation tests are performed.
Online publication date: Sun, 19-Aug-2012
is only available to individual subscribers or to users at subscribing institutions.
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 Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and 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 firstname.lastname@example.org