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Wind Energy Conversions, Controls, and Applications: A Review for Sustainable Technologies and Directions

Author

Listed:
  • M. A. Hannan

    (Department of Electrical and Electronic Engineering, COE, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • Ali Q. Al-Shetwi

    (Electrical Engineering Department, Fahad Bin Sultan University, Tabuk 47721, Saudi Arabia)

  • M. S. Mollik

    (Department of Mechatronics Engineering, International Islamic University Malaysia, Kuala Lumpur 50728, Malaysia)

  • Pin Jern Ker

    (Institute of Sustainable Energy, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • M. Mannan

    (Department of Electrical and Electronic Engineering, COE, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • M. Mansor

    (Department of Electrical and Electronic Engineering, COE, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • Hussein M. K. Al-Masri

    (Department of Electrical Power Engineering, Yarmouk University, Irbid 21163, Jordan)

  • T. M. Indra Mahlia

    (Centre of Green Technology, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia)

Abstract

The use of renewable energy techniques is becoming increasingly popular because of rising demand and the threat of negative carbon footprints. Wind power offers a great deal of untapped potential as an alternative source of energy. The rising demand for wind energy typically results in the generation of high-quality output electricity through grid integration. More sophisticated contemporary generators, power converters, energy management, and controllers have been recently developed to integrate wind turbines into the electricity system. However, a comprehensive review of the role of converters in the wind system’s power conversion, control, and application toward sustainable development is not thoroughly investigated. Thus, this paper proposes a comprehensive review of the impact of converters on wind energy conversion with its operation, control, and recent challenges. The converters’ impact on the integration and control of wind turbines was highlighted. Moreover, the conversion and implementation of the control of the wind energy power system have been analyzed in detail. Also, the recently advanced converters applications for wind energy conversion were presented. Finally, recommendations for future converters use in wind energy conversions were highlighted for efficient, stable, and sustainable wind power. This rigorous study will lead academic researchers and industry partners toward the development of optimal wind power technologies with improved efficiency, operation, and costs.

Suggested Citation

  • M. A. Hannan & Ali Q. Al-Shetwi & M. S. Mollik & Pin Jern Ker & M. Mannan & M. Mansor & Hussein M. K. Al-Masri & T. M. Indra Mahlia, 2023. "Wind Energy Conversions, Controls, and Applications: A Review for Sustainable Technologies and Directions," Sustainability, MDPI, vol. 15(5), pages 1-30, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:3986-:d:1076811
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    References listed on IDEAS

    as
    1. Jabbari Asl, Hamed & Yoon, Jungwon, 2016. "Power capture optimization of variable-speed wind turbines using an output feedback controller," Renewable Energy, Elsevier, vol. 86(C), pages 517-525.
    2. Hannan, M.A. & Lipu, M.S. Hossain & Ker, Pin Jern & Begum, R.A. & Agelidis, Vasilios G. & Blaabjerg, F., 2019. "Power electronics contribution to renewable energy conversion addressing emission reduction: Applications, issues, and recommendations," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. Liu, W.Y., 2017. "A review on wind turbine noise mechanism and de-noising techniques," Renewable Energy, Elsevier, vol. 108(C), pages 311-320.
    4. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
    5. Zhang, Guozhou & Hu, Weihao & Cao, Di & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2021. "A novel deep reinforcement learning enabled sparsity promoting adaptive control method to improve the stability of power systems with wind energy penetration," Renewable Energy, Elsevier, vol. 178(C), pages 363-376.
    6. Assareh, Ehsanolah & Biglari, Mojtaba, 2015. "A novel approach to capture the maximum power from variable speed wind turbines using PI controller, RBF neural network and GSA evolutionary algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1023-1037.
    7. Belmokhtar, K. & Doumbia, M.L. & Agbossou, K., 2014. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 76(C), pages 679-693.
    8. 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).
    9. Yin, Xiu-xing & Lin, Yong-gang & Li, Wei & Gu, Ya-jing & Liu, Hong-wei & Lei, Peng-fei, 2015. "A novel fuzzy integral sliding mode current control strategy for maximizing wind power extraction and eliminating voltage harmonics," Energy, Elsevier, vol. 85(C), pages 677-686.
    10. Sanaz Sabzevari & Rasool Heydari & Maryam Mohiti & Mehdi Savaghebi & Jose Rodriguez, 2021. "Model-Free Neural Network-Based Predictive Control for Robust Operation of Power Converters," Energies, MDPI, vol. 14(8), pages 1-12, April.
    11. Willis, D.J. & Niezrecki, C. & Kuchma, D. & Hines, E. & Arwade, S.R. & Barthelmie, R.J. & DiPaola, M. & Drane, P.J. & Hansen, C.J. & Inalpolat, M. & Mack, J.H. & Myers, A.T. & Rotea, M., 2018. "Wind energy research: State-of-the-art and future research directions," Renewable Energy, Elsevier, vol. 125(C), pages 133-154.
    12. Xiangwu Yan & Xuewei Sun, 2020. "Inertia and Droop Frequency Control Strategy of Doubly-Fed Induction Generator Based on Rotor Kinetic Energy and Supercapacitor," Energies, MDPI, vol. 13(14), pages 1-19, July.
    13. Zuo, Haoran & Bi, Kaiming & Hao, Hong, 2020. "A state-of-the-art review on the vibration mitigation of wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    14. Lin, Whei-Min & Hong, Chih-Ming, 2010. "Intelligent approach to maximum power point tracking control strategy for variable-speed wind turbine generation system," Energy, Elsevier, vol. 35(6), pages 2440-2447.
    15. Baroudi, Jamal A. & Dinavahi, Venkata & Knight, Andrew M., 2007. "A review of power converter topologies for wind generators," Renewable Energy, Elsevier, vol. 32(14), pages 2369-2385.
    16. Hand, Brian & Kelly, Ger & Cashman, Andrew, 2021. "Aerodynamic design and performance parameters of a lift-type vertical axis wind turbine: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    17. Xiangwu Yan & Linlin Yang & Tiecheng Li, 2021. "The LVRT Control Scheme for PMSG-Based Wind Turbine Generator Based on the Coordinated Control of Rotor Overspeed and Supercapacitor Energy Storage," Energies, MDPI, vol. 14(2), pages 1-22, January.
    18. Ren, Zhengru & Verma, Amrit Shankar & Li, Ye & Teuwen, Julie J.E. & Jiang, Zhiyu, 2021. "Offshore wind turbine operations and maintenance: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    19. Moradi, Hamed & Vossoughi, Gholamreza, 2015. "Robust control of the variable speed wind turbines in the presence of uncertainties: A comparison between H∞ and PID controllers," Energy, Elsevier, vol. 90(P2), pages 1508-1521.
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