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

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

1 Citationer (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.

Originalsprog	Engelsk
Titel	Proceedings of the 23rd International Conference on Methods and Models in Automation and Robotics, MMAR
Antal sider	6
Forlag	IEEE Press
Publikationsdato	aug. 2018
Sider	327-332
Artikelnummer	8485979
ISBN (Elektronisk)	978-1-5386-4325-9
DOI	https://doi.org/10.1109/MMAR.2018.8485979
Status	Udgivet - aug. 2018
Begivenhed	23rd International Conference on Methods & Models in Automation & Robotics - Amber Baltic Hotel, Miedzyzdroje, Polen Varighed: 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

Konference

Konference	23rd International Conference on Methods & Models in Automation & Robotics
Lokation	Amber Baltic Hotel
Land/Område	Polen
By	Miedzyzdroje
Periode	27/08/2018 → 30/08/2018
Internetadresse	http://www.ieee-ras.org/component/rseventspro/event/1308-mmar-2018-23rd-international-conference-on-methods-and-models-in-automation-and-robotics?Itemid=101

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10.1109/MMAR.2018.8485979

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Citationsformater

@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. i Proceedings of the 23rd International Conference on Methods and Models in Automation and Robotics, MMAR., 8485979, IEEE Press, s. 327-332, 23rd International Conference on Methods & Models in Automation & Robotics, Miedzyzdroje, Polen, 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. s. 327-332 8485979.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › 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

UR - http://www.scopus.com/inward/record.url?scp=85056453554&partnerID=8YFLogxK

U2 - 10.1109/MMAR.2018.8485979

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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