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Feedback Linearization Controller for a Wind Energy Power System

Author

Listed:
  • Muthana Alrifai

    (Department of Electrical Engineering, Kuwait University, P. O. Box 5969, Safat 13060, Kuwait)

  • Mohamed Zribi

    (Department of Electrical Engineering, Kuwait University, P. O. Box 5969, Safat 13060, Kuwait)

  • Mohamed Rayan

    (Department of Electrical Engineering, Kuwait University, P. O. Box 5969, Safat 13060, Kuwait)

Abstract

This paper deals with the control of a doubly-fed induction generator (DFIG)-based variable speed wind turbine power system. A system of eight ordinary differential equations is used to model the wind energy conversion system. The generator has a wound rotor type with back-to-back three-phase power converter bridges between its rotor and the grid; it is modeled using the direct-quadrature rotating reference frame with aligned stator flux. An input-state feedback linearization controller is proposed for the wind energy power system. The controller guarantees that the states of the system track the desired states. Simulation results are presented to validate the proposed control scheme. Moreover, further simulation results are shown to investigate the robustness of the proposed control scheme to changes in some of the parameters of the system.

Suggested Citation

  • Muthana Alrifai & Mohamed Zribi & Mohamed Rayan, 2016. "Feedback Linearization Controller for a Wind Energy Power System," Energies, MDPI, vol. 9(10), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:10:p:771-:d:78777
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    References listed on IDEAS

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    1. Aman Abdulla Tanvir & Adel Merabet & Rachid Beguenane, 2015. "Real-Time Control of Active and Reactive Power for Doubly Fed Induction Generator (DFIG)-Based Wind Energy Conversion System," Energies, MDPI, vol. 8(9), pages 1-20, September.
    2. Oscar Barambones, 2012. "Sliding Mode Control Strategy for Wind Turbine Power Maximization," Energies, MDPI, vol. 5(7), pages 1-21, July.
    3. Ganjefar, Soheil & Ghassemi, Ali Akbar & Ahmadi, Mohamad Mehdi, 2014. "Improving efficiency of two-type maximum power point tracking methods of tip-speed ratio and optimum torque in wind turbine system using a quantum neural network," Energy, Elsevier, vol. 67(C), pages 444-453.
    4. Jau-Woei Perng & Guan-Yan Chen & Shan-Chang Hsieh, 2014. "Optimal PID Controller Design Based on PSO-RBFNN for Wind Turbine Systems," Energies, MDPI, vol. 7(1), pages 1-19, January.
    5. Dinh-Chung Phan & Shigeru Yamamoto, 2015. "Maximum Energy Output of a DFIG Wind Turbine Using an Improved MPPT-Curve Method," Energies, MDPI, vol. 8(10), pages 1-19, October.
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    Citations

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    Cited by:

    1. Jian Zuo & Yinhong Li & Dongyuan Shi & Xianzhong Duan, 2017. "Simultaneous Robust Coordinated Damping Control of Power System Stabilizers (PSSs), Static Var Compensator (SVC) and Doubly-Fed Induction Generator Power Oscillation Dampers (DFIG PODs) in Multimachin," Energies, MDPI, vol. 10(4), pages 1-23, April.
    2. Walter Gil-González & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Alberto-Jesus Perea-Moreno & Quetzalcoatl Hernandez-Escobedo, 2020. "Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves," Sustainability, MDPI, vol. 12(7), pages 1-20, April.
    3. Mohamed Zribi & Muthana Alrifai & Mohamed Rayan, 2017. "Sliding Mode Control of a Variable- Speed Wind Energy Conversion System Using a Squirrel Cage Induction Generator," Energies, MDPI, vol. 10(5), pages 1-21, May.
    4. Fausto Pedro García Márquez & Alberto Pliego Marugán & Jesús María Pinar Pérez & Stuart Hillmansen & Mayorkinos Papaelias, 2017. "Optimal Dynamic Analysis of Electrical/Electronic Components in Wind Turbines," Energies, MDPI, vol. 10(8), pages 1-19, July.

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