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Optimized linearization of chord and twist angle profiles for fixed-pitch fixed-speed wind turbine blades

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  • Liu, Xiongwei
  • Wang, Lin
  • Tang, Xinzi

Abstract

The chord and twist angle radial profiles of a fixed-pitch fixed-speed (FPFS) horizontal-axis wind turbine blade are based on a particular design wind speed and design tip speed ratio. Because the tip speed ratio varies with wind speed, the originally optimized chord and twist angle radial profiles for a preliminary blade design through optimum rotor theory do not necessarily provide the highest annual energy production (AEP) for the wind turbine on a specific site with known wind resources. This paper aims to demonstrate a novel optimal blade design method for an FPFS wind turbine through adopting linear radial profiles of the blade chord and twist angle and optimizing the slope of these two lines. The radial profiles of the blade chord and twist angle are linearized on a heuristic basis with fixed values at the blade tip and floating values at the blade root based on the preliminary blade design, and the best solution is determined using the highest AEP for a particular wind speed Weibull distribution as the optimization criteria with constraints of the top limit power output of the wind turbine. The outcomes demonstrate clearly that the proposed blade design optimization method offers a good opportunity for FPFS wind turbine blade design to achieve a better power performance and low manufacturing cost. This approach can be used for any practice of FPFS wind turbine blade design and refurbishment.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:57:y:2013:i:c:p:111-119
    DOI: 10.1016/j.renene.2013.01.036
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    References listed on IDEAS

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    1. Maalawi, K.Y. & Badr, M.A, 2003. "A practical approach for selecting optimum wind rotors," Renewable Energy, Elsevier, vol. 28(5), pages 803-822.
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    Cited by:

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    2. Tahani, Mojtaba & Kavari, Ghazale & Masdari, Mehran & Mirhosseini, Mojtaba, 2017. "Aerodynamic design of horizontal axis wind turbine with innovative local linearization of chord and twist distributions," Energy, Elsevier, vol. 131(C), pages 78-91.
    3. Wang, Lin & Liu, Xiongwei & Kolios, Athanasios, 2016. "State of the art in the aeroelasticity of wind turbine blades: Aeroelastic modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 195-210.
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    6. Ahmadi Asl, Hamid & Kamali Monfared, Reza & Rad, Manouchehr, 2017. "Experimental investigation of blade number and design effects for a ducted wind turbine," Renewable Energy, Elsevier, vol. 105(C), pages 334-343.
    7. Del Valle Carrasco, Arturo & Valles-Rosales, Delia J. & Mendez, Luis C. & Rodriguez, Manuel I., 2016. "A site-specific design of a fixed-pitch fixed-speed wind turbine blade for energy optimization using surrogate models," Renewable Energy, Elsevier, vol. 88(C), pages 112-119.
    8. Nour Khlaifat & Ali Altaee & John Zhou & Yuhan Huang & Ali Braytee, 2020. "Optimization of a Small Wind Turbine for a Rural Area: A Case Study of Deniliquin, New South Wales, Australia," Energies, MDPI, vol. 13(9), pages 1-26, May.
    9. 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.
    10. Abdelsalam, Ali M. & El-Askary, W.A. & Kotb, M.A. & Sakr, I.M., 2021. "Experimental study on small scale horizontal axis wind turbine of analytically-optimized blade with linearized chord twist angle profile," Energy, Elsevier, vol. 216(C).
    11. 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.
    12. Mustafa Kaya, 2019. "A CFD Based Application of Support Vector Regression to Determine the Optimum Smooth Twist for Wind Turbine Blades," Sustainability, MDPI, vol. 11(16), pages 1-25, August.
    13. Iqbal, M. & Azam, M. & Naeem, M. & Khwaja, A.S. & Anpalagan, A., 2014. "Optimization classification, algorithms and tools for renewable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 640-654.
    14. Moghadassian, Behnam & Sharma, Anupam, 2020. "Designing wind turbine rotor blades to enhance energy capture in turbine arrays," Renewable Energy, Elsevier, vol. 148(C), pages 651-664.
    15. Jia, Liangyue & Hao, Jia & Hall, John & Nejadkhaki, Hamid Khakpour & Wang, Guoxin & Yan, Yan & Sun, Mengyuan, 2021. "A reinforcement learning based blade twist angle distribution searching method for optimizing wind turbine energy power," Energy, Elsevier, vol. 215(PA).
    16. Sun, ZhaoCheng & Li, Dong & Mao, YuFeng & Feng, Long & Zhang, Yue & Liu, Chao, 2022. "Anti-cavitation optimal design and experimental research on tidal turbines based on improved inverse BEM," Energy, Elsevier, vol. 239(PD).

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