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Power capture optimization of variable-speed wind turbines using an output feedback controller

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  • Jabbari Asl, Hamed
  • Yoon, Jungwon

Abstract

One of the major factors that can increase the efficiency of wind turbines is through control of the rotor speed to track the optimal value. A high performance controller can significantly increase the amount of energy that can be captured from wind. The main problem associated with controller design is the presence of uncertainties in the dynamic model of the system, which can be associated with unknown constant parameters and/or unmodeled dynamics such as external disturbances. several adaptive and robust control approaches have been developed to account for these uncertainties. In this paper, a robust controller is presented that compensates for both types of uncertainties; the full mechanical and electrical dynamics of the turbine are considered. These dynamics require acceleration of the rotor to provide feedback information which is not available in sufficiently accurate form during practice. Therefore, in this approach, an observer estimates this information using the speed of the rotor as the output, with the estimation error considered during the stability analysis. This presents one of the main advantages of the approach; the simulation results illustrate the effectiveness of the controller.

Suggested Citation

  • Jabbari Asl, Hamed & Yoon, Jungwon, 2016. "Power capture optimization of variable-speed wind turbines using an output feedback controller," Renewable Energy, Elsevier, vol. 86(C), pages 517-525.
    • Handle: RePEc:eee:renene:v:86:y:2016:i:c:p:517-525
    DOI: 10.1016/j.renene.2015.08.040
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    Cited by:

    1. Tiwari, Ramji & Babu, N. Ramesh, 2016. "Recent developments of control strategies for wind energy conversion system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 268-285.
    2. Fan, Zhixin & Zhu, Caichao, 2019. "The optimization and the application for the wind turbine power-wind speed curve," Renewable Energy, Elsevier, vol. 140(C), pages 52-61.
    3. M. A. Hannan & Ali Q. Al-Shetwi & M. S. Mollik & Pin Jern Ker & M. Mannan & M. Mansor & Hussein M. K. Al-Masri & T. M. Indra Mahlia, 2023. "Wind Energy Conversions, Controls, and Applications: A Review for Sustainable Technologies and Directions," Sustainability, MDPI, vol. 15(5), pages 1-30, February.
    4. Zholtayev, Darkhan & Rubagotti, Matteo & Do, Ton Duc, 2022. "Adaptive super-twisting sliding mode control for maximum power point tracking of PMSG-based wind energy conversion systems," Renewable Energy, Elsevier, vol. 183(C), pages 877-889.
    5. Shrabani Sahu & Sasmita Behera, 2022. "A review on modern control applications in wind energy conversion system," Energy & Environment, , vol. 33(2), pages 223-262, March.
    6. Zhicheng Lin & Song Zheng & Zhicheng Chen & Rong Zheng & Wang Zhang, 2019. "Application Research of the Parallel System Theory and the Data Engine Approach in Wind Energy Conversion System," Energies, MDPI, vol. 12(5), pages 1-20, March.
    7. Francesco Bottiglione & Giacomo Mantriota & Marco Valle, 2018. "Power-Split Hydrostatic Transmissions for Wind Energy Systems," Energies, MDPI, vol. 11(12), pages 1-15, December.
    8. Baniassadi, Amir & Shirinbakhsh, Mehrdad & Torabi, Farschad, 2017. "Multivariate optimization of off-grid wind turbines with variable demand - Case study of a remote commercial building," Renewable Energy, Elsevier, vol. 101(C), pages 1021-1029.
    9. Mazare, Mahmood & Taghizadeh, Mostafa, 2022. "Uncertainty estimator-based dual layer adaptive fault-tolerant control for wind turbines," Renewable Energy, Elsevier, vol. 188(C), pages 545-560.

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