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Wind direction fluctuation analysis for wind turbines

Author

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  • Guo, Peng
  • Chen, Si
  • Chu, Jingchun
  • Infield, David

Abstract

Fluctuations are a key characteristic of the wind resource. It is important to quantitatively analyze wind direction fluctuation due to its influence on the optimization of wind turbine yaw control. Based on wind resource data available from SCADA systems, a method is proposed to describe wind direction fluctuations in terms of fluctuation amplitude A and fluctuation duration T. A Weibull distribution is employed to fit the marginal probability density of both these two measures of wind direction fluctuations, and a mixed Copula used to connect the marginal distributions, establishing the joint probability density function. This representation has been verified through comparison with the real operating SCADA data. A set of indicators are extracted from the probability distribution which can accurately quantify the local wind direction fluctuation characteristics of a wind turbine. These indicators can be helpful in the optimization of the yaw control system parameters, facilitating an improvement in the power generating performance of the wind turbine.

Suggested Citation

  • Guo, Peng & Chen, Si & Chu, Jingchun & Infield, David, 2020. "Wind direction fluctuation analysis for wind turbines," Renewable Energy, Elsevier, vol. 162(C), pages 1026-1035.
    • Handle: RePEc:eee:renene:v:162:y:2020:i:c:p:1026-1035
    DOI: 10.1016/j.renene.2020.07.137
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    2. Ahmed, Ijaz & Rehan, Muhammad & Basit, Abdul & Malik, Saddam Hussain & Alvi, Um-E-Habiba & Hong, Keum-Shik, 2022. "Multi-area economic emission dispatch for large-scale multi-fueled power plants contemplating inter-connected grid tie-lines power flow limitations," Energy, Elsevier, vol. 261(PB).
    3. Paxis Marques João Roque & Shyama Pada Chowdhury & Zhongjie Huan, 2021. "Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study," Energies, MDPI, vol. 14(14), pages 1-22, July.
    4. Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
    5. Sang Heon Chae & Chul Uoong Kang & Eel-Hwan Kim, 2020. "Field Test of Wind Power Output Fluctuation Control Using an Energy Storage System on Jeju Island," Energies, MDPI, vol. 13(21), pages 1-16, November.

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