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Frequency Support of Smart Grid Using Fuzzy Logic-Based Controller for Wind Energy Systems

Author

Listed:
  • Marcelo Godoy Simões

    (Electrical Engineering Department, Colorado School of Mines, Golden, CO 80401, USA)

  • Abdullah Bubshait

    (Electrical Engineering Department, King Faisal University, Alahsa 31982, Saudi Arabia)

Abstract

This paper proposes a fuzzy logic-based controller for a wind turbine system to provide frequency support for a smart grid. The designed controller is aimed to provide an appropriate dynamic droop rate depending on the local measurements of each wind turbine of a wind farm such as the maximum power available and the amount of power reserve. The designed fuzzy controller depends on the rate of change of frequency (ROCOF) at the point of common coupling (PCC). The main advantage of the proposed fuzzy controller is to provide frequency support by the wind turbine system connected to a smart grid. The dynamic rate of the controller is defined by the fuzzy sets considering the change in the grid’s frequency and the available reserve power. First, the response of static droop curves is investigated for different scenarios of wind turbines connected to a smart grid. Then, the proposed fuzzy logic-based droop controller is integrated into the system, and its performance and response are evaluated, and the results are compared with static-droop based controller. The proposed controller is tested using Matlab\Simulink.

Suggested Citation

  • Marcelo Godoy Simões & Abdullah Bubshait, 2019. "Frequency Support of Smart Grid Using Fuzzy Logic-Based Controller for Wind Energy Systems," Energies, MDPI, vol. 12(8), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1550-:d:225584
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    References listed on IDEAS

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    1. Singarao, Venkatesh Yadav & Rao, Vittal S., 2016. "Frequency responsive services by wind generation resources in United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1097-1108.
    2. Dreidy, Mohammad & Mokhlis, H. & Mekhilef, Saad, 2017. "Inertia response and frequency control techniques for renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 144-155.
    3. El Mokadem, M. & Courtecuisse, V. & Saudemont, C. & Robyns, B. & Deuse, J., 2009. "Experimental study of variable speed wind generator contribution to primary frequency control," Renewable Energy, Elsevier, vol. 34(3), pages 833-844.
    4. Camblong, H. & Nourdine, S. & Vechiu, I. & Tapia, G., 2012. "Control of wind turbines for fatigue loads reduction and contribution to the grid primary frequency regulation," Energy, Elsevier, vol. 48(1), pages 284-291.
    5. Moutis, Panayiotis & Papathanassiou, Stavros A. & Hatziargyriou, Nikos D., 2012. "Improved load-frequency control contribution of variable speed variable pitch wind generators," Renewable Energy, Elsevier, vol. 48(C), pages 514-523.
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    Cited by:

    1. Ramesh Kumar Behara & Akshay Kumar Saha, 2022. "Artificial Intelligence Control System Applied in Smart Grid Integrated Doubly Fed Induction Generator-Based Wind Turbine: A Review," Energies, MDPI, vol. 15(17), pages 1-56, September.

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