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Quantifying the effect of vortex generator installation on wind power production: An academia-industry case study

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  • Hwangbo, Hoon
  • Ding, Yu
  • Eisele, Oliver
  • Weinzierl, Guido
  • Lang, Ulrich
  • Pechlivanoglou, Georgios

Abstract

This paper presents an academia-industry joint study concerning effective methods to estimate and quantify the effect of vortex generator installation on wind power production. This problem has presented a challenge to the wind industry, because (a) vortex generator installation may lead to a moderate 1–5% extra power production, but this level of improvement is difficult to be accurately detected; and (b) it is equally difficult to validate the estimated effect of vortex generator installation because a controlled experiment is practically impossible to conduct to provide a credible baseline. An academic institute and a wind technology company team up to tackle this challenge. The two teams develop their own version of quantification methods, which are profoundly different. The academic method uses 10-min data and makes use of both power and environmental data, whereas the company method uses high-frequency data via primarily a direct power comparison approach that relies less on the environmental data. When applying the respective methods to two inland wind farms, each of which presents four pairs of turbines, the quantification results from the two methods are surprisingly consistent. We believe the consistent outcome presents a strong case of cross validation, testifying to the respective method's capability and credibility.

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  • Hwangbo, Hoon & Ding, Yu & Eisele, Oliver & Weinzierl, Guido & Lang, Ulrich & Pechlivanoglou, Georgios, 2017. "Quantifying the effect of vortex generator installation on wind power production: An academia-industry case study," Renewable Energy, Elsevier, vol. 113(C), pages 1589-1597.
    • Handle: RePEc:eee:renene:v:113:y:2017:i:c:p:1589-1597
    DOI: 10.1016/j.renene.2017.07.009
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    1. Giwhyun Lee & Yu Ding & Marc G. Genton & Le Xie, 2015. "Power Curve Estimation With Multivariate Environmental Factors for Inland and Offshore Wind Farms," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 56-67, March.
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    2. Ding, Yu & Kumar, Nitesh & Prakash, Abhinav & Kio, Adaiyibo E. & Liu, Xin & Liu, Lei & Li, Qingchang, 2021. "A case study of space-time performance comparison of wind turbines on a wind farm," Renewable Energy, Elsevier, vol. 171(C), pages 735-746.
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    4. Unai Fernandez-Gamiz & Macarena Gomez-Mármol & Tomas Chacón-Rebollo, 2018. "Computational Modeling of Gurney Flaps and Microtabs by POD Method," Energies, MDPI, vol. 11(8), pages 1-19, August.
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    7. Davide Astolfi & Raymond Byrne & Francesco Castellani, 2020. "Analysis of Wind Turbine Aging through Operation Curves," Energies, MDPI, vol. 13(21), pages 1-21, October.
    8. Moon, Hyeongi & Jeong, Junhee & Park, Sunho & Ha, Kwangtae & Jeong, Jae-Ho, 2023. "Numerical and experimental validation of vortex generator effect on power performance improvement in MW-class wind turbine blade," Renewable Energy, Elsevier, vol. 212(C), pages 443-454.
    9. Davide Astolfi & Francesco Castellani & Ludovico Terzi, 2018. "Wind Turbine Power Curve Upgrades," Energies, MDPI, vol. 11(5), pages 1-17, May.
    10. Davide Astolfi & Francesco Castellani, 2019. "Wind Turbine Power Curve Upgrades: Part II," Energies, MDPI, vol. 12(8), pages 1-20, April.
    11. Zaki, Abanoub & Abdelrahman, M.A. & Ayad, Samir S. & Abdellatif, O.E., 2022. "Effects of leading edge slat on the aerodynamic performance of low Reynolds number horizontal axis wind turbine," Energy, Elsevier, vol. 239(PD).
    12. Davide Astolfi & Francesco Castellani & Matteo Becchetti & Andrea Lombardi & Ludovico Terzi, 2020. "Wind Turbine Systematic Yaw Error: Operation Data Analysis Techniques for Detecting It and Assessing Its Performance Impact," Energies, MDPI, vol. 13(9), pages 1-17, May.
    13. Shafiqur Rehman & Md. Mahbub Alam & Luai M. Alhems & M. Mujahid Rafique, 2018. "Horizontal Axis Wind Turbine Blade Design Methodologies for Efficiency Enhancement—A Review," Energies, MDPI, vol. 11(3), pages 1-34, February.
    14. Md Zishan Akhter & Farag Khalifa Omar, 2021. "Review of Flow-Control Devices for Wind-Turbine Performance Enhancement," Energies, MDPI, vol. 14(5), pages 1-35, February.
    15. Manolesos, M. & Chng, L. & Kaufmann, N. & Ouro, P. & Ntouras, D. & Papadakis, G., 2023. "Using vortex generators for flow separation control on tidal turbine profiles and blades," Renewable Energy, Elsevier, vol. 205(C), pages 1025-1039.
    16. Francesco Castellani & Ravi Pandit & Francesco Natili & Francesca Belcastro & Davide Astolfi, 2023. "Advanced Methods for Wind Turbine Performance Analysis Based on SCADA Data and CFD Simulations," Energies, MDPI, vol. 16(3), pages 1-15, January.
    17. Zhu, Haitian & Hao, Wenxing & Li, Chun & Ding, Qinwei & Wu, Baihui, 2018. "A critical study on passive flow control techniques for straight-bladed vertical axis wind turbine," Energy, Elsevier, vol. 165(PA), pages 12-25.
    18. Zhong, Junwei & Li, Jingyin & Liu, Huizhong, 2023. "Dynamic mode decomposition analysis of flow separation control on wind turbine airfoil using leading−edge rod," Energy, Elsevier, vol. 268(C).

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