IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v263y2023ipas0360544222025786.html
   My bibliography  Save this article

Mode interpretation of blade number effects on wake dynamics of small-scale horizontal axis wind turbine

Author

Listed:
  • Wen, Jiahao
  • Zhou, Lei
  • Zhang, Hongfu

Abstract

The blade number of a wind turbine is a critical parameter that significantly affects its near-wake dynamics. In this study, we focused on the effect of the blade number on the wake of a small-scale horizontal-axis wind turbine (SHAWT) with a diameter of 0.18 m. An airfoil with a high lift coefficient was designed for a SHAWT model operating at a low Reynolds number. Large eddy simulation (LES) and optimal mode decomposition (OMD) were performed to identify the underlying coherence mode and to elucidate the wake dynamics. The LES results indicate that an increase in the blade number causes the double-peak velocity distribution to prematurely form a single peak shape. The effects of the blade number and tip speed ratio on the width and velocity deficit of the wake were also determined. The OMD results show that an increase in the number of blades results in the appearance of interharmonic modes with energies lower than that of the mean flow mode. Meanwhile, the increase in blade number causes early instability of the tip and hub/root vortices, leading to the break down and formation of patterns of streamwise vortices in the far wake. This leads to earlier wake recovery and influences the energy extraction and fatigue loads of the downstream turbines.

Suggested Citation

  • Wen, Jiahao & Zhou, Lei & Zhang, Hongfu, 2023. "Mode interpretation of blade number effects on wake dynamics of small-scale horizontal axis wind turbine," Energy, Elsevier, vol. 263(PA).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pa:s0360544222025786
    DOI: 10.1016/j.energy.2022.125692
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222025786
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125692?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (Part I: Power performance)," Energy, Elsevier, vol. 113(C), pages 713-722.
    2. Tummala, Abhishiktha & Velamati, Ratna Kishore & Sinha, Dipankur Kumar & Indraja, V. & Krishna, V. Hari, 2016. "A review on small scale wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1351-1371.
    3. Abraham, Aliza & Hong, Jiarong, 2020. "Dynamic wake modulation induced by utility-scale wind turbine operation," Applied Energy, Elsevier, vol. 257(C).
    4. Zhu, Xiaocheng & Sun, Chong & Ouyang, Hua & Du, Zhaohui, 2022. "Numerical investigation of the effect of towers and nacelles on the near wake of a horizontal-axis wind turbine model," Energy, Elsevier, vol. 238(PA).
    5. Shin, Dongheon & Ko, Kyungnam, 2022. "Experimental study on application of nacelle-mounted LiDAR for analyzing wind turbine wake effects by distance," Energy, Elsevier, vol. 243(C).
    6. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (part II: Wake characteristics)," Energy, Elsevier, vol. 113(C), pages 1304-1315.
    7. Hegazy, Amr & Blondel, Frédéric & Cathelain, Marie & Aubrun, Sandrine, 2022. "LiDAR and SCADA data processing for interacting wind turbine wakes with comparison to analytical wake models," Renewable Energy, Elsevier, vol. 181(C), pages 457-471.
    8. Sun, Chong & Tian, Tian & Zhu, Xiaocheng & Hua, Ouyang & Du, Zhaohui, 2021. "Investigation of the near wake of a horizontal-axis wind turbine model by dynamic mode decomposition," Energy, Elsevier, vol. 227(C).
    9. Sedaghatizadeh, Nima & Arjomandi, Maziar & Kelso, Richard & Cazzolato, Benjamin & Ghayesh, Mergen H., 2018. "Modelling of wind turbine wake using large eddy simulation," Renewable Energy, Elsevier, vol. 115(C), pages 1166-1176.
    10. Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2020. "A review of full-scale wind-field measurements of the wind-turbine wake effect and a measurement of the wake-interaction effect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    11. De Cillis, Giovanni & Cherubini, Stefania & Semeraro, Onofrio & Leonardi, Stefano & De Palma, Pietro, 2022. "The influence of incoming turbulence on the dynamic modes of an NREL-5MW wind turbine wake," Renewable Energy, Elsevier, vol. 183(C), pages 601-616.
    12. Newman, A. Jensen & Cal, Raúl Bayoán & Castillo, Luciano, 2015. "Blade number effects in a scaled down wind farm," Renewable Energy, Elsevier, vol. 81(C), pages 472-481.
    13. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    14. Chanprasert, W. & Sharma, R.N. & Cater, J.E. & Norris, S.E., 2022. "Large Eddy Simulation of wind turbine fatigue loading and yaw dynamics induced by wake turbulence," Renewable Energy, Elsevier, vol. 190(C), pages 208-222.
    15. Ge, Mingwei & Zhang, Shuaibin & Meng, Hang & Ma, Hongliang, 2020. "Study on interaction between the wind-turbine wake and the urban district model by large eddy simulation," Renewable Energy, Elsevier, vol. 157(C), pages 941-950.
    16. Zhang, Shuaibin & Du, Bowen & Ge, Mingwei & Zuo, Yingtao, 2022. "Study on the operation of small rooftop wind turbines and its effect on the wind environment in blocks," Renewable Energy, Elsevier, vol. 183(C), pages 708-718.
    17. Yossri, Widad & Ben Ayed, Samah & Abdelkefi, Abdessattar, 2021. "Airfoil type and blade size effects on the aerodynamic performance of small-scale wind turbines: Computational fluid dynamics investigation," Energy, Elsevier, vol. 229(C).
    18. Sarlak, H. & Nishino, T. & Martínez-Tossas, L.A. & Meneveau, C. & Sørensen, J.N., 2016. "Assessment of blockage effects on the wake characteristics and power of wind turbines," Renewable Energy, Elsevier, vol. 93(C), pages 340-352.
    19. Vaz, Jerson Rogério Pinheiro & Pinho, João Tavares & Mesquita, André Luiz Amarante, 2011. "An extension of BEM method applied to horizontal-axis wind turbine design," Renewable Energy, Elsevier, vol. 36(6), pages 1734-1740.
    20. Gao, Xiaoxia & Zhang, Shaohai & Li, Luqing & Xu, Shinai & Chen, Yao & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu & Lu, Hao, 2022. "Quantification of 3D spatiotemporal inhomogeneity for wake characteristics with validations from field measurement and wind tunnel test," Energy, Elsevier, vol. 254(PA).
    21. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Experimental investigation of the performance and wake effect of a small-scale wind turbine in a wind tunnel," Energy, Elsevier, vol. 166(C), pages 819-833.
    22. Singh, Ronit K. & Ahmed, M. Rafiuddin & Zullah, Mohammad Asid & Lee, Young-Ho, 2012. "Design of a low Reynolds number airfoil for small horizontal axis wind turbines," Renewable Energy, Elsevier, vol. 42(C), pages 66-76.
    23. Gao, Xiaoxia & Chen, Yao & Xu, Shinai & Gao, Wei & Zhu, Xiaoxun & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Lu, Hao, 2022. "Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements," Applied Energy, Elsevier, vol. 307(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hao Yue & Yagebai Zhao & Dabo Xin & Gaowa Xu, 2023. "Seasons Effects of Field Measurement of Near-Ground Wind Characteristics in a Complex Terrain Forested Region," Sustainability, MDPI, vol. 15(14), pages 1-33, July.
    2. Guanghui Che & Daocheng Zhou & Rui Wang & Lei Zhou & Hongfu Zhang & Sheng Yu, 2024. "Wind Energy Assessment in Forested Regions Based on the Combination of WRF and LSTM-Attention Models," Sustainability, MDPI, vol. 16(2), pages 1-18, January.
    3. Marcin Augustyn & Filip Lisowski, 2023. "Experimental and Numerical Studies on a Single Coherent Blade of a Vertical Axis Carousel Wind Rotor," Energies, MDPI, vol. 16(14), pages 1-17, July.
    4. Zhou, Lei & Wen, Jiahao & Wang, Zhaokun & Deng, Pengru & Zhang, Hongfu, 2023. "High-fidelity wind turbine wake velocity prediction by surrogate model based on d-POD and LSTM," Energy, Elsevier, vol. 275(C).
    5. He, J.Y. & Chan, P.W. & Li, Q.S. & Tong, H.W., 2023. "Mapping future offshore wind resources in the South China Sea under climate change by regional climate modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).

    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. Zhou, Lei & Wen, Jiahao & Wang, Zhaokun & Deng, Pengru & Zhang, Hongfu, 2023. "High-fidelity wind turbine wake velocity prediction by surrogate model based on d-POD and LSTM," Energy, Elsevier, vol. 275(C).
    2. Zhu, Xiaoxun & Chen, Yao & Xu, Shinai & Zhang, Shaohai & Gao, Xiaoxia & Sun, Haiying & Wang, Yu & Zhao, Fei & Lv, Tiancheng, 2023. "Three-dimensional non-uniform full wake characteristics for yawed wind turbine with LiDAR-based experimental verification," Energy, Elsevier, vol. 270(C).
    3. He, Ruiyang & Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2022. "Wind tunnel tests for wind turbines: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    4. Xu, Zongyuan & Gao, Xiaoxia & Zhang, Huanqiang & Lv, Tao & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu, 2023. "Analysis of the anisotropy aerodynamic characteristics of downstream wind turbine considering the 3D wake expansion based on coupling method," Energy, Elsevier, vol. 263(PD).
    5. Zhang, Sanxia & Luo, Kun & Yuan, Renyu & Wang, Qiang & Wang, Jianwen & Zhang, Liru & Fan, Jianren, 2018. "Influences of operating parameters on the aerodynamics and aeroacoustics of a horizontal-axis wind turbine," Energy, Elsevier, vol. 160(C), pages 597-611.
    6. Wang, Tengyuan & Cai, Chang & Wang, Xinbao & Wang, Zekun & Chen, Yewen & Song, Juanjuan & Xu, Jianzhong & Zhang, Yuning & Li, Qingan, 2023. "A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow," Energy, Elsevier, vol. 271(C).
    7. Liu, Weiqi & Shi, Jian & Chen, Hailong & Liu, Hengxu & Lin, Zi & Wang, Lingling, 2021. "Lagrangian actuator model for wind turbine wake aerodynamics," Energy, Elsevier, vol. 232(C).
    8. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Experimental investigation of the performance and wake effect of a small-scale wind turbine in a wind tunnel," Energy, Elsevier, vol. 166(C), pages 819-833.
    9. Majid Bastankhah & Fernando Porté-Agel, 2017. "A New Miniature Wind Turbine for Wind Tunnel Experiments. Part I: Design and Performance," Energies, MDPI, vol. 10(7), pages 1-19, July.
    10. Yang, Haoze & Ge, Mingwei & Gu, Bo & Du, Bowen & Liu, Yongqian, 2022. "The effect of swell on marine atmospheric boundary layer and the operation of an offshore wind turbine," Energy, Elsevier, vol. 244(PB).
    11. Yang, Haoze & Ge, Mingwei & Abkar, Mahdi & Yang, Xiang I.A., 2022. "Large-eddy simulation study of wind turbine array above swell sea," Energy, Elsevier, vol. 256(C).
    12. Bingzheng Dou & Zhanpei Yang & Michele Guala & Timing Qu & Liping Lei & Pan Zeng, 2020. "Comparison of Different Driving Modes for the Wind Turbine Wake in Wind Tunnels," Energies, MDPI, vol. 13(8), pages 1-17, April.
    13. Xiaoxia, Gao & Luqing, Li & Shaohai, Zhang & Xiaoxun, Zhu & Haiying, Sun & Hongxing, Yang & Yu, Wang & Hao, Lu, 2022. "LiDAR-based observation and derivation of large-scale wind turbine's wake expansion model downstream of a hill," Energy, Elsevier, vol. 259(C).
    14. Liang, Xiaoling & Fu, Shifeng & Cai, Fulin & Han, Xingxing & Zhu, Weijun & Yang, Hua & Shen, Wenzhong, 2023. "Experimental investigation on wake characteristics of wind turbine and a new two-dimensional wake model," Renewable Energy, Elsevier, vol. 203(C), pages 373-381.
    15. Kaldellis, John K. & Triantafyllou, Panagiotis & Stinis, Panagiotis, 2021. "Critical evaluation of Wind Turbines’ analytical wake models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    16. Sun, Chong & Tian, Tian & Zhu, Xiaocheng & Hua, Ouyang & Du, Zhaohui, 2021. "Investigation of the near wake of a horizontal-axis wind turbine model by dynamic mode decomposition," Energy, Elsevier, vol. 227(C).
    17. Hongtao Niu & Congxin Yang & Yin Wang, 2023. "Experimental Study on the Influence of Incoming Flow on Wind Turbine Power and Wake Based on Wavelet Analysis," Energies, MDPI, vol. 16(16), pages 1-15, August.
    18. Wang, Zhenyu & Ozbay, Ahmet & Tian, Wei & Hu, Hui, 2018. "An experimental study on the aerodynamic performances and wake characteristics of an innovative dual-rotor wind turbine," Energy, Elsevier, vol. 147(C), pages 94-109.
    19. Zhang, Shaohai & Gao, Xiaoxia & Ma, Wanli & Lu, Hongkun & Lv, Tao & Xu, Shinai & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu, 2023. "Derivation and verification of three-dimensional wake model of multiple wind turbines based on super-Gaussian function," Renewable Energy, Elsevier, vol. 215(C).
    20. Liu, Weiqi & Liu, Weixing & Zhang, Liang & Sheng, Qihu & Zhou, Binzhen, 2018. "A numerical model for wind turbine wakes based on the vortex filament method," Energy, Elsevier, vol. 157(C), pages 561-570.

    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:eee:energy:v:263:y:2023:i:pa:s0360544222025786. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.