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A Comparative Analysis of Some Methods for Wind Turbine Maximum Power Point Tracking

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  • Constantin Voloşencu

    (Department of Automation and Applied Informatics, Faculty of Automation and Computers, Politehnica University Timişoara, 300223 Timişoara, Romania)

Abstract

The study in the paper is placed in the broad context of research for increasing the efficiency of capturing and converting wind energy. The purpose of the study is to analyze some mathematical methods for maximum power point tracking in wind turbines. The mathematical methods studied are on–off control, fuzzy control, and neural predictive control. The rules developed for maximum power point tracking are presented. The related control structures and their design methods are presented. The behaviors of the control systems and their energy efficiency are analyzed. Maximum power point tracking ensures a significant increase in the energy generated compared to the unfavorable case of operation at a small and constant load torque. The differences in energy efficiency between the methods of maximum power point tracking studied are small.

Suggested Citation

  • Constantin Voloşencu, 2021. "A Comparative Analysis of Some Methods for Wind Turbine Maximum Power Point Tracking," Mathematics, MDPI, vol. 9(19), pages 1-33, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:19:p:2399-:d:644040
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    References listed on IDEAS

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    1. Hae Gwang Jeong & Ro Hak Seung & Kyo Beum Lee, 2012. "An Improved Maximum Power Point Tracking Method for Wind Power Systems," Energies, MDPI, vol. 5(5), pages 1-16, May.
    2. Abdullah, M.A. & Yatim, A.H.M. & Tan, C.W. & Saidur, R., 2012. "A review of maximum power point tracking algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3220-3227.
    3. Dongran Song & Jian Yang & Mei Su & Anfeng Liu & Yao Liu & Young Hoon Joo, 2017. "A Comparison Study between Two MPPT Control Methods for a Large Variable-Speed Wind Turbine under Different Wind Speed Characteristics," Energies, MDPI, vol. 10(5), pages 1-18, May.
    4. Constantin Volosencu, 2021. "Reducing Energy Consumption and Increasing the Performances of AC Motor Drives Using Fuzzy PI Speed Controllers," Energies, MDPI, vol. 14(8), pages 1-15, April.
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