RESEARCH ON YAW ANGLE OPTIMIZATION ALGORITHM FOR WAKE CONTROL IN WIND FARMS

Cong Longfu; Dai Liping; Chang Ning; Zou Ang; Zhou Yixiao; Wang Zikun

doi:10.19912/j.0254-0096.tynxb.2024-1295

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (11) : 747-753. DOI: 10.19912/j.0254-0096.tynxb.2024-1295

RESEARCH ON YAW ANGLE OPTIMIZATION ALGORITHM FOR WAKE CONTROL IN WIND FARMS

Cong Longfu, Dai Liping, Chang Ning, Zou Ang, Zhou Yixiao, Wang Zikun

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Abstract

This paper establishes an accurate process for yaw angle calculation based on the Ishihara Gaussian wake model, the energy-conserving wake superposition model, and several optimization algorithms, including the African Vulture Optimization Algorithm （AVOA）. The efficiency of these algorithms is evaluated, and the influence of the turbulence superposition coefficient on the results is analyzed by comparing with LES data from the literature. Furthermore, a rapid yaw angle optimization process is developed using the TSFC optimization algorithm proposed in this study. Both optimization algorithms are applied to yaw angle optimization for turbines in tandem and in optimized layout configurations. The results indicate that a turbulence superposition coefficient of 2.8 leads to more accurate predictions of downstream turbulence intensity. For wind farms with varying layouts, active yaw control can improve power generation by 0.4% to 2.2%. Additionally, the TSFC algorithm significantly outperforms the African Vulture Optimization Algorithm in terms of efficiency, reducing computational time by an order of magnitude.

Key words

wind farm / optimization / wake / yaw control / wind turbines / algorithm

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Cong Longfu, Dai Liping, Chang Ning, Zou Ang, Zhou Yixiao, Wang Zikun. RESEARCH ON YAW ANGLE OPTIMIZATION ALGORITHM FOR WAKE CONTROL IN WIND FARMS[J]. Acta Energiae Solaris Sinica. 2025, 46(11): 747-753 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1295

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