IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i9p3648-d1383758.html
   My bibliography  Save this article

Optimization Based on Computational Fluid Dynamics and Machine Learning for the Performance of Diffuser-Augmented Wind Turbines with Inlet Shrouds

Author

Listed:
  • Po-Wen Hwang

    (Department of Aerospace and Systems Engineering, Feng Chia University, Taichung 407102, Taiwan)

  • Jia-Heng Wu

    (Department of Aerospace and Systems Engineering, Feng Chia University, Taichung 407102, Taiwan)

  • Yuan-Jen Chang

    (Department of Aerospace and Systems Engineering, Feng Chia University, Taichung 407102, Taiwan)

Abstract

A methodology that could reduce computational cost and time, combining computational fluid dynamics (CFD) simulations, neural networks, and genetic algorithms to determine a diffuser-augmented wind turbine (DAWT) design is proposed. The specific approach used implements a CFD simulation validated with experimental data, and key parameters are analyzed to generate datasets for the relevant mathematical model established with the backpropagation neural network algorithm. Then, the mathematical model is used with the non-dominant sorting genetic algorithm II to optimize the design and improve the DAWT design to overcome negative constraints such as noise and low energy density. The key parameters adopted are the diffuser’s flange height/angle, the diffuser’s length, and the rotor’s axial position. It was found that the impact of the rotor’s axial position on the power output of the DAWT is the most significant parameter, and a well-designed diffuser requires accelerating the airflow while maintaining high-pressure recovery. Introducing a diffuser can suppress the wind turbine’s noise, but if the induced tip vortex is too strong, it will have the opposite effect on the noise reduction.

Suggested Citation

  • Po-Wen Hwang & Jia-Heng Wu & Yuan-Jen Chang, 2024. "Optimization Based on Computational Fluid Dynamics and Machine Learning for the Performance of Diffuser-Augmented Wind Turbines with Inlet Shrouds," Sustainability, MDPI, vol. 16(9), pages 1-31, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3648-:d:1383758
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/9/3648/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/9/3648/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Heikal, Hasim A. & Abu-Elyazeed, Osayed S.M. & Nawar, Mohamed A.A. & Attai, Youssef A. & Mohamed, Maged M.S., 2018. "On the actual power coefficient by theoretical developing of the diffuser flange of wind-lens turbine," Renewable Energy, Elsevier, vol. 125(C), pages 295-305.
    2. Thuy-Anh Nguyen & Hai-Bang Ly & Binh Thai Pham, 2020. "Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, December.
    3. Koichi Watanabe & Yuji Ohya, 2021. "A Simple Theory and Performance Prediction for a Shrouded Wind Turbine with a Brimmed Diffuser," Energies, MDPI, vol. 14(12), pages 1-15, June.
    4. Hashem, I. & Mohamed, M.H. & Hafiz, A.A., 2017. "Aero-acoustics noise assessment for Wind-Lens turbine," Energy, Elsevier, vol. 118(C), pages 345-368.
    5. Rahmatian, Mohammad Ali & Nazarian Shahrbabaki, Amin & Moeini, Seyed Peyman, 2023. "Single-objective optimization design of convergent-divergent ducts of ducted wind turbine using RSM and GA, to increase power coefficient of a small-scale horizontal axis wind turbine," Energy, Elsevier, vol. 269(C).
    6. Nunes, Matheus M. & Brasil Junior, Antonio C.P. & Oliveira, Taygoara F., 2020. "Systematic review of diffuser-augmented horizontal-axis turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    7. Khamlaj, Tariq Abdulsalam & Rumpfkeil, Markus Peer, 2018. "Analysis and optimization of ducted wind turbines," Energy, Elsevier, vol. 162(C), pages 1234-1252.
    8. Liu, Jie & Song, Mengxuan & Chen, Kai & Wu, Bingheng & Zhang, Xing, 2016. "An optimization methodology for wind lens profile using Computational Fluid Dynamics simulation," Energy, Elsevier, vol. 109(C), pages 602-611.
    9. Leloudas, Stavros N. & Lygidakis, Georgios N. & Eskantar, Alexandros I. & Nikolos, Ioannis K., 2020. "A robust methodology for the design optimization of diffuser augmented wind turbine shrouds," Renewable Energy, Elsevier, vol. 150(C), pages 722-742.
    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. Abdel Hameed, Hossam S. & Hashem, Islam & Nawar, Mohamed A.A. & Attai, Youssef A. & Mohamed, Mohamed H., 2023. "Shape optimization of a shrouded Archimedean-spiral type wind turbine for small-scale applications," Energy, Elsevier, vol. 263(PB).
    2. Hamid, Hossam & Mohamed Abd El Maksoud, Rafea, 2024. "An optimization study of passive flow control mechanism for a seashell-shaped wind turbine," Energy, Elsevier, vol. 289(C).
    3. Rahmatian, Mohammad Ali & Khaksar, Saba & Tari, Pooyan Hashemi & Karbasian, Hamid Reza, 2024. "Optimizing duct geometry for micro-scale VAWTs: Exploring aerodynamics and aeroacoustics with URANS and DDES models," Energy, Elsevier, vol. 313(C).
    4. Nunes, Matheus M. & Brasil Junior, Antonio C.P. & Oliveira, Taygoara F., 2020. "Systematic review of diffuser-augmented horizontal-axis turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    5. Rezek, Thiago J. & Camacho, Ramiro G.R. & Manzanares-Filho, Nelson, 2023. "A novel methodology for the design of diffuser-augmented hydrokinetic rotors," Renewable Energy, Elsevier, vol. 210(C), pages 524-539.
    6. Kuang, Limin & Su, Jie & Chen, Yaoran & Han, Zhaolong & Zhou, Dai & Zhang, Kai & Zhao, Yongsheng & Bao, Yan, 2022. "Wind-capture-accelerate device for performance improvement of vertical-axis wind turbines: External diffuser system," Energy, Elsevier, vol. 239(PB).
    7. Rahmatian, Mohammad Ali & Hashemi Tari, Pooyan & Majidi, Sahand & Mojaddam, Mohammad, 2023. "Experimental study of the effect of the duct on dual co-axial horizontal axis wind turbines and the effect of rotors diameter ratio and distance on increasing power coefficient," Energy, Elsevier, vol. 284(C).
    8. Ali, Qazi Shahzad & Kim, Man-Hoe, 2022. "Power conversion performance of airborne wind turbine under unsteady loads," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    9. Maduka, Maduka & Li, Chi Wai, 2022. "Experimental evaluation of power performance and wake characteristics of twin flanged duct turbines in tandem under bi-directional tidal flows," Renewable Energy, Elsevier, vol. 199(C), pages 1543-1567.
    10. Silva, Paulo A.S.F. & Tsoutsanis, Panagiotis & Vaz, Jerson R.P. & Macias, Marianela M., 2024. "A comprehensive CFD investigation of tip vortex trajectory in shrouded wind turbines using compressible RANS solver," Energy, Elsevier, vol. 294(C).
    11. Rahmatian, Mohammad Ali & Hashemi Tari, Pooyan & Mojaddam, Mohammad & Majidi, Sahand, 2022. "Numerical and experimental study of the ducted diffuser effect on improving the aerodynamic performance of a micro horizontal axis wind turbine," Energy, Elsevier, vol. 245(C).
    12. Khamlaj, Tariq Abdulsalam & Rumpfkeil, Markus Peer, 2018. "Analysis and optimization of ducted wind turbines," Energy, Elsevier, vol. 162(C), pages 1234-1252.
    13. Leloudas, Stavros N. & Lygidakis, Georgios N. & Eskantar, Alexandros I. & Nikolos, Ioannis K., 2020. "A robust methodology for the design optimization of diffuser augmented wind turbine shrouds," Renewable Energy, Elsevier, vol. 150(C), pages 722-742.
    14. Kaseb, Z. & Montazeri, H., 2022. "Data-driven optimization of building-integrated ducted openings for wind energy harvesting: Sensitivity analysis of metamodels," Energy, Elsevier, vol. 258(C).
    15. Koichi Watanabe & Yuji Ohya, 2021. "A Simple Theory and Performance Prediction for a Shrouded Wind Turbine with a Brimmed Diffuser," Energies, MDPI, vol. 14(12), pages 1-15, June.
    16. Antonio García Auyanet & Patrick G. Verdin, 2022. "Numerical Study of the Effect of Flap Geometry in a Multi-Slot Ducted Wind Turbine," Sustainability, MDPI, vol. 14(19), pages 1-17, September.
    17. Ghorani, Mohammad Mahdi & Karimi, Behrooz & Mirghavami, Seyed Mohammad & Saboohi, Zoheir, 2023. "A numerical study on the feasibility of electricity production using an optimized wind delivery system (Invelox) integrated with a Horizontal axis wind turbine (HAWT)," Energy, Elsevier, vol. 268(C).
    18. Ngwarai Shambira & Golden Makaka & Patrick Mukumba, 2024. "Velocity Augmentation Model for an Empty Concentrator-Diffuser-Augmented Wind Turbine and Optimisation of Geometrical Parameters Using Surface Response Methodology," Sustainability, MDPI, vol. 16(4), pages 1-30, February.
    19. Koichi Watanabe & Yuji Ohya & Takanori Uchida, 2019. "Power Output Enhancement of a Ducted Wind Turbine by Stabilizing Vortices around the Duct," Energies, MDPI, vol. 12(16), pages 1-17, August.
    20. Mohammad Hassan Ranjbar & Behnam Rafiei & Seyyed Abolfazl Nasrazadani & Kobra Gharali & Madjid Soltani & Armughan Al-Haq & Jatin Nathwani, 2021. "Power Enhancement of a Vertical Axis Wind Turbine Equipped with an Improved Duct," Energies, MDPI, vol. 14(18), pages 1-16, September.

    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:jsusta:v:16:y:2024:i:9:p:3648-:d:1383758. 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.