Wind turbine rotor acceleration: identification using Gaussian regression

W.E. Leithead, S. Dominguez

Research output: Contribution to conferencePaper

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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 ratherthan 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.
Original languageEnglish
Publication statusPublished - 2005
EventProceedings of International Conference on Informatics in Control, Automation - Barcelona, Spain
Duration: 14 Sep 200517 Sep 2005

Conference

ConferenceProceedings of International Conference on Informatics in Control, Automation
CountrySpain
CityBarcelona
Period14/09/0517/09/05

Keywords

  • gaussian regression
  • wind turbines

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    Leithead, W. E., & Dominguez, S. (2005). Wind turbine rotor acceleration: identification using Gaussian regression. Paper presented at Proceedings of International Conference on Informatics in Control, Automation, Barcelona, Spain.