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A novel dynamic stall model based on Theodorsen theory and its application

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  • Li, Zhiguo
  • Gao, Zhiying
  • Chen, Yongyan
  • Zhang, Liru
  • Wang, Jianwen

Abstract

The unsteady aerodynamic characteristics and serious time-lag of wind turbine blades due to long time of dynamic stall make the actual measured power of rotor seriously deviate from its static prediction value. Therefore, dynamic stall model is becoming more and more significant for the Megawatt wind turbine with larger size and flexibility. In this paper, a novel dynamic stall model accounting for attached flow and dynamic separation flow of trailing edge is built using Theodorsen theory and Kirchhoff potential flow theory. The model includes the unsteady effect arising from vortex shedding and flow separation on trailing edge, and takes boundary layer lag and pressure lag into consideration. A validation is carried out by comparing the response of the model with incompressible dynamic stall model in software GH Bladed using airfoils data from National Renewable Energy Laboratory (NREL) 5 MW offshore wind turbine blades as input. The consistent results prove that the proposed model is accurate, reliable and universal. Furthermore, effect factors such as mean angle of attack, angle of attack amplitude, Mach number, reduced frequency and time constants on dynamic stall performance are further explored. The proposed model will provide a new choice for calculating aerodynamic load of the blades under stall condition.

Suggested Citation

  • Li, Zhiguo & Gao, Zhiying & Chen, Yongyan & Zhang, Liru & Wang, Jianwen, 2022. "A novel dynamic stall model based on Theodorsen theory and its application," Renewable Energy, Elsevier, vol. 193(C), pages 344-356.
    • Handle: RePEc:eee:renene:v:193:y:2022:i:c:p:344-356
    DOI: 10.1016/j.renene.2022.04.128
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    References listed on IDEAS

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    1. Liu, Xiong & Liang, Shi & Li, Gangqiang & Godbole, Ajit & Lu, Cheng, 2020. "An improved dynamic stall model and its effect on wind turbine fatigue load prediction," Renewable Energy, Elsevier, vol. 156(C), pages 117-130.
    2. Liu, Pengyin & Yu, Guohua & Zhu, Xiaocheng & Du, Zhaohui, 2014. "Unsteady aerodynamic prediction for dynamic stall of wind turbine airfoils with the reduced order modeling," Renewable Energy, Elsevier, vol. 69(C), pages 402-409.
    3. Huang, Bin & Wang, Pengzhong & Wang, Lu & Cao, Tingfa & Wu, Dazhuan & Wu, Peng, 2021. "A combined method of CFD simulation and modified Beddoes-Leishman model to predict the dynamic stall characterizations of S809 airfoil," Renewable Energy, Elsevier, vol. 179(C), pages 1636-1649.
    4. Zhu, Chengyong & Qiu, Yingning & Wang, Tongguang, 2021. "Dynamic stall of the wind turbine airfoil and blade undergoing pitch oscillations: A comparative study," Energy, Elsevier, vol. 222(C).
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    1. Li, Zhiguo & Gao, Zhiying & Dai, Yuanjun & Wen, Caifeng & Zhang, Liru & Wang, Jianwen, 2023. "Unsteady aeroelastic performance analysis for large-scale megawatt wind turbines based on a novel aeroelastic coupling model," Renewable Energy, Elsevier, vol. 218(C).
    2. Yan, Jie & Nuertayi, Akejiang & Yan, Yamin & Liu, Shan & Liu, Yongqian, 2023. "Hybrid physical and data driven modeling for dynamic operation characteristic simulation of wind turbine," Renewable Energy, Elsevier, vol. 215(C).

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