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Assessment of Correction Methods Applied to BEMT for Predicting Performance of Horizontal-Axis Wind Turbines

Author

Listed:
  • Hércules Araújo Oliveira

    (Institute of Electrical Engineering, Federal University of Maranhão, São Luís 65080-805, Brazil)

  • José Gomes de Matos

    (Institute of Electrical Engineering, Federal University of Maranhão, São Luís 65080-805, Brazil)

  • Luiz Antonio de Souza Ribeiro

    (Institute of Electrical Engineering, Federal University of Maranhão, São Luís 65080-805, Brazil)

  • Osvaldo Ronald Saavedra

    (Institute of Electrical Engineering, Federal University of Maranhão, São Luís 65080-805, Brazil)

  • Jerson Rogério Pinheiro Vaz

    (Faculty of Energy Engineering, Federal University of Pará, Belém 66075-110, Brazil)

Abstract

Blade Element Momentum Theory (BEMT) is the most used method to design horizontal-axis wind turbines worldwide. This is because BEMT has a low computational cost and easy numerical implementation. Additionally, it is demonstrated in the literature that the prediction of output power using BEMT agrees well with experimental data. Another important feature of the BEMT is its applicability to small, medium, and large-sized turbines. However, BEMT models are usually implemented and adjusted for a specific power range turbine, and they are not applied in a more general form. Thus, this article presents an analysis of additional correction methods for tip and root losses, high values of the axial induction factor, and high angle of attack to better represent horizontal-axis turbines in terms of numerical stability. The approach has the intention of combining several complementary correction methods strategically inserted in the BEMT in order to compile an algorithm that is more general, stable, and workable for any turbine size. The main contribution of this work is to propose a stable BEMT numerical algorithm through the assessment of the combination of the correction methods available in the literature, i.e., classical and modern ones. The algorithm ensures applicability for small, medium, and large-sized wind turbines, as well as being fast and easy to implement in any computer and extendable even to turbines with a diffuser. This approach is validated by comparing the results with experimental data from four turbines of different power ranges (1.9 kW to 7.3 MW). The results show the best approximations for performance power curves against the measured values of all turbines. Moreover, it is effective, less complex, and quick in analyzing the performance of those turbines. Furthermore, the need for high-performance computers to analyze the performance of horizontal-axis turbines is avoided.

Suggested Citation

  • Hércules Araújo Oliveira & José Gomes de Matos & Luiz Antonio de Souza Ribeiro & Osvaldo Ronald Saavedra & Jerson Rogério Pinheiro Vaz, 2023. "Assessment of Correction Methods Applied to BEMT for Predicting Performance of Horizontal-Axis Wind Turbines," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:7021-:d:1129829
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    References listed on IDEAS

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    1. Wood, D.H. & Okulov, V.L. & Bhattacharjee, D., 2016. "Direct calculation of wind turbine tip loss," Renewable Energy, Elsevier, vol. 95(C), pages 269-276.
    2. Bavanish, B. & Thyagarajan, K., 2013. "Optimization of power coefficient on a horizontal axis wind turbine using bem theory," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 169-182.
    3. 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.
    4. Bai, Chi-Jeng & Wang, Wei-Cheng, 2016. "Review of computational and experimental approaches to analysis of aerodynamic performance in horizontal-axis wind turbines (HAWTs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 506-519.
    5. Wood, D.H., 2018. "Application of extended vortex theory for blade element analysis of horizontal-axis wind turbines," Renewable Energy, Elsevier, vol. 121(C), pages 188-194.
    6. Bangga, Galih & Lutz, Thorsten, 2021. "Aerodynamic modeling of wind turbine loads exposed to turbulent inflow and validation with experimental data," Energy, Elsevier, vol. 223(C).
    7. Wood, D.H. & Okulov, V.L., 2017. "Nonlinear blade element-momentum analysis of Betz-Goldstein rotors," Renewable Energy, Elsevier, vol. 107(C), pages 542-549.
    8. Martin, Sean & Jung, Sungmoon & Vanli, Arda, 2020. "Impact of near-future turbine technology on the wind power potential of low wind regions," Applied Energy, Elsevier, vol. 272(C).
    9. MacPhee, David W. & Beyene, Asfaw, 2019. "Performance analysis of a small wind turbine equipped with flexible blades," Renewable Energy, Elsevier, vol. 132(C), pages 497-508.
    10. Chen, Jincheng & Wang, Feng & Stelson, Kim A., 2018. "A mathematical approach to minimizing the cost of energy for large utility wind turbines," Applied Energy, Elsevier, vol. 228(C), pages 1413-1422.
    11. 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.
    12. Yin, Minghui & Yang, Zhiqiang & Xu, Yan & Liu, Jiankun & Zhou, Lianjun & Zou, Yun, 2018. "Aerodynamic optimization for variable-speed wind turbines based on wind energy capture efficiency," Applied Energy, Elsevier, vol. 221(C), pages 508-521.
    13. Yang, Hua & Shen, Wenzhong & Xu, Haoran & Hong, Zedong & Liu, Chao, 2014. "Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD," Renewable Energy, Elsevier, vol. 70(C), pages 107-115.
    14. Ji, Baifeng & Zhong, Kuanwei & Xiong, Qian & Qiu, Penghui & Zhang, Xu & Wang, Liang, 2022. "CFD simulations of aerodynamic characteristics for the three-blade NREL Phase VI wind turbine model," Energy, Elsevier, vol. 249(C).
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    Cited by:

    1. Wenyan Li & Yuxuan Xiong & Guoliang Su & Zuyang Ye & Guowu Wang & Zhao Chen, 2023. "The Aerodynamic Performance of Horizontal Axis Wind Turbines under Rotation Condition," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    2. Mauro J. Guerreiro Veloso & Carlos H. P. dos Santos & Jerson R. P. Vaz & Antonio M. Chaves Neto, 2023. "Quasi-Steady Analysis of a Small Wind Rotor with Swept Blades," Sustainability, MDPI, vol. 15(13), pages 1-21, June.

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