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Stabilization of power output and platform motion of a floating offshore wind turbine-generator system using model predictive control based on previewed disturbances

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  • Wakui, Tetsuya
  • Nagamura, Atsushi
  • Yokoyama, Ryohei

Abstract

Model predictive control of a floating offshore wind turbine-generator system, in which wave height as well as inflow wind speed is regarded as the previewed disturbances, is developed to stabilize power output and platform motion and reduce dynamic loads at mechanical and supporting components at high wind speeds. First, the internal model to predict dynamic control behaviors to previewed disturbances is identified from an aero-elastic-hydro-control coupled simulation result, in which pseudorandom binary sequence signals are added to the manipulated variables calculated in a gain-scheduling feedback controller of the generator speed to satisfy a persistently exciting condition. Second, an aero-elastic-hydro-control coupled simulation using the developed model predictive control is performed for a 5-MW floating offshore wind turbine-generator system. The identified internal model has a high prediction accuracy of the system outputs by regarding the spatial mean wind speed in the swept area of the wind turbine as a rotor effective wind speed. The simulation results under turbulent wind fields and irregular wave height variations reveal that the stabilization of the power output and platform motion and the dynamic load reduction are achieved by employing the developed model predictive control with a perfect preview of the wind speed and wave height.

Suggested Citation

  • Wakui, Tetsuya & Nagamura, Atsushi & Yokoyama, Ryohei, 2021. "Stabilization of power output and platform motion of a floating offshore wind turbine-generator system using model predictive control based on previewed disturbances," Renewable Energy, Elsevier, vol. 173(C), pages 105-127.
  • Handle: RePEc:eee:renene:v:173:y:2021:i:c:p:105-127
    DOI: 10.1016/j.renene.2021.03.112
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    References listed on IDEAS

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    1. Bottasso, C.L. & Pizzinelli, P. & Riboldi, C.E.D. & Tasca, L., 2014. "LiDAR-enabled model predictive control of wind turbines with real-time capabilities," Renewable Energy, Elsevier, vol. 71(C), pages 442-452.
    2. Wakui, Tetsuya & Yoshimura, Motoki & Yokoyama, Ryohei, 2017. "Multiple-feedback control of power output and platform pitching motion for a floating offshore wind turbine-generator system," Energy, Elsevier, vol. 141(C), pages 563-578.
    3. Ma, Yu & Sclavounos, Paul D. & Cross-Whiter, John & Arora, Dhiraj, 2018. "Wave forecast and its application to the optimal control of offshore floating wind turbine for load mitigation," Renewable Energy, Elsevier, vol. 128(PA), pages 163-176.
    4. Madsen, F.J. & Nielsen, T.R.L. & Kim, T. & Bredmose, H. & Pegalajar-Jurado, A. & Mikkelsen, R.F. & Lomholt, A.K. & Borg, M. & Mirzaei, M. & Shin, P., 2020. "Experimental analysis of the scaled DTU10MW TLP floating wind turbine with different control strategies," Renewable Energy, Elsevier, vol. 155(C), pages 330-346.
    5. Zhang, Mingming & Li, Xin & Tong, Jingxin & Xu, Jianzhong, 2020. "Load control of floating wind turbine on a Tension-Leg-Platform subject to extreme wind condition," Renewable Energy, Elsevier, vol. 151(C), pages 993-1007.
    6. Zhang, Mingming & Li, Xin & Xu, Jianzhong, 2019. "Smart control of fatigue loads on a floating wind turbine with a tension-leg-platform," Renewable Energy, Elsevier, vol. 134(C), pages 745-756.
    7. Joannes Olondriz & Iker Elorza & Josu Jugo & Santi Alonso-Quesada & Aron Pujana-Arrese, 2018. "An Advanced Control Technique for Floating Offshore Wind Turbines Based on More Compact Barge Platforms," Energies, MDPI, vol. 11(5), pages 1-14, May.
    8. Zountouridou, E.I. & Kiokes, G.C. & Chakalis, S. & Georgilakis, P.S. & Hatziargyriou, N.D., 2015. "Offshore floating wind parks in the deep waters of Mediterranean Sea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 433-448.
    9. deCastro, M. & Salvador, S. & Gómez-Gesteira, M. & Costoya, X. & Carvalho, D. & Sanz-Larruga, F.J. & Gimeno, L., 2019. "Europe, China and the United States: Three different approaches to the development of offshore wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 55-70.
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