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A Model-Free Approach for Maximizing Power Production of Wind Farm Using Multi-Resolution Simultaneous Perturbation Stochastic Approximation

Author

Listed:
  • Mohd Ashraf Ahmad

    (Department of Systems Science, Kyoto University, Yoshida-Honmachi, Kyoto 606-8501, Japan)

  • Shun-ichi Azuma

    (Department of Systems Science, Kyoto University, Yoshida-Honmachi, Kyoto 606-8501, Japan)

  • Toshiharu Sugie

    (Department of Systems Science, Kyoto University, Yoshida-Honmachi, Kyoto 606-8501, Japan)

Abstract

This paper provides a model-free approach based on the Multi-Resolution Simultaneous Perturbation Stochastic Approximation (MR-SPSA) for maximizing power production of wind farms. The main advantage is that the method based on MR-SPSA can achieve fast controller tuning without any plant model by exploiting the information of the wind farm configuration such as turbines location and wind direction. In order to simulate the performance of the model-free scheme, a wind farm model with dynamic characterization of wake interaction between turbines is used and then the proposed method is applied to the Horns Rev wind farm. Simulation results illustrate that the method based on MR-SPSA achieves the maximum total power production with faster convergence compared with other existing model-free methods.

Suggested Citation

  • Mohd Ashraf Ahmad & Shun-ichi Azuma & Toshiharu Sugie, 2014. "A Model-Free Approach for Maximizing Power Production of Wind Farm Using Multi-Resolution Simultaneous Perturbation Stochastic Approximation," Energies, MDPI, vol. 7(9), pages 1-23, August.
  • Handle: RePEc:gam:jeners:v:7:y:2014:i:9:p:5624-5646:d:39685
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    References listed on IDEAS

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    1. Hansen, Anca D. & Sørensen, Poul & Iov, Florin & Blaabjerg, Frede, 2006. "Centralised power control of wind farm with doubly fed induction generators," Renewable Energy, Elsevier, vol. 31(7), pages 935-951.
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    Cited by:

    1. Park, Jinkyoo & Law, Kincho H., 2016. "A data-driven, cooperative wind farm control to maximize the total power production," Applied Energy, Elsevier, vol. 165(C), pages 151-165.
    2. Herp, Jürgen & Poulsen, Uffe V. & Greiner, Martin, 2015. "Wind farm power optimization including flow variability," Renewable Energy, Elsevier, vol. 81(C), pages 173-181.
    3. Jay P. Goit & Wim Munters & Johan Meyers, 2016. "Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects," Energies, MDPI, vol. 9(1), pages 1-20, January.

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