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Dynamic aeroelastic behavior of wind turbine rotors in rapid pitch-control actions

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  • Menon, Muraleekrishnan
  • Ponta, Fernando L.

Abstract

Pitch control comprises a significant proportion of current wind turbine load-control approaches. Collective pitching is used in restricting the overall power generation at high winds, whereas individual pitching has the added advantage of mitigating cyclic loads that are detrimental in fatigue damage of the turbines. Currently, there are many studies on conventional pitching control that account for long-term variations in wind speeds and associated high loads, but a smaller number of studies in short-term pitch action.

Suggested Citation

  • Menon, Muraleekrishnan & Ponta, Fernando L., 2017. "Dynamic aeroelastic behavior of wind turbine rotors in rapid pitch-control actions," Renewable Energy, Elsevier, vol. 107(C), pages 327-339.
    • Handle: RePEc:eee:renene:v:107:y:2017:i:c:p:327-339
    DOI: 10.1016/j.renene.2017.02.019
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    References listed on IDEAS

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    1. Chen, Jinglong & Pan, Jun & Li, Zipeng & Zi, Yanyang & Chen, Xuefeng, 2016. "Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals," Renewable Energy, Elsevier, vol. 89(C), pages 80-92.
    2. de Bessa, Iury Valente & Palhares, Reinaldo Martinez & D'Angelo, Marcos Flávio Silveira Vasconcelos & Chaves Filho, João Edgar, 2016. "Data-driven fault detection and isolation scheme for a wind turbine benchmark," Renewable Energy, Elsevier, vol. 87(P1), pages 634-645.
    3. Yolanda Vidal & Christian Tutivén & José Rodellar & Leonardo Acho, 2015. "Fault Diagnosis and Fault-Tolerant Control of Wind Turbines via a Discrete Time Controller with a Disturbance Compensator," Energies, MDPI, vol. 8(5), pages 1-17, May.
    4. Ponta, Fernando L. & Otero, Alejandro D. & Lago, Lucas I. & Rajan, Anurag, 2016. "Effects of rotor deformation in wind-turbine performance: The Dynamic Rotor Deformation Blade Element Momentum model (DRD–BEM)," Renewable Energy, Elsevier, vol. 92(C), pages 157-170.
    5. Njiri, Jackson G. & Söffker, Dirk, 2016. "State-of-the-art in wind turbine control: Trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 377-393.
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    Cited by:

    1. Gao, Rongzhen & Yang, Junwei & Yang, Hua & Wang, Xiangjun, 2023. "Wind-tunnel experimental study on aeroelastic response of flexible wind turbine blades under different wind conditions," Renewable Energy, Elsevier, vol. 219(P2).
    2. Ernesto Chavero-Navarrete & Mario Trejo-Perea & Juan-Carlos Jáuregui-Correa & Roberto-Valentín Carrillo-Serrano & José-Gabriel Rios-Moreno, 2019. "Pitch Angle Optimization by Intelligent Adjusting the Gains of a PI Controller for Small Wind Turbines in Areas with Drastic Wind Speed Changes," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    3. Xue, Zhanpu & Wang, Wei & Fang, Liqing & Zhou, Jingbo, 2020. "Numerical simulation on structural dynamics of 5 MW wind turbine," Renewable Energy, Elsevier, vol. 162(C), pages 222-233.
    4. Sang, Le Quang & Takao, Maeda & Kamada, Yasunari & Li, Qing'an, 2017. "Experimental investigation of the cyclic pitch control on a horizontal axis wind turbine in diagonal inflow wind condition," Energy, Elsevier, vol. 134(C), pages 269-278.
    5. Liu, Zhenqing & Wang, Yize & Nyangi, Patrice & Zhu, Zhiwen & Hua, Xugang, 2021. "Proposal of a novel GPU-accelerated lifetime optimization method for onshore wind turbine dampers under real wind distribution," Renewable Energy, Elsevier, vol. 168(C), pages 516-543.
    6. Zhanpu Xue & Hao Zhang & Yunguang Ji, 2023. "Dynamic Response of a Flexible Multi-Body in Large Wind Turbines: A Review," Sustainability, MDPI, vol. 15(8), pages 1-25, April.
    7. Santo, G. & Peeters, M. & Van Paepegem, W. & Degroote, J., 2019. "Dynamic load and stress analysis of a large horizontal axis wind turbine using full scale fluid-structure interaction simulation," Renewable Energy, Elsevier, vol. 140(C), pages 212-226.

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