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Wind energy harnessing of the NREL 5 MW reference wind turbine in icing conditions under different operational strategies

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  • Zanon, Alessandro
  • De Gennaro, Michele
  • Kühnelt, Helmut

Abstract

Icing is a strong limitation for the performance of wind turbines in cold climates and the prediction of the performance loss due to ice accretion is essential for designing effective ice mitigation measures. This paper presents a numerical approach capable of simulating the ice accretion transient phenomenon and its effects on wind turbine performance. This approach is applied to the NREL 5 MW reference wind turbine to predict (i) its performance during and after an icing event lasting for 8 h and (ii) the potential improvement in energy harnessing due to different operational strategies. The results show that by decreasing the turbine rotational speed and accepting a slight energy conversion decrease during the icing event, the performance can improve up to 6% when full operation is restored compared to the baseline operational strategy. Whereas, sustaining the rotational speed during the icing event can generate a 3% of performance loss afterwards compared to the same baseline. The developed workflow can be used for optimising performance of wind turbines by accounting for environmental conditions, the duration of the icing event, and performance after the icing event itself, thus constituting a valuable tool to maximise profitability of wind turbines in cold climates.

Suggested Citation

  • Zanon, Alessandro & De Gennaro, Michele & Kühnelt, Helmut, 2018. "Wind energy harnessing of the NREL 5 MW reference wind turbine in icing conditions under different operational strategies," Renewable Energy, Elsevier, vol. 115(C), pages 760-772.
    • Handle: RePEc:eee:renene:v:115:y:2018:i:c:p:760-772
    DOI: 10.1016/j.renene.2017.08.076
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    References listed on IDEAS

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    1. Kraj, Andrea G. & Bibeau, Eric L., 2010. "Phases of icing on wind turbine blades characterized by ice accumulation," Renewable Energy, Elsevier, vol. 35(5), pages 966-972.
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    Cited by:

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    2. Jokar, H. & Mahzoon, M. & Vatankhah, R., 2020. "Dynamic modeling and free vibration analysis of horizontal axis wind turbine blades in the flap-wise direction," Renewable Energy, Elsevier, vol. 146(C), pages 1818-1832.
    3. Akintayo T. Abolude & Wen Zhou, 2018. "A Comparative Computational Fluid Dynamic Study on the Effects of Terrain Type on Hub-Height Wind Aerodynamic Properties," Energies, MDPI, vol. 12(1), pages 1-14, December.
    4. Gao, Linyue & Tao, Tao & Liu, Yongqian & Hu, Hui, 2021. "A field study of ice accretion and its effects on the power production of utility-scale wind turbines," Renewable Energy, Elsevier, vol. 167(C), pages 917-928.
    5. Sudhakar Gantasala & Narges Tabatabaei & Michel Cervantes & Jan-Olov Aidanpää, 2019. "Numerical Investigation of the Aeroelastic Behavior of a Wind Turbine with Iced Blades," Energies, MDPI, vol. 12(12), pages 1-24, June.
    6. Stoyanov, D.B. & Nixon, J.D. & Sarlak, H., 2021. "Analysis of derating and anti-icing strategies for wind turbines in cold climates," Applied Energy, Elsevier, vol. 288(C).
    7. Fahed Martini & Hussein Ibrahim & Leidy Tatiana Contreras Montoya & Patrick Rizk & Adrian Ilinca, 2022. "Turbulence Modeling of Iced Wind Turbine Airfoils," Energies, MDPI, vol. 15(22), pages 1-20, November.
    8. Papi, Francesco & Balduzzi, Francesco & Ferrara, Giovanni & Bianchini, Alessandro, 2021. "Uncertainty quantification on the effects of rain-induced erosion on annual energy production and performance of a Multi-MW wind turbine," Renewable Energy, Elsevier, vol. 165(P1), pages 701-715.
    9. Abel Arredondo-Galeana & Feargal Brennan, 2021. "Floating Offshore Vertical Axis Wind Turbines: Opportunities, Challenges and Way Forward," Energies, MDPI, vol. 14(23), pages 1-24, November.
    10. Fahed Martini & Adrian Ilinca & Patrick Rizk & Hussein Ibrahim & Mohamad Issa, 2022. "A Survey of the Quasi-3D Modeling of Wind Turbine Icing," Energies, MDPI, vol. 15(23), pages 1-32, November.
    11. Ma, Liqun & Zhang, Zichen & Gao, Linyue & Liu, Yang & Hu, Hui, 2020. "An exploratory study on using Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation," Renewable Energy, Elsevier, vol. 162(C), pages 2344-2360.
    12. Wang, Xuefei & Zeng, Xiangwu & Li, Xinyao & Li, Jiale, 2019. "Investigation on offshore wind turbine with an innovative hybrid monopile foundation: An experimental based study," Renewable Energy, Elsevier, vol. 132(C), pages 129-141.
    13. Guo, Wenfeng & Shen, He & Li, Yan & Feng, Fang & Tagawa, Kotaro, 2021. "Wind tunnel tests of the rime icing characteristics of a straight-bladed vertical axis wind turbine," Renewable Energy, Elsevier, vol. 179(C), pages 116-132.
    14. Akintayo Temiloluwa Abolude & Wen Zhou, 2018. "Assessment and Performance Evaluation of a Wind Turbine Power Output," Energies, MDPI, vol. 11(8), pages 1-15, August.
    15. Yang, Muchen & Xiao, Zhixiang, 2019. "Distributed roughness induced transition on wind-turbine airfoils simulated by four-equation k-ω-γ-Ar transition model," Renewable Energy, Elsevier, vol. 135(C), pages 1166-1177.
    16. Jiménez, Alfredo Arcos & García Márquez, Fausto Pedro & Moraleda, Victoria Borja & Gómez Muñoz, Carlos Quiterio, 2019. "Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis," Renewable Energy, Elsevier, vol. 132(C), pages 1034-1048.
    17. Xiaoyi Qian & Yuxian Zhang & Mohammed Gendeel, 2019. "State Rules Mining and Probabilistic Fault Analysis for 5 MW Offshore Wind Turbines," Energies, MDPI, vol. 12(11), pages 1-18, May.
    18. Dong, Weiwei & Zhao, Guohua & Yüksel, Serhat & Dinçer, Hasan & Ubay, Gözde Gülseven, 2022. "A novel hybrid decision making approach for the strategic selection of wind energy projects," Renewable Energy, Elsevier, vol. 185(C), pages 321-337.

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