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Variable Torque Control of Offshore Wind Turbine on Spar Floating Platform Using Advanced RBF Neural Network

Author

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  • Lei Wang
  • Shan Zuo
  • Y. D. Song
  • Zheng Zhou

Abstract

Offshore floating wind turbine (OFWT) has been a challenging research spot because of the high‐quality wind power and complex load environment. This paper focuses on the research of variable torque control of offshore wind turbine on Spar floating platform. The control objective in below‐rated wind speed region is to optimize the output power by tracking the optimal tip‐speed ratio and ideal power curve. Aiming at the external disturbances and nonlinear uncertain dynamic systems of OFWT because of the proximity to load centers and strong wave coupling, this paper proposes an advanced radial basis function (RBF) neural network approach for torque control of OFWT system at speeds lower than rated wind speed. The robust RBF neural network weight adaptive rules are acquired based on the Lyapunov stability analysis. The proposed control approach is tested and compared with the NREL baseline controller using the “NREL offshore 5 MW wind turbine” model mounted on a Spar floating platform run on FAST and Matlab/Simulink, operating in the below‐rated wind speed condition. The simulation results show a better performance in tracking the optimal output power curve, therefore, completing the maximum wind energy utilization.

Suggested Citation

  • Lei Wang & Shan Zuo & Y. D. Song & Zheng Zhou, 2014. "Variable Torque Control of Offshore Wind Turbine on Spar Floating Platform Using Advanced RBF Neural Network," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:903493
    DOI: 10.1155/2014/903493
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    References listed on IDEAS

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    1. Zaragoza, Jordi & Pou, Josep & Arias, Antoni & Spiteri, Cyril & Robles, Eider & Ceballos, Salvador, 2011. "Study and experimental verification of control tuning strategies in a variable speed wind energy conversion system," Renewable Energy, Elsevier, vol. 36(5), pages 1421-1430.
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    Cited by:

    1. Feng Yang & Qing-wang Song & Lei Wang & Shan Zuo & Sheng-shan Li, 2014. "Wind and Wave Disturbances Compensation to Floating Offshore Wind Turbine Using Improved Individual Pitch Control Based on Fuzzy Control Strategy," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    2. Shan Zuo & Yongduan Song & Lei Wang & Zheng Zhou, 2014. "Neuron‐Adaptive PID Based Speed Control of SCSG Wind Turbine System," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).

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