Experimental Modelling of a Floating Offshore Wind Turbine

Christian Lindquist; Patrick Nørgaard Nielsen; Rikke Pedersen; Mohsen N. Soltani

doi:10.1109/MMAR.2018.8485979

Experimental Modelling of a Floating Offshore Wind Turbine

Christian Lindquist, Patrick Nørgaard Nielsen, Rikke Pedersen, Mohsen N. Soltani

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

1 Citation (Scopus)

Abstract

Leading wind turbine manufacturers are increasinglylooking at the possibilities of sending offshore wind turbinesto deep seas. This can be done using a Floating Offshore WindTurbine (FOWT). Therefore FOWT is an interesting and timelyfield of study. The aim of the paper is to use System Identification(SI) to make a data-driven-based model for the FOWT system,located in Offshore Wind & Wave Laboratory at Aalborg University.This is achieved by conducting experiments and analyzingthe data. SI is used to analyze data from the experiments andobtain different models. These models are then evaluated basedon the fit, the frequency response, autocorrelation and crosscorrelation.Eventually, an AutoRegressive Moving Average andExtra input (ARMAX) model is shown to be the most accurateamongst the analyzed models.

Original language	English
Title of host publication	Proceedings of the 23rd International Conference on Methods and Models in Automation and Robotics, MMAR
Number of pages	6
Publisher	IEEE Press
Publication date	Aug 2018
Pages	327-332
Article number	8485979
ISBN (Electronic)	978-1-5386-4325-9
DOIs	https://doi.org/10.1109/MMAR.2018.8485979
Publication status	Published - Aug 2018
Event	23rd International Conference on Methods & Models in Automation & Robotics - Amber Baltic Hotel, Miedzyzdroje, Poland Duration: 27 Aug 2018 → 30 Aug 2018 http://www.ieee-ras.org/component/rseventspro/event/1308-mmar-2018-23rd-international-conference-on-methods-and-models-in-automation-and-robotics?Itemid=101

Conference

Conference	23rd International Conference on Methods & Models in Automation & Robotics
Location	Amber Baltic Hotel
Country/Territory	Poland
City	Miedzyzdroje
Period	27/08/2018 → 30/08/2018
Internet address	http://www.ieee-ras.org/component/rseventspro/event/1308-mmar-2018-23rd-international-conference-on-methods-and-models-in-automation-and-robotics?Itemid=101

Keywords

Offshore
Floating
Wind Turbine
Hydrodynamic
system identification
Modeling

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10.1109/MMAR.2018.8485979

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Cite this

@inproceedings{f32a046117764109a8e60c7158aa5fbc,

title = "Experimental Modelling of a Floating Offshore Wind Turbine",

abstract = "Leading wind turbine manufacturers are increasinglylooking at the possibilities of sending offshore wind turbinesto deep seas. This can be done using a Floating Offshore WindTurbine (FOWT). Therefore FOWT is an interesting and timelyfield of study. The aim of the paper is to use System Identification(SI) to make a data-driven-based model for the FOWT system,located in Offshore Wind & Wave Laboratory at Aalborg University.This is achieved by conducting experiments and analyzingthe data. SI is used to analyze data from the experiments andobtain different models. These models are then evaluated basedon the fit, the frequency response, autocorrelation and crosscorrelation.Eventually, an AutoRegressive Moving Average andExtra input (ARMAX) model is shown to be the most accurateamongst the analyzed models.",

keywords = "Offshore, Floating, Wind Turbine, Hydrodynamic, system identification, Modeling",

author = "Christian Lindquist and Nielsen, {Patrick N{\o}rgaard} and Rikke Pedersen and {N. Soltani}, Mohsen",

year = "2018",

month = aug,

doi = "10.1109/MMAR.2018.8485979",

language = "English",

pages = "327--332",

booktitle = "Proceedings of the 23rd International Conference on Methods and Models in Automation and Robotics, MMAR",

publisher = "IEEE Press",

note = "23rd International Conference on Methods & Models in Automation & Robotics, MMAR ; Conference date: 27-08-2018 Through 30-08-2018",

url = "http://www.ieee-ras.org/component/rseventspro/event/1308-mmar-2018-23rd-international-conference-on-methods-and-models-in-automation-and-robotics?Itemid=101",

}

Lindquist, C, Nielsen, PN, Pedersen, R & N. Soltani, M 2018, Experimental Modelling of a Floating Offshore Wind Turbine. in Proceedings of the 23rd International Conference on Methods and Models in Automation and Robotics, MMAR., 8485979, IEEE Press, pp. 327-332, 23rd International Conference on Methods & Models in Automation & Robotics, Miedzyzdroje, Poland, 27/08/2018. https://doi.org/10.1109/MMAR.2018.8485979

Experimental Modelling of a Floating Offshore Wind Turbine. / Lindquist, Christian; Nielsen, Patrick Nørgaard; Pedersen, Rikke et al.
Proceedings of the 23rd International Conference on Methods and Models in Automation and Robotics, MMAR. IEEE Press, 2018. p. 327-332 8485979.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Experimental Modelling of a Floating Offshore Wind Turbine

AU - Lindquist, Christian

AU - Nielsen, Patrick Nørgaard

AU - Pedersen, Rikke

AU - N. Soltani, Mohsen

PY - 2018/8

Y1 - 2018/8

N2 - Leading wind turbine manufacturers are increasinglylooking at the possibilities of sending offshore wind turbinesto deep seas. This can be done using a Floating Offshore WindTurbine (FOWT). Therefore FOWT is an interesting and timelyfield of study. The aim of the paper is to use System Identification(SI) to make a data-driven-based model for the FOWT system,located in Offshore Wind & Wave Laboratory at Aalborg University.This is achieved by conducting experiments and analyzingthe data. SI is used to analyze data from the experiments andobtain different models. These models are then evaluated basedon the fit, the frequency response, autocorrelation and crosscorrelation.Eventually, an AutoRegressive Moving Average andExtra input (ARMAX) model is shown to be the most accurateamongst the analyzed models.

AB - Leading wind turbine manufacturers are increasinglylooking at the possibilities of sending offshore wind turbinesto deep seas. This can be done using a Floating Offshore WindTurbine (FOWT). Therefore FOWT is an interesting and timelyfield of study. The aim of the paper is to use System Identification(SI) to make a data-driven-based model for the FOWT system,located in Offshore Wind & Wave Laboratory at Aalborg University.This is achieved by conducting experiments and analyzingthe data. SI is used to analyze data from the experiments andobtain different models. These models are then evaluated basedon the fit, the frequency response, autocorrelation and crosscorrelation.Eventually, an AutoRegressive Moving Average andExtra input (ARMAX) model is shown to be the most accurateamongst the analyzed models.

KW - Offshore

KW - Floating

KW - Wind Turbine

KW - Hydrodynamic

KW - system identification

KW - Modeling

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DO - 10.1109/MMAR.2018.8485979

M3 - Article in proceeding

SP - 327

EP - 332

BT - Proceedings of the 23rd International Conference on Methods and Models in Automation and Robotics, MMAR

PB - IEEE Press

T2 - 23rd International Conference on Methods & Models in Automation & Robotics

Y2 - 27 August 2018 through 30 August 2018

ER -

Experimental Modelling of a Floating Offshore Wind Turbine

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Keywords

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