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Future research directions for the wind turbine generator system

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  • Hossain, Md Maruf
  • Ali, Mohd. Hasan

Abstract

The headway of wind power generation is a great blessing to help meet up the electrical power demand day by day. The strongest challenges for wind energy conversion system (WECS) are to handle the intermittency of wind and to maintain the grid reliability. The power electronics and energy storage systems are essential elements of the WECS. This paper attempts to provide various new directions to the future wind energy researchers to improve the wind turbine aerodynamics, electric generators׳ configurations with improved control of power electronics and lower cost energy storage system for designing a reliable wind turbine generator system. This study will work as a guideline for the researchers to understand the development and requirement of a reliable and smart wind energy conversion system.

Suggested Citation

  • Hossain, Md Maruf & Ali, Mohd. Hasan, 2015. "Future research directions for the wind turbine generator system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 481-489.
    • Handle: RePEc:eee:rensus:v:49:y:2015:i:c:p:481-489
    DOI: 10.1016/j.rser.2015.04.126
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    5. Miguel A. Rodríguez-López & Luis M. López-González & Luis M. López-Ochoa & Jesús Las-Heras-Casas, 2018. "Methodology for Detecting Malfunctions and Evaluating the Maintenance Effectiveness in Wind Turbine Generator Bearings Using Generic versus Specific Models from SCADA Data," Energies, MDPI, vol. 11(4), pages 1-22, March.
    6. Youssef, Abdel-Raheem & Mousa, Hossam H.H. & Mohamed, Essam E.M., 2020. "Development of self-adaptive P&O MPPT algorithm for wind generation systems with concentrated search area," Renewable Energy, Elsevier, vol. 154(C), pages 875-893.
    7. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    8. Ayodele, T.R. & Ogunjuyigbe, A.S.O. & Adetokun, B.B., 2017. "Optimal capacitance selection for a wind-driven self-excited reluctance generator under varying wind speed and load conditions," Applied Energy, Elsevier, vol. 190(C), pages 339-353.
    9. Ruiz de la Hermosa González-Carrato, Raúl, 2017. "Sound and vibration-based pattern recognition for wind turbines driving mechanisms," Renewable Energy, Elsevier, vol. 109(C), pages 262-274.
    10. Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Adetokun, B.B., 2017. "Steady state analysis of wind-driven self-excited reluctance generator for isolated applications," Renewable Energy, Elsevier, vol. 114(PB), pages 984-1004.
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    12. Fantino, Roberto & Solsona, Jorge & Busada, Claudio, 2016. "Nonlinear observer-based control for PMSG wind turbine," Energy, Elsevier, vol. 113(C), pages 248-257.

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