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Design and comparison of quasi continuous sliding mode control with feedback linearization for a large scale wind turbine with wind speed estimation

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  • Golnary, Farshad
  • Moradi, Hamed

Abstract

In this paper, dynamic modelling and control of WindPACT 1.5 MW wind turbine in Region 2 for extracting the maximum energy from wind is investigated (where the wind velocity is greater than ‘cut in’ and below ‘rated’ wind speeds). In this region, the generator torque must regulate the rotor speed in its optimal value while the blade pitch angle is considered constant in its optimal value. To achieve a more accurate model, wind turbine is modeled as an electromechanical system with two masses dynamics. A new method based on adaptive neuro fuzzy inference system (ANFIS) is considered for wind speed estimation; where rotor speed, output power and pitch angle are inputs of such system and estimated wind velocity is the output. Using estimated wind speed, two control methods based on feedback linearization & quasi continuous sliding mode control are designed for tracking the optimal rotor speed and increasing the efficiency. For implementation of feedback linearization approach, design of an observer based on high order sliding mode is investigated. Performance of these control methods is compared in terms of different mean wind speeds in Region 2. Results are validated by FAST which shows that feedback linearization control with observer has a better ability in performance and load reduction in various wind speeds.

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  • Golnary, Farshad & Moradi, Hamed, 2018. "Design and comparison of quasi continuous sliding mode control with feedback linearization for a large scale wind turbine with wind speed estimation," Renewable Energy, Elsevier, vol. 127(C), pages 495-508.
  • Handle: RePEc:eee:renene:v:127:y:2018:i:c:p:495-508
    DOI: 10.1016/j.renene.2018.04.081
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    Cited by:

    1. Yarmohammadi, Mohammad J. & Sadeghzadeh, Arash & Taghizadeh, Mostafa, 2020. "Gain-scheduled control of wind turbine exploiting inexact wind speed measurement for full operating range," Renewable Energy, Elsevier, vol. 149(C), pages 890-901.
    2. Golnary, Farshad & Tse, K.T., 2021. "Novel sensorless fault-tolerant pitch control of a horizontal axis wind turbine with a new hybrid approach for effective wind velocity estimation," Renewable Energy, Elsevier, vol. 179(C), pages 1291-1315.
    3. Hawari, Qusay & Kim, Taeseong & Ward, Christopher & Fleming, James, 2022. "A robust gain scheduling method for a PI collective pitch controller of multi-MW onshore wind turbines," Renewable Energy, Elsevier, vol. 192(C), pages 443-455.
    4. Hongfu Zhang & Jiahao Wen & Farshad Golnary & Lei Zhou, 2022. "Output Power Control and Load Mitigation of a Horizontal Axis Wind Turbine with a Fully Coupled Aeroelastic Model: Novel Sliding Mode Perspective," Mathematics, MDPI, vol. 10(15), pages 1-40, August.
    5. Golnary, Farshad & Moradi, Hamed, 2022. "Identification of the dynamics of the drivetrain and estimating its unknown parts in a large scale wind turbine," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 50-69.
    6. Mousavi, Yashar & Bevan, Geraint & Kucukdemiral, Ibrahim Beklan & Fekih, Afef, 2022. "Sliding mode control of wind energy conversion systems: Trends and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

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