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A Multi-Point Method Considering the Maximum Power Point Tracking Dynamic Process for Aerodynamic Optimization of Variable-Speed Wind Turbine Blades

Author

Listed:
  • Zhiqiang Yang

    (School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)

  • Minghui Yin

    (School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)

  • Yan Xu

    (School of Electrical and Information Engineering, University of Sydney, Sydney, NSW 2006, Australia)

  • Zhengyang Zhang

    (School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)

  • Yun Zou

    (School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)

  • Zhao Yang Dong

    (School of Electrical and Information Engineering, University of Sydney, Sydney, NSW 2006, Australia)

Abstract

Due to the dynamic process of maximum power point tracking (MPPT) caused by turbulence and large rotor inertia, variable-speed wind turbines (VSWTs) cannot maintain the optimal tip speed ratio (TSR) from cut-in wind speed up to the rated speed. Therefore, in order to increase the total captured wind energy, the existing aerodynamic design for VSWT blades, which only focuses on performance improvement at a single TSR, needs to be improved to a multi-point design. In this paper, based on a closed-loop system of VSWTs, including turbulent wind, rotor, drive train and MPPT controller, the distribution of operational TSR and its description based on inflow wind energy are investigated. Moreover, a multi-point method considering the MPPT dynamic process for the aerodynamic optimization of VSWT blades is proposed. In the proposed method, the distribution of operational TSR is obtained through a dynamic simulation of the closed-loop system under a specific turbulent wind, and accordingly the multiple design TSRs and the corresponding weighting coefficients in the objective function are determined. Finally, using the blade of a National Renewable Energy Laboratory (NREL) 1.5 MW wind turbine as the baseline, the proposed method is compared with the conventional single-point optimization method using the commercial software Bladed. Simulation results verify the effectiveness of the proposed method.

Suggested Citation

  • Zhiqiang Yang & Minghui Yin & Yan Xu & Zhengyang Zhang & Yun Zou & Zhao Yang Dong, 2016. "A Multi-Point Method Considering the Maximum Power Point Tracking Dynamic Process for Aerodynamic Optimization of Variable-Speed Wind Turbine Blades," Energies, MDPI, vol. 9(6), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:6:p:425-:d:71151
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    References listed on IDEAS

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    1. Bavanish, B. & Thyagarajan, K., 2013. "Optimization of power coefficient on a horizontal axis wind turbine using bem theory," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 169-182.
    2. Peter J. Schubel & Richard J. Crossley, 2012. "Wind Turbine Blade Design," Energies, MDPI, vol. 5(9), pages 1-25, September.
    3. Yun-Su Kim & Il-Yop Chung & Seung-Il Moon, 2013. "An Analysis of Variable-Speed Wind Turbine Power-Control Methods with Fluctuating Wind Speed," Energies, MDPI, vol. 6(7), pages 1-16, July.
    4. Liu, Xiongwei & Wang, Lin & Tang, Xinzi, 2013. "Optimized linearization of chord and twist angle profiles for fixed-pitch fixed-speed wind turbine blades," Renewable Energy, Elsevier, vol. 57(C), pages 111-119.
    5. 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.
    6. Kim, Bumsuk & Kim, Woojune & Lee, Sanglae & Bae, Sungyoul & Lee, Youngho, 2013. "Developement and verification of a performance based optimal design software for wind turbine blades," Renewable Energy, Elsevier, vol. 54(C), pages 166-172.
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    Cited by:

    1. Yin, Minghui & Yang, Zhiqiang & Xu, Yan & Liu, Jiankun & Zhou, Lianjun & Zou, Yun, 2018. "Aerodynamic optimization for variable-speed wind turbines based on wind energy capture efficiency," Applied Energy, Elsevier, vol. 221(C), pages 508-521.
    2. Kyoungboo Yang, 2020. "Geometry Design Optimization of a Wind Turbine Blade Considering Effects on Aerodynamic Performance by Linearization," Energies, MDPI, vol. 13(9), pages 1-18, May.
    3. Alkhabbaz, Ali & Yang, Ho-Seong & Weerakoon, A.H Samitha & Lee, Young-Ho, 2021. "A novel linearization approach of chord and twist angle distribution for 10 kW horizontal axis wind turbine," Renewable Energy, Elsevier, vol. 178(C), pages 1398-1420.
    4. Jie Zhu & Xin Cai & Rongrong Gu, 2017. "Multi-Objective Aerodynamic and Structural Optimization of Horizontal-Axis Wind Turbine Blades," Energies, MDPI, vol. 10(1), pages 1-18, January.
    5. Khamlaj, Tariq Abdulsalam & Rumpfkeil, Markus Peer, 2018. "Analysis and optimization of ducted wind turbines," Energy, Elsevier, vol. 162(C), pages 1234-1252.
    6. Zhiqiang Yang & Minghui Yin & Yan Xu & Yun Zou & Zhao Yang Dong & Qian Zhou, 2016. "Inverse Aerodynamic Optimization Considering Impacts of Design Tip Speed Ratio for Variable-Speed Wind Turbines," Energies, MDPI, vol. 9(12), pages 1-15, December.
    7. Xiaolian Zhang & Can Huang & Sipeng Hao & Fan Chen & Jingjing Zhai, 2016. "An Improved Adaptive-Torque-Gain MPPT Control for Direct-Driven PMSG Wind Turbines Considering Wind Farm Turbulences," Energies, MDPI, vol. 9(11), pages 1-16, November.

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