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Simplified Polynomial-asymptotic-distribution Actuator Disc (SPAD) method for wind turbine wake simulation based on k-ϵ-fP turbulence model

Author

Listed:
  • Meng, Hang
  • Chen, Tao
  • Chen, Xiaodong
  • Ge, Mingwei
  • Han, Yunzhou
  • Liu, Yongqian

Abstract

In large wind farms, wake effect has a negative impact on the annual production of wind turbines. As a result, wind turbine wake simulation is important for wind farm micro-sitting to minimize power loss and maximize energy production. Coupled with Reynolds Averaged Navier–Stokes turbulence model, Simplified Uniform-distribution Actuator Disc method is the most widely-used rotor model for wake simulation in engineering practice. The conventional simplified uniform-distribution actuator disc models suffer discrepancies of wake velocity prediction compared with the measurements in the near wake region. The novelty of the current research is to propose a Simplified Polynomial-asymptotic-distribution Actuator Disc method based on k−ϵ−fP turbulence model for cylindrical actuator disc cell region with finite thickness, which is simple for implementation and improves the accuracy of wake simulation compared with conventional method. The proposed method conforms to momentum conservation and is as simple as conventional method because of its polynomial formulation and no requirement for aerodynamics data in Generalized Actuator Disc model. From the verification and validation cases, it can be found that the proposed model has better agreement with both high-fidelity actuator line model and the field test measurements from Lillgrund wind farm compared with conventional model. The proposed actuator disc model has the potential to be applied to the micrositting of large offshore wind farms in the future.

Suggested Citation

  • Meng, Hang & Chen, Tao & Chen, Xiaodong & Ge, Mingwei & Han, Yunzhou & Liu, Yongqian, 2024. "Simplified Polynomial-asymptotic-distribution Actuator Disc (SPAD) method for wind turbine wake simulation based on k-ϵ-fP turbulence model," Renewable Energy, Elsevier, vol. 236(C).
  • Handle: RePEc:eee:renene:v:236:y:2024:i:c:s0960148124015477
    DOI: 10.1016/j.renene.2024.121479
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