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Theoretical Modeling of Vertical-Axis Wind Turbine Wakes

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  • Mahdi Abkar

    (Department of Engineering, Aarhus University, 8000 Aarhus C, Denmark)

Abstract

In this work, two different theoretical models for predicting the wind velocity downwind of an H-rotor vertical-axis wind turbine are presented. The first model uses mass conservation together with the momentum theory and assumes a top-hat distribution for the wind velocity deficit. The second model considers a two-dimensional Gaussian shape for the velocity defect and satisfies mass continuity and the momentum balance. Both approaches are consistent with the existing and widely-used theoretical wake models for horizontal-axis wind turbines and, thus, can be implemented in the current numerical codes utilized for optimization and real-time applications. To assess and compare the two proposed models, we use large eddy simulation as well as field measurement data of vertical-axis wind turbine wakes. The results show that, although both models are generally capable of predicting the velocity defect, the prediction from the Gaussian-based wake model is more accurate compared to the top-hat counterpart. This is mainly related to the consistency of the assumptions used in the Gaussian-based wake model with the physics of the turbulent wake development downwind of the turbine.

Suggested Citation

  • Mahdi Abkar, 2018. "Theoretical Modeling of Vertical-Axis Wind Turbine Wakes," Energies, MDPI, vol. 12(1), pages 1-10, December.
  • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:10-:d:192207
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    References listed on IDEAS

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    1. Mahdi Abkar & Jens Nørkær Sørensen & Fernando Porté-Agel, 2018. "An Analytical Model for the Effect of Vertical Wind Veer on Wind Turbine Wakes," Energies, MDPI, vol. 11(7), pages 1-10, July.
    2. Sina Shamsoddin & Fernando Porté-Agel, 2016. "A Large-Eddy Simulation Study of Vertical Axis Wind Turbine Wakes in the Atmospheric Boundary Layer," Energies, MDPI, vol. 9(5), pages 1-23, May.
    3. Feng, Ju & Shen, Wen Zhong, 2017. "Design optimization of offshore wind farms with multiple types of wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 1283-1297.
    4. Lam, H.F. & Peng, H.Y., 2016. "Study of wake characteristics of a vertical axis wind turbine by two- and three-dimensional computational fluid dynamics simulations," Renewable Energy, Elsevier, vol. 90(C), pages 386-398.
    5. Govind, Bala, 2017. "Increasing the operational capability of a horizontal axis wind turbine by its integration with a vertical axis wind turbine," Applied Energy, Elsevier, vol. 199(C), pages 479-494.
    6. Sina Shamsoddin & Fernando Porté-Agel, 2014. "Large Eddy Simulation of Vertical Axis Wind Turbine Wakes," Energies, MDPI, vol. 7(2), pages 1-23, February.
    7. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Ogasawara, Tatsuhiko & Nakai, Alisa & Kasuya, Takuji, 2017. "Investigation of power performance and wake on a straight-bladed vertical axis wind turbine with field experiments," Energy, Elsevier, vol. 141(C), pages 1113-1123.
    8. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
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    Cited by:

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    2. Rezaeiha, Abdolrahim & Montazeri, Hamid & Blocken, Bert, 2019. "On the accuracy of turbulence models for CFD simulations of vertical axis wind turbines," Energy, Elsevier, vol. 180(C), pages 838-857.
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    4. Zheng Yuan & Jin Jiang & Jun Zang & Qihu Sheng & Ke Sun & Xuewei Zhang & Renwei Ji, 2020. "A Fast Two-Dimensional Numerical Method for the Wake Simulation of a Vertical Axis Wind Turbine," Energies, MDPI, vol. 14(1), pages 1-21, December.

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