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Sliding Mode Control Strategy for Wind Turbine Power Maximization

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  • Oscar Barambones

    (Automatic Control and System Engineering Department, Engineering School of Vitoria, University of the Basque Country, Nieves Cano 12, Vitoria 01006, Spain)

Abstract

The efficiency of the wind power conversions systems can be greatly improved using an appropriate control algorithm. In this work, a sliding mode control for variable speed wind turbine that incorporates a doubly fed induction generator is described. The electrical system incorporates a wound rotor induction machine with back-to-back three phase power converter bridges between its rotor and the grid. In the presented design the so-called vector control theory is applied, in order to simplify the electrical equations. The proposed control scheme uses stator flux-oriented vector control for the rotor side converter bridge control and grid voltage vector control for the grid side converter bridge control. The stability analysis of the proposed sliding mode controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand, that the proposed controller provides high-performance dynamic characteristics, and on the other hand, that this scheme is robust with respect to the uncertainties that usually appear in the real systems.

Suggested Citation

  • Oscar Barambones, 2012. "Sliding Mode Control Strategy for Wind Turbine Power Maximization," Energies, MDPI, vol. 5(7), pages 1-21, July.
  • Handle: RePEc:gam:jeners:v:5:y:2012:i:7:p:2310-2330:d:18767
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    References listed on IDEAS

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    1. Maurício B. C. Salles & Kay Hameyer & José R. Cardoso & Ahda. P. Grilo & Claudia Rahmann, 2010. "Crowbar System in Doubly Fed Induction Wind Generators," Energies, MDPI, vol. 3(4), pages 1-16, April.
    2. Joselin Herbert, G.M. & Iniyan, S. & Sreevalsan, E. & Rajapandian, S., 2007. "A review of wind energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(6), pages 1117-1145, August.
    3. Christina N. Papadimitriou & Nicholas A. Vovos, 2010. "Transient Response Improvement of Microgrids Exploiting the Inertia of a Doubly-Fed Induction Generator (DFIG)," Energies, MDPI, vol. 3(6), pages 1-18, June.
    4. John Kabouris & Fotis D. Kanellos, 2009. "Impacts of Large Scale Wind Penetration on Energy Supply Industry," Energies, MDPI, vol. 2(4), pages 1-11, November.
    5. Ioannis D. Margaris & Anca D. Hansen & Poul Sørensen & Nikolaos D. Hatziargyriou, 2010. "Illustration of Modern Wind Turbine Ancillary Services," Energies, MDPI, vol. 3(6), pages 1-13, June.
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    Cited by:

    1. Mircea Neagoe & Radu Saulescu & Codruta Jaliu, 2019. "Design and Simulation of a 1 DOF Planetary Speed Increaser for Counter-Rotating Wind Turbines with Counter-Rotating Electric Generators," Energies, MDPI, vol. 12(9), pages 1-19, May.
    2. David De la Vega & James C. G. Matthews & Lars Norin & Itziar Angulo, 2013. "Mitigation Techniques to Reduce the Impact of Wind Turbines on Radar Services," Energies, MDPI, vol. 6(6), pages 1-15, June.
    3. Oscar Barambones & Jose A. Cortajarena & Patxi Alkorta & Jose M. Gonzalez De Durana, 2014. "A Real-Time Sliding Mode Control for a Wind Energy System Based on a Doubly Fed Induction Generator," Energies, MDPI, vol. 7(10), pages 1-22, October.
    4. Chen, Jincheng & Wang, Feng & Stelson, Kim A., 2018. "A mathematical approach to minimizing the cost of energy for large utility wind turbines," Applied Energy, Elsevier, vol. 228(C), pages 1413-1422.
    5. Rodrigo Teixeira Pinto & Sílvio Fragoso Rodrigues & Edwin Wiggelinkhuizen & Ricardo Scherrer & Pavol Bauer & Jan Pierik, 2012. "Operation and Power Flow Control of Multi-Terminal DC Networks for Grid Integration of Offshore Wind Farms Using Genetic Algorithms," Energies, MDPI, vol. 6(1), pages 1-26, December.
    6. 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.
    7. Adel Merabet, 2018. "Adaptive Sliding Mode Speed Control for Wind Energy Experimental System," Energies, MDPI, vol. 11(9), pages 1-14, August.
    8. Yu-Huei Cheng & Ching-Ming Lai, 2017. "Control Strategy Optimization for Parallel Hybrid Electric Vehicles Using a Memetic Algorithm," Energies, MDPI, vol. 10(3), pages 1-21, March.
    9. Justo, Jackson John & Mwasilu, Francis & Jung, Jin-Woo, 2015. "Doubly-fed induction generator based wind turbines: A comprehensive review of fault ride-through strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 447-467.
    10. Yolanda Vidal & Leonardo Acho & Ignasi Cifre & Àlex Garcia & Francesc Pozo & José Rodellar, 2017. "Wind Turbine Synchronous Reset Pitch Control," Energies, MDPI, vol. 10(6), pages 1-16, June.
    11. Oscar Barambones & Jose M. Gonzalez de Durana & Isidro Calvo, 2018. "Adaptive Sliding Mode Control for a Double Fed Induction Generator Used in an Oscillating Water Column System," Energies, MDPI, vol. 11(11), pages 1-27, October.
    12. Nuria Novas & Alfredo Alcayde & Isabel Robalo & Francisco Manzano-Agugliaro & Francisco G. Montoya, 2020. "Energies and Its Worldwide Research," Energies, MDPI, vol. 13(24), pages 1-41, December.
    13. 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.
    14. Ulas Eminoglu & Saffet Ayasun, 2014. "Modeling and Design Optimization of Variable-Speed Wind Turbine Systems," Energies, MDPI, vol. 7(1), pages 1-18, January.
    15. Sung-Won Lee & Kwan-Ho Chun, 2019. "Adaptive Sliding Mode Control for PMSG Wind Turbine Systems," Energies, MDPI, vol. 12(4), pages 1-17, February.

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