IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v60y2016icp377-393.html
   My bibliography  Save this article

State-of-the-art in wind turbine control: Trends and challenges

Author

Listed:
  • Njiri, Jackson G.
  • Söffker, Dirk

Abstract

Wind energy is one of the most rapidly growing renewable sources of energy due to the fact that it has little negative impact on environment. To meet the growing demand, wind turbines are being scaled up both in size and power rating. However, as the size increases, the structural loads of the turbine become more dominant, causing increased fatigue stress on the turbine components which can lead to early failure. Another area of focus in wind energy is lowering production cost to give it a competitive edge over other alternative power sources. From the control point of view, low production cost of wind energy can be achieved by operating the wind turbine at/or near the optimum power efficiency during partial load regime, guaranteeing reliability by reducing fatigue loads, and regulating generated power to its rated value in the high wind regime. Often, it is difficult to realize a control algorithm that can guarantee both efficiency and reliability because these two aspects involve conflicting objectives. This paper reviews various control strategies that are used in wind turbine systems, both in low and high wind speed regions focusing primarily on multi-objective control schemes. Emerging trends that are likely to influence the current or future wind energy production, either positively or negatively, are also discussed.

Suggested Citation

  • Njiri, Jackson G. & Söffker, Dirk, 2016. "State-of-the-art in wind turbine control: Trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 377-393.
    • Handle: RePEc:eee:rensus:v:60:y:2016:i:c:p:377-393
    DOI: 10.1016/j.rser.2016.01.110
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032116001404
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2016.01.110?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Yan & Söffker, Dirk, 2012. "Variable high-gain disturbance observer design with online adaption of observer gains embedded in numerical integration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 847-857.
    2. Peter J. Schubel & Richard J. Crossley, 2012. "Wind Turbine Blade Design," Energies, MDPI, vol. 5(9), pages 1-25, September.
    3. Ali Eltamaly & A Alolah & Hassan Farh, 2013. "Maximum Power Extraction from Utility-Interfaced Wind Turbines," Chapters, in: Hasan Arman & Ibrahim Yuksel (ed.), New Developments in Renewable Energy, IntechOpen.
    4. Bottasso, C.L. & Croce, A. & Riboldi, C.E.D. & Nam, Y., 2013. "Multi-layer control architecture for the reduction of deterministic and non-deterministic loads on wind turbines," Renewable Energy, Elsevier, vol. 51(C), pages 159-169.
    5. Hassan, H.M. & ElShafei, A.L. & Farag, W.A. & Saad, M.S., 2012. "A robust LMI-based pitch controller for large wind turbines," Renewable Energy, Elsevier, vol. 44(C), pages 63-71.
    6. 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.
    7. Sungsu Park & Yoonsu Nam, 2012. "Two LQRI based Blade Pitch Controls for Wind Turbines," Energies, MDPI, vol. 5(6), pages 1-19, June.
    8. Petrović, Vlaho & Jelavić, Mate & Baotić, Mato, 2015. "Advanced control algorithms for reduction of wind turbine structural loads," Renewable Energy, Elsevier, vol. 76(C), pages 418-431.
    9. George C. Ledec & Kennan W. Rapp & Roberto G. Aiello, 2011. "Greening the Wind : Environmental and Social Considerations for Wind Power Development," World Bank Publications - Books, The World Bank Group, number 2388.
    10. 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.
    11. Bilgili, Mehmet & Yasar, Abdulkadir & Simsek, Erdogan, 2011. "Offshore wind power development in Europe and its comparison with onshore counterpart," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 905-915, February.
    12. Tian, Zhigang & Jin, Tongdan & Wu, Bairong & Ding, Fangfang, 2011. "Condition based maintenance optimization for wind power generation systems under continuous monitoring," Renewable Energy, Elsevier, vol. 36(5), pages 1502-1509.
    13. Asier Diaz De Corcuera & Aron Pujana-Arrese & Jose M. Ezquerra & Edurne Segurola & Joseba Landaluze, 2012. "H ? Based Control for Load Mitigation in Wind Turbines," Energies, MDPI, vol. 5(4), pages 1-30, April.
    14. Boukhezzar, B. & Lupu, L. & Siguerdidjane, H. & Hand, M., 2007. "Multivariable control strategy for variable speed, variable pitch wind turbines," Renewable Energy, Elsevier, vol. 32(8), pages 1273-1287.
    15. Sun, Xiaojing & Huang, Diangui & Wu, Guoqing, 2012. "The current state of offshore wind energy technology development," Energy, Elsevier, vol. 41(1), pages 298-312.
    16. Wei Yu & Ming Ming Zhang & Jian Zhong Xu, 2012. "Effect of Smart Rotor Control Using a Deformable Trailing Edge Flap on Load Reduction under Normal and Extreme Turbulence," Energies, MDPI, vol. 5(9), pages 1-19, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yolanda Vidal & Leonardo Acho & Ningsu Luo & Mauricio Zapateiro & Francesc Pozo, 2012. "Power Control Design for Variable-Speed Wind Turbines," Energies, MDPI, vol. 5(8), pages 1-18, August.
    2. Yuan, Yuan & Chen, Xu & Tang, J., 2020. "Multivariable robust blade pitch control design to reject periodic loads on wind turbines," Renewable Energy, Elsevier, vol. 146(C), pages 329-341.
    3. 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.
    4. Mérida, Jován & Aguilar, Luis T. & Dávila, Jorge, 2014. "Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization," Renewable Energy, Elsevier, vol. 71(C), pages 715-728.
    5. Phan, Dinh-Chung & Yamamoto, Shigeru, 2016. "Rotor speed control of doubly fed induction generator wind turbines using adaptive maximum power point tracking," Energy, Elsevier, vol. 111(C), pages 377-388.
    6. Emejeamara, F.C. & Tomlin, A.S. & Millward-Hopkins, J.T., 2015. "Urban wind: Characterisation of useful gust and energy capture," Renewable Energy, Elsevier, vol. 81(C), pages 162-172.
    7. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    8. Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    9. Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
    10. Yuan, Yuan & Tang, J., 2017. "Adaptive pitch control of wind turbine for load mitigation under structural uncertainties," Renewable Energy, Elsevier, vol. 105(C), pages 483-494.
    11. Ewa Chomać-Pierzecka & Anna Sobczak & Dariusz Soboń, 2022. "Wind Energy Market in Poland in the Background of the Baltic Sea Bordering Countries in the Era of the COVID-19 Pandemic," Energies, MDPI, vol. 15(7), pages 1-21, March.
    12. Gao, Richie & Gao, Zhiwei, 2016. "Pitch control for wind turbine systems using optimization, estimation and compensation," Renewable Energy, Elsevier, vol. 91(C), pages 501-515.
    13. Piirainen, Kalle A. & Tanner, Anne Nygaard & Alkærsig, Lars, 2017. "Regional foresight and dynamics of smart specialization: A typology of regional diversification patterns," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 289-300.
    14. Shrabani Sahu & Sasmita Behera, 2022. "A review on modern control applications in wind energy conversion system," Energy & Environment, , vol. 33(2), pages 223-262, March.
    15. Petrović, Vlaho & Jelavić, Mate & Baotić, Mato, 2015. "Advanced control algorithms for reduction of wind turbine structural loads," Renewable Energy, Elsevier, vol. 76(C), pages 418-431.
    16. Lüth, Alexandra & Keles, Dogan, 2024. "Risks, strategies, and benefits of offshore energy hubs: A literature-based survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    17. Jongmin Cheon & Jinwook Kim & Joohoon Lee & Kichang Lee & Youngkiu Choi, 2019. "Development of Hardware-in-the-Loop-Simulation Testbed for Pitch Control System Performance Test," Energies, MDPI, vol. 12(10), pages 1-20, May.
    18. Zhao, Xin-gang & Ren, Ling-zhi, 2015. "Focus on the development of offshore wind power in China: Has the golden period come?," Renewable Energy, Elsevier, vol. 81(C), pages 644-657.
    19. Salcedo-Sanz, S. & Gallo-Marazuela, D. & Pastor-Sánchez, A. & Carro-Calvo, L. & Portilla-Figueras, A. & Prieto, L., 2014. "Offshore wind farm design with the Coral Reefs Optimization algorithm," Renewable Energy, Elsevier, vol. 63(C), pages 109-115.
    20. Lasheen, Ahmed & Elshafei, Abdel Latif, 2016. "Wind-turbine collective-pitch control via a fuzzy predictive algorithm," Renewable Energy, Elsevier, vol. 87(P1), pages 298-306.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:60:y:2016:i:c:p:377-393. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.