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Engineering Application of Numerical Calibration of Wind Power in Complex Terrain Wind Farms
1 School of Energy and Power Engineering, Shenyang Institute of Engineering, Shenyang, 110136, China
2 Guoneng (Suizhong) Power Generation Co., Ltd., Huludao, 125222, China
* Corresponding Author: Xin Guan. Email:
Energy Engineering 2026, 123(10), 17 https://doi.org/10.32604/ee.2026.075468
Received 01 November 2025; Accepted 05 January 2026; Issue published 30 August 2026
Abstract
Numerical calibration of wind power is a critical strategy for mitigating power generation deficits and optimizing the micro-siting of wind turbine units. As wind energy development shifts towards mountainous regions, accurate assessment in these environments becomes increasingly challenging due to complex turbulence structures. This paper conducts a theoretical and numerical investigation of atmospheric boundary layer flow in complex terrain. Utilizing the industry-standard Askervein Hill benchmark for validation, we first evaluate the influence of top boundary condition settings in rectangular fluid domains on the simulation accuracy of the equilibrium atmospheric boundary layer. Subsequently, the study proposes a method to optimize the coefficients of the k-ε turbulence model. By designing nonlinear orthogonal experiments, the range of turbulence parameters is refined, and the spatial discretization error is systematically analyzed to minimize the deviation in turbulent kinetic energy. The results demonstrate that the optimized turbulence model coefficients significantly improve the stability and accuracy of wind power density calibration. Specifically, the proposed methodology effectively reduces the high prediction errors typically observed in the leeward wake regions of mountains. Additionally, a hybrid grid strategy—combining unstructured grids near the terrain surface with structured grids elsewhere—is recommended to balance computational efficiency and accuracy. This study provides a robust engineering reference for wind resource assessment in complex topographical conditions.Keywords
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Copyright © 2026 The Author(s). Published by Tech Science Press.This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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