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Numerical Investigation of the Aeroelastic Behavior of a Wind Turbine with Iced Blades

Author

Listed:
  • Sudhakar Gantasala

    (Computer-Aided Design, Division of Product and Production Development, Department of Engineering Sciences and Mathematics, Luleå University of Technology, 97187 Luleå, Sweden)

  • Narges Tabatabaei

    (Fluid Mechanics, Division of Fluid and Experimental Mechanics, Department of Engineering Sciences and Mathematics, Luleå University of Technology, 97187 Luleå, Sweden)

  • Michel Cervantes

    (Fluid Mechanics, Division of Fluid and Experimental Mechanics, Department of Engineering Sciences and Mathematics, Luleå University of Technology, 97187 Luleå, Sweden)

  • Jan-Olov Aidanpää

    (Computer-Aided Design, Division of Product and Production Development, Department of Engineering Sciences and Mathematics, Luleå University of Technology, 97187 Luleå, Sweden)

Abstract

Wind turbines installed in cold-climate regions are prone to the risks of ice accumulation which affects their aeroelastic behavior. The studies carried out on this topic so far considered icing in a few sections of the blade, mostly located in the outer part of the blade, and their influence on the loads and power production of the turbine are only analyzed. The knowledge about the influence of icing in different locations of the blade and asymmetrical icing of the blades on loads, power, and vibration behavior of the turbine is still not matured. To improve this knowledge, multiple simulation cases are needed to run with different ice accumulations on the blade considering structural and aerodynamic property changes due to ice. Such simulations can be easily run by automating the ice shape creation on aerofoil sections and two-dimensional (2-D) Computational Fluid Dynamics (CFD) analysis of those sections. The current work proposes such methodology and it is illustrated on the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine model. The influence of symmetrical icing in different locations of the blade and asymmetrical icing of the blade assembly is analyzed on the turbine’s dynamic behavior using the aeroelastic computer-aided engineering tool FAST. The outer third of the blade produces about 50% of the turbine’s total power and severe icing in this part of the blade reduces power output and aeroelastic damping of the blade’s flapwise vibration modes. The increase in blade mass due to ice reduces its natural frequencies which can be extracted from the vibration responses of the turbine operating under turbulent wind conditions. Symmetrical icing of the blades reduces loads acting on the turbine components, whereas asymmetrical icing of the blades induces loads and vibrations in the tower, hub, and nacelle assembly at a frequency synchronous to rotational speed of the turbine.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2422-:d:242466
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    References listed on IDEAS

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    1. Peter J. Schubel & Richard J. Crossley, 2012. "Wind Turbine Blade Design," Energies, MDPI, vol. 5(9), pages 1-25, September.
    2. 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.
    3. Tomas Wallenius & Ville Lehtomäki, 2016. "Overview of cold climate wind energy: challenges, solutions, and future needs," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(2), pages 128-135, March.
    4. Hu, Liangquan & Zhu, Xiaocheng & Hu, Chenxing & Chen, Jinge & Du, Zhaohui, 2017. "Wind turbines ice distribution and load response under icing conditions," Renewable Energy, Elsevier, vol. 113(C), pages 608-619.
    5. Sudhakar Gantasala & Jean-Claude Luneno & Jan-Olov Aidanpää, 2016. "Influence of Icing on the Modal Behavior of Wind Turbine Blades," Energies, MDPI, vol. 9(11), pages 1-14, October.
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    Citations

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    Cited by:

    1. Yanpeng Hao & Zhaohong Yao & Junke Wang & Hao Li & Ruihai Li & Lin Yang & Wei Liang, 2019. "A Classification Method for Transmission Line Icing Process Curve Based on Hierarchical K-Means Clustering," Energies, MDPI, vol. 12(24), pages 1-14, December.
    2. Dimitris Al. Katsaprakakis & Nikos Papadakis & Ioannis Ntintakis, 2021. "A Comprehensive Analysis of Wind Turbine Blade Damage," Energies, MDPI, vol. 14(18), pages 1-31, September.
    3. Santhanam, Chandramouli & Riva, Riccardo & Knudsen, Torben, 2023. "A study of Stall-Induced Vibrations using Surrogate-Based Optimization," Renewable Energy, Elsevier, vol. 214(C), pages 201-215.
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    5. Viktor Elistratov & Mikhail Konishchev & Roman Denisov & Inna Bogun & Aki Grönman & Teemu Turunen-Saaresti & Afonso Julian Lugo, 2021. "Study of the Intelligent Control and Modes of the Arctic-Adopted Wind–Diesel Hybrid System," Energies, MDPI, vol. 14(14), pages 1-14, July.
    6. Valery Okulov & Ivan Kabardin & Dmitry Mukhin & Konstantin Stepanov & Nastasia Okulova, 2021. "Physical De-Icing Techniques for Wind Turbine Blades," Energies, MDPI, vol. 14(20), pages 1-16, October.
    7. Marcin Augustyn & Filip Lisowski, 2023. "Experimental and Numerical Studies on a Single Coherent Blade of a Vertical Axis Carousel Wind Rotor," Energies, MDPI, vol. 16(14), pages 1-17, July.
    8. Hongmei Cui & Zhongyang Li & Bingchuan Sun & Teng Fan & Yonghao Li & Lida Luo & Yong Zhang & Jian Wang, 2022. "A New Ice Quality Prediction Method of Wind Turbine Impeller Based on the Deep Neural Network," Energies, MDPI, vol. 15(22), pages 1-18, November.

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