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Parameter-varying modeling and nonlinear model predictive control with disturbance prediction for spar-type floating offshore wind turbines

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Abstract

This paper proposes novel methods for the modeling and control of spar-type floating offshore wind turbines (FOWTs) by focusing on the dependency of the equilibrium and perturbed dynamics on the rotor azimuth angle. In addition, three new reduced models for controller design are derived using trajectory linearization by accounting for the dependency of the equilibrium on the azimuth angle. A thorough simulation study shows that the proposed models reproduce the important dynamic characteristics of FOWTs more accurately than the conventional models. Then, nonlinear model predictive controllers (NMPCs) minimizing the nonquadratic cost functions are developed for the proposed models, which include nonlinear terms for the rotor azimuth angle. These NMPCs suppress the variation in the forces applied to the blades better than the conventional linear MPCs while maintaining a low computational cost. The best NMPC for the models is one that accounts for the dependency of both the equilibrium and perturbed dynamics on the rotor azimuth angle. This NMPC suppresses the platform yaw and forces added on the blades. The performance of such an NMPC can be further improved using the inflow wind disturbance data predicted using a light detection and ranging wind sensor.

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Authors and Affiliations

  1. Department of Systems Science, Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyoku, Kyoto, 606-8501, Japan

    Yuga Okada & Toshiyuki Ohtsuka

  2. Offshore Advanced Technology Department, National Maritime Research Institute, Mitaka, 181-0004, Japan

    Ken Haneda & Toshiki Chujo

Authors
  1. Yuga Okada
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  2. Ken Haneda
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  3. Toshiki Chujo
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  4. Toshiyuki Ohtsuka
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Correspondence to Yuga Okada.

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This work was partly supported by JSPS KAKENHI Grant Number 15H02257.

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Okada, Y., Haneda, K., Chujo, T. et al. Parameter-varying modeling and nonlinear model predictive control with disturbance prediction for spar-type floating offshore wind turbines. J Mar Sci Technol 27, 589–603 (2022). https://doi.org/10.1007/s00773-021-00854-6

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  • DOI: https://doi.org/10.1007/s00773-021-00854-6

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