# WIND TURBINE ROTOR ACCELERATION: IDENTIFICATION USING GAUSSIAN REGRESSION

### W. E. Leithead, Yunong Zhang, Kian Seng Neo

#### 2005

#### Abstract

Gaussian processes prior model methods for data analysis are applied to wind turbine time series data to identify both rotor speed and rotor acceleration from a poor measurement of rotor speed. In so doing, two issues are addressed. Firstly, the rotor speed is extracted from a combined rotor speed and generator speed measurement. A novel adaptation of Gaussian process regression based on two independent processes rather than a single process is presented. Secondly, efficient algorithms for the manipulation of large matrices are required. The Toeplitz nature of the matrices is exploited to derive novel fast algorithms for the Gaussian process methodology that are memory efficient.

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#### Paper Citation

#### in Harvard Style

E. Leithead W., Zhang Y. and Seng Neo K. (2005). **WIND TURBINE ROTOR ACCELERATION: IDENTIFICATION USING GAUSSIAN REGRESSION** . In *Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,* ISBN 972-8865-31-7, pages 84-91. DOI: 10.5220/0001179300840091

#### in Bibtex Style

@conference{icinco05,

author={W. E. Leithead and Yunong Zhang and Kian Seng Neo},

title={WIND TURBINE ROTOR ACCELERATION: IDENTIFICATION USING GAUSSIAN REGRESSION},

booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},

year={2005},

pages={84-91},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0001179300840091},

isbn={972-8865-31-7},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,

TI - WIND TURBINE ROTOR ACCELERATION: IDENTIFICATION USING GAUSSIAN REGRESSION

SN - 972-8865-31-7

AU - E. Leithead W.

AU - Zhang Y.

AU - Seng Neo K.

PY - 2005

SP - 84

EP - 91

DO - 10.5220/0001179300840091