TY - GEN
T1 - System Identification and model comparison of a Tension Leg Platform for Floating Offshore Wind Turbines
AU - Hansen, Thomas
AU - Jørgensen, Maria A. B.
AU - Tran, Van Roy
AU - Jessen, Kasper
AU - N. Soltani, Mohsen
PY - 2019/8
Y1 - 2019/8
N2 - This paper will focus on using system identification on experimental data for building a mathematical model for the platform of a floating offshore wind turbine and analyzing the behavior of the structure. The floating offshore wind turbine examined in this paper uses a scaled tension leg platform as itsfoundation and the wind turbine is a 1:35 scaled model of the 5 MW NREL offshore wind turbine. The mathematical model of the platform will describe thedisplacement of the TLP in surge when affected by an irregular wave series generated from a scaled Pierson-Moskowitz wave spectrum. To obtain such a mathematical model, an examination of the displacement of the platform due to the hydrodynamic loads will be conducted on the foundation of the floating offshore wind turbine. The height of the waves and the displacement ofthe floating offshore wind turbines will be measured by resistive wave gauges and OptiTrack cameras, respectively, at the offshore laboratory at Aalborg University Esbjerg. System identification is used on the data obtained from the experiments, to build multiple mathematical models with different model structures, in order to find the most appropriate model structure. It isconcluded from the analysis of the different mathematical models, that the Autoregressive Moving Average and Extra input model structure is the most accurate model at describing the dynamics of the platform of a floating offshore wind turbine. The model is valid for a specific operating range of Pierson-Moskowitz waves generated with a wind speed corresponding to 2 meters per seconds.
AB - This paper will focus on using system identification on experimental data for building a mathematical model for the platform of a floating offshore wind turbine and analyzing the behavior of the structure. The floating offshore wind turbine examined in this paper uses a scaled tension leg platform as itsfoundation and the wind turbine is a 1:35 scaled model of the 5 MW NREL offshore wind turbine. The mathematical model of the platform will describe thedisplacement of the TLP in surge when affected by an irregular wave series generated from a scaled Pierson-Moskowitz wave spectrum. To obtain such a mathematical model, an examination of the displacement of the platform due to the hydrodynamic loads will be conducted on the foundation of the floating offshore wind turbine. The height of the waves and the displacement ofthe floating offshore wind turbines will be measured by resistive wave gauges and OptiTrack cameras, respectively, at the offshore laboratory at Aalborg University Esbjerg. System identification is used on the data obtained from the experiments, to build multiple mathematical models with different model structures, in order to find the most appropriate model structure. It isconcluded from the analysis of the different mathematical models, that the Autoregressive Moving Average and Extra input model structure is the most accurate model at describing the dynamics of the platform of a floating offshore wind turbine. The model is valid for a specific operating range of Pierson-Moskowitz waves generated with a wind speed corresponding to 2 meters per seconds.
KW - System Identification
KW - Floating wind turbine
KW - TLP
KW - Tension Leg Platform
KW - Offshore Wind
KW - Pierson-Moskowitz
KW - Scaled-model
KW - SI
KW - FOWT
KW - Floating offshore wind turbines
KW - System identification
UR - http://www.scopus.com/inward/record.url?scp=85074241549&partnerID=8YFLogxK
U2 - 10.1109/MMAR.2019.8864710
DO - 10.1109/MMAR.2019.8864710
M3 - Article in proceeding
SP - 410
EP - 415
BT - 2019 24th International Conference on Methods and Models in Automation and Robotics, MMAR 2019
PB - IEEE Press
T2 - 24th International Conference on Methods & Models in Automation & Robotics (MMAR)
Y2 - 26 August 2019 through 29 August 2019
ER -