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Comparative study of the behavior of wind-turbines in a wind farm

Author

Listed:
  • Migoya, Emilio
  • Crespo, Antonio
  • García, Javier
  • Moreno, Fermín
  • Manuel, Fernando
  • Jiménez, Ángel
  • Costa, Alexandre

Abstract

The Sotavento wind farm is an experimental wind farm which has different types of wind turbines. It is located in an area whose topography is moderately complex, and where wake effects can be significant. One of the objectives of Sotavento wind farm is to compare the performances of the different machines; particularly regarding power production, maintenance and failures. However, because of wakes and topography, the different machines are not working under identical conditions. Two linearized codes have been used to estimate topography effects: UPMORO and WAsP. For wind directions in which topography is abrupt, the non-linear flow equations have been solved with the commercial code FLUENT, although the results are only qualitatively used. For wake effects, the UPMPARK code has been applied. As a result, the incident velocity over each wind turbine is obtained, and the power production is estimated by means of the power curve of each machine. Experimental measurements give simultaneously the wind characteristics at the measuring stations, the wind velocity, at the nacelle anemometer, and the power production of each wind turbine. These experimental results are employed to validate the numerical predictions. The main objective of this work is to deduce and validate a relationship between the wind characteristics measured in the anemometers and the wind velocity and the power output in each machine.

Suggested Citation

  • Migoya, Emilio & Crespo, Antonio & García, Javier & Moreno, Fermín & Manuel, Fernando & Jiménez, Ángel & Costa, Alexandre, 2007. "Comparative study of the behavior of wind-turbines in a wind farm," Energy, Elsevier, vol. 32(10), pages 1871-1885.
    • Handle: RePEc:eee:energy:v:32:y:2007:i:10:p:1871-1885
    DOI: 10.1016/j.energy.2007.03.012
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    Citations

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    Cited by:

    1. Shaler, Kelsey & Kecskemety, Krista M. & McNamara, Jack J., 2019. "Benchmarking of a Free Vortex Wake Model for Prediction of Wake Interactions," Renewable Energy, Elsevier, vol. 136(C), pages 607-620.
    2. Abdelkafi, Achraf & Krichen, Lotfi, 2011. "New strategy of pitch angle control for energy management of a wind farm," Energy, Elsevier, vol. 36(3), pages 1470-1479.
    3. Ko, Kyungnam & Kim, Kyoungbo & Huh, Jongchul, 2010. "Variations of wind speed in time on Jeju Island, Korea," Energy, Elsevier, vol. 35(8), pages 3381-3387.
    4. Zhang, Yagang & Yang, Jingyun & Wang, Kangcheng & Wang, Zengping & Wang, Yinding, 2015. "Improved wind prediction based on the Lorenz system," Renewable Energy, Elsevier, vol. 81(C), pages 219-226.
    5. Buen Zhang & Shyuan Cheng & Fanghan Lu & Yuan Zheng & Leonardo P. Chamorro, 2020. "Impact of Topographic Steps in the Wake and Power of a Wind Turbine: Part A—Statistics," Energies, MDPI, vol. 13(23), pages 1-14, December.
    6. Hocine, Labar & Mounira, Mekki, 2011. "Effect of nonlinear energy on wind farm generators connected to a distribution grid," Energy, Elsevier, vol. 36(5), pages 3255-3261.
    7. An, Xueli & Jiang, Dongxiang & Li, Shaohua & Zhao, Minghao, 2011. "Application of the ensemble empirical mode decomposition and Hilbert transform to pedestal looseness study of direct-drive wind turbine," Energy, Elsevier, vol. 36(9), pages 5508-5520.
    8. Lanzafame, R. & Messina, M., 2010. "Power curve control in micro wind turbine design," Energy, Elsevier, vol. 35(2), pages 556-561.
    9. Kusiak, Andrew & Zheng, Haiyang, 2010. "Optimization of wind turbine energy and power factor with an evolutionary computation algorithm," Energy, Elsevier, vol. 35(3), pages 1324-1332.

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