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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
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    References listed on IDEAS

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    1. Singh, Ronit K. & Ahmed, M. Rafiuddin, 2013. "Blade design and performance testing of a small wind turbine rotor for low wind speed applications," Renewable Energy, Elsevier, vol. 50(C), pages 812-819.
    2. 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.
    3. Avallone, Francesco & Ragni, Daniele & Casalino, Damiano, 2020. "On the effect of the tip-clearance ratio on the aeroacoustics of a diffuser-augmented wind turbine," Renewable Energy, Elsevier, vol. 152(C), pages 1317-1327.
    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. Khamlaj, Tariq Abdulsalam & Rumpfkeil, Markus Peer, 2018. "Analysis and optimization of ducted wind turbines," Energy, Elsevier, vol. 162(C), pages 1234-1252.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. 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).
    12. 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.
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