Analysis and real-time prediction of the full-scale thrust for floating wind turbine based on artificial intelligence

Xue Jiang, Sandy Day, David Clelland, Xu Liang

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)
34 Downloads (Pure)


In this paper, numerous aero-hydro-servo-elastic coupled simulations are carried out in time-domain to observe the performance of the real-time thrust acting on the rotor of the OC3-Hywind offshore floating wind turbine. And the studying focuses on investigating the correlation between inputs (surge motion, pitch motion, wind conditions, etc.) and the targeted output (rotor thrust) in the time domain. Besides, artificial intelligence (AI) techniques are used to estimate a prediction model of real-time thrust based on the data from simulations. To predict the thrust, data for four comparative coupled environmental conditions are considered, by which the effect of turbulence and wave spectrum on the thrust force is also investigated. Moreover, a series of simulations of frequency-increasing regular wave conditions and speed-increasing wind conditions are carried out to observe their effect on the real-time rotor thrust. Additionally, the impact of the pitch and surge RAOs of the floating foundation and the wind velocity are quantitatively studied. It reveals that the high-frequency response of thrust is dominated by wave change, whereas low-frequency response is dominated by wind change. Besides, one simulation model of the thrust acting on the rotor is estimated regarding high-frequency and low-frequency response separately to account the dominating influence.
Original languageEnglish
Pages (from-to)207-216
Number of pages10
JournalOcean Engineering
Early online date15 Feb 2019
Publication statusPublished - 1 Mar 2019


  • fully coupled simulation
  • OC3-Hywind
  • real time thrust prediction
  • artificial neural network
  • impact analyses on the real time thrust


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