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Full wind rose wind farm simulation including wake and terrain effects for energy yield assessment

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  • Navarro Diaz, Gonzalo P.
  • Saulo, A. Celeste
  • Otero, Alejandro D.

Abstract

In this work, CFD simulation along with the site complete wind rose are used for the first time to estimate a key magnitude for the project development of a wind farm, the capacity factor, which is directly related with the energy yield. The large computational cost that restricted CFD simulation for such a task is drastically reduced by means of a novel interpolation-extrapolation methodology, requiring the simulation of only three inlet velocities for each wind rose sector. This methodology is based on the velocity at met mast and results of the reference velocity for each wind turbine from pre-simulated cases, which are then used to compute a wide range of cases not explicitly simulated. A comparative study is carried out, in which the measured capacity factor of an onshore wind farm in the Argentinean Patagonia is compared against different solution approaches. In the particular case of this wind farm, it is found that the separate effects of wakes and terrain produce errors in the opposite sense, and results very close to the measured value are achieved when both are considered. Also, the increase in the number of simulated direction sectors from 16 to 32 does not significantly change the results.

Suggested Citation

  • Navarro Diaz, Gonzalo P. & Saulo, A. Celeste & Otero, Alejandro D., 2021. "Full wind rose wind farm simulation including wake and terrain effects for energy yield assessment," Energy, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221018909
    DOI: 10.1016/j.energy.2021.121642
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    2. Hu, Weicheng & Yang, Qingshan & Chen, Hua-Peng & Guo, Kunpeng & Zhou, Tong & Liu, Min & Zhang, Jian & Yuan, Ziting, 2022. "A novel approach for wind farm micro-siting in complex terrain based on an improved genetic algorithm," Energy, Elsevier, vol. 251(C).
    3. Tian, Linlin & Song, Yilei & Wang, Zhenming & Zhao, Ning & Zhu, Chunling & Lu, Xiyun, 2024. "Predictive capability of an improved AD/RANS method for multiple wind turbines and wind farm wakes," Energy, Elsevier, vol. 297(C).
    4. Jhan Piero Rojas & Gonzalo Romero Garcia & Dora Villada Castillo, 2022. "Parametric study of a Hybrid Renewable Energy Power Generation System in the Colombian Caribbean Region," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 394-399, March.

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