IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i22p7529-d1278199.html
   My bibliography  Save this article

Design and Analysis of an Adaptive Dual-Drive Lift–Drag Composite Vertical-Axis Wind Turbine Generator

Author

Listed:
  • Pengfei Yan

    (School of Mechanical Engineering, North University of China, Taiyuan 030051, China)

  • Yaning Li

    (School of Mechanical Engineering, North University of China, Taiyuan 030051, China)

  • Qiang Gao

    (School of Mechanical Engineering, North University of China, Taiyuan 030051, China)

  • Shuai Lian

    (School of Mechanical Engineering, North University of China, Taiyuan 030051, China)

  • Qihui Wu

    (School of Mechanical Engineering, North University of China, Taiyuan 030051, China)

Abstract

In this paper, based on the lift-type wind turbine, an adaptive double-drive lift–drag composite vertical-axis wind turbine is designed to improve the wind energy utilization rate. A drag blade was employed to rapidly accelerate the wind turbine, and the width of the blade was adaptively adjusted with the speed of the wind turbine to realize lift–drag conversion. The aerodynamic performance analysis using Fluent showed that the best performance is achieved with a blade curvature of 30° and a drag-type blade width ratio of 2/3. Physical experiments proved that a lift–drag composite vertical-axis wind turbine driven by dual blades can start when the incoming wind speed is 1.6 m/s, which is 23.8% lower than the existing lift-type wind turbine’s starting wind speed of 2.1 m/s. At the same time, when the wind speed reaches 8.8 m/s, the guide rail adaptive drag-type blades all contract and transform into lift-type wind turbine blades. The results show that the comprehensive wind energy utilization rate of the adaptive dual-drive lift–drag composite vertical-axis wind turbine was 5.98% higher than that of ordinary lift-type wind turbines and can be applied to wind power generation in high-wind-speed wind farms.

Suggested Citation

  • Pengfei Yan & Yaning Li & Qiang Gao & Shuai Lian & Qihui Wu, 2023. "Design and Analysis of an Adaptive Dual-Drive Lift–Drag Composite Vertical-Axis Wind Turbine Generator," Energies, MDPI, vol. 16(22), pages 1-15, November.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7529-:d:1278199
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/22/7529/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/22/7529/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zamani, Mahdi & Nazari, Saeed & Moshizi, Sajad A. & Maghrebi, Mohammad Javad, 2016. "Three dimensional simulation of J-shaped Darrieus vertical axis wind turbine," Energy, Elsevier, vol. 116(P1), pages 1243-1255.
    2. Xu, You-Lin & Peng, Yi-Xin & Zhan, Sheng, 2019. "Optimal blade pitch function and control device for high-solidity straight-bladed vertical axis wind turbines," Applied Energy, Elsevier, vol. 242(C), pages 1613-1625.
    3. Biao Wang & Sandrine Geoffroy & Marion Bonhomme, 2022. "Urban form study for wind potential development," Environment and Planning B, , vol. 49(1), pages 76-91, January.
    4. Sagharichi, A. & Zamani, M. & Ghasemi, A., 2018. "Effect of solidity on the performance of variable-pitch vertical axis wind turbine," Energy, Elsevier, vol. 161(C), pages 753-775.
    5. Sengupta, A.R. & Biswas, A. & Gupta, R., 2019. "Comparison of low wind speed aerodynamics of unsymmetrical blade H-Darrieus rotors-blade camber and curvature signatures for performance improvement," Renewable Energy, Elsevier, vol. 139(C), pages 1412-1427.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Su, Jie & Chen, Yaoran & Han, Zhaolong & Zhou, Dai & Bao, Yan & Zhao, Yongsheng, 2020. "Investigation of V-shaped blade for the performance improvement of vertical axis wind turbines," Applied Energy, Elsevier, vol. 260(C).
    2. Xu, Zhongyun & Chen, Jian & Li, Chun, 2023. "Research on the adaptability of dynamic pitch control strategies on H-type VAWT close-range arrays by simulation study," Renewable Energy, Elsevier, vol. 218(C).
    3. Barnes, Andrew & Marshall-Cross, Daniel & Hughes, Ben Richard, 2021. "Towards a standard approach for future Vertical Axis Wind Turbine aerodynamics research and development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    4. Lin Pan & Ze Zhu & Haodong Xiao & Leichong Wang, 2021. "Numerical Analysis and Parameter Optimization of J-Shaped Blade on Offshore Vertical Axis Wind Turbine," Energies, MDPI, vol. 14(19), pages 1-29, October.
    5. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    6. Hand, Brian & Kelly, Ger & Cashman, Andrew, 2021. "Aerodynamic design and performance parameters of a lift-type vertical axis wind turbine: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    7. Zhang, Tengxi & Xin, Li & Wang, Shunjiang & Guo, Ren & Wang, Wentao & Cui, Jia & Wang, Peng, 2024. "A novel approach of energy and reserve scheduling for hybrid power systems: Frequency security constraints," Applied Energy, Elsevier, vol. 361(C).
    8. Ma, Ning & Lei, Hang & Han, Zhaolong & Zhou, Dai & Bao, Yan & Zhang, Kai & Zhou, Lei & Chen, Caiyong, 2018. "Airfoil optimization to improve power performance of a high-solidity vertical axis wind turbine at a moderate tip speed ratio," Energy, Elsevier, vol. 150(C), pages 236-252.
    9. Ghazalla, R.A. & Mohamed, M.H. & Hafiz, A.A., 2019. "Synergistic analysis of a Darrieus wind turbine using computational fluid dynamics," Energy, Elsevier, vol. 189(C).
    10. Farzadi, Ramin & Zanj, Amir & Bazargan, Majid, 2024. "Effect of baffles on efficiency of darrieus vertical axis wind turbines equipped with J-type blades," Energy, Elsevier, vol. 305(C).
    11. Gonçalves, Afonso N.C. & Pereira, José M.C. & Sousa, João M.M., 2022. "Passive control of dynamic stall in a H-Darrieus Vertical Axis Wind Turbine using blade leading-edge protuberances," Applied Energy, Elsevier, vol. 324(C).
    12. Tatiana Tucunduva Philippi Cortese & Jairo Filho Sousa de Almeida & Giseli Quirino Batista & José Eduardo Storopoli & Aaron Liu & Tan Yigitcanlar, 2022. "Understanding Sustainable Energy in the Context of Smart Cities: A PRISMA Review," Energies, MDPI, vol. 15(7), pages 1-38, March.
    13. Lidong Zhang & Kaiqi Zhu & Junwei Zhong & Ling Zhang & Tieliu Jiang & Shaohua Li & Zhongbin Zhang, 2018. "Numerical Investigations of the Effects of the Rotating Shaft and Optimization of Urban Vertical Axis Wind Turbines," Energies, MDPI, vol. 11(7), pages 1-25, July.
    14. Yi Song Liu & Tan Yigitcanlar & Mirko Guaralda & Kenan Degirmenci & Aaron Liu & Michael Kane, 2022. "Leveraging the Opportunities of Wind for Cities through Urban Planning and Design: A PRISMA Review," Sustainability, MDPI, vol. 14(18), pages 1-78, September.
    15. Matteo Vedovelli & Abdelgalil Eltayesh & Francesco Natili & Francesco Castellani, 2022. "Experimental and Numerical Investigation of the Effect of Blades Number on the Dynamic Response of a Small Horizontal-Axis Wind Turbine," Energies, MDPI, vol. 15(23), pages 1-19, December.
    16. Xiancheng Wang & Hao Li & Junhua Chen & Chuhua Jiang & Lingjie Bao, 2023. "Research on Solidity of Horizontal-Axis Tidal Current Turbine," Energies, MDPI, vol. 16(8), pages 1-17, April.
    17. Singh, Enderaaj & Roy, Sukanta & Yam, Ke San & Law, Ming Chiat, 2023. "Numerical analysis of H-Darrieus vertical axis wind turbines with varying aspect ratios for exhaust energy extractions," Energy, Elsevier, vol. 277(C).
    18. Yosry, Ahmed Gharib & Álvarez, Eduardo Álvarez & Valdés, Rodolfo Espina & Pandal, Adrián & Marigorta, Eduardo Blanco, 2023. "Experimental and multiphase modeling of small vertical-axis hydrokinetic turbine with free-surface variations," Renewable Energy, Elsevier, vol. 203(C), pages 788-801.
    19. Palanisamy Mohan Kumar & Krishnamoorthi Sivalingam & Teik-Cheng Lim & Seeram Ramakrishna & He Wei, 2019. "Strategies for Enhancing the Low Wind Speed Performance of H-Darrieus Wind Turbine—Part 1," Clean Technol., MDPI, vol. 1(1), pages 1-20, August.
    20. Jiang, Yichen & Liu, Shijie & Zao, Peidong & Yu, Yanwei & Zou, Li & Liu, Liqin & Li, Jiawen, 2022. "Experimental evaluation of a tree-shaped quad-rotor wind turbine on power output controllability and survival shutdown capability," Applied Energy, Elsevier, vol. 309(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7529-:d:1278199. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.