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Optimal yaw strategy and fatigue analysis of wind turbines under the combined effects of wake and yaw control

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  • He, Ruiyang
  • Yang, Hongxing
  • Lu, Lin

Abstract

Yaw control is one of the most important farm-level active control strategies with the aim of power maximization and load mitigation. However, improper yaw strategies may induce a significant load increase on wind turbines (WTs) although a power enhancement can be achieved. Therefore, it is essential to conduct a comprehensive fatigue analysis of wind turbines under yaw control before proposing an optimal yaw control strategy. In this study, fatigue analysis of WTs under shear flow is conducted first under various environmental and yaw conditions. Bending moments at not only blade root and yaw bearing, but also non-rotating component like tower base are investigated. Furthermore, various wake conditions including both full wake and partial wake are generated to explore the combined effects of wake flow and yaw control. Different load trends and variation rates are obtained in the analysis. To determine the optimal yaw angle at different practical inflow and yaw conditions, a cost function is proposed by using resultant bending moments and further integrating loads at different components together. The results show that efficient yaw ranges all appear in the positive yaw direction and optimal yaw angle increases with the increase of inflow speeds. The comprehensive fatigue analysis and the proposed cost function for optimal yaw control in this work are expected to contribute to the research and applications of multi-objective active yaw control strategies and therefore to increase total power output while extending operation lifetime of wind turbines.

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  • He, Ruiyang & Yang, Hongxing & Lu, Lin, 2023. "Optimal yaw strategy and fatigue analysis of wind turbines under the combined effects of wake and yaw control," Applied Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:appene:v:337:y:2023:i:c:s0306261923002428
    DOI: 10.1016/j.apenergy.2023.120878
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    Cited by:

    1. He, Ruiyang & Yang, Hongxing & Lu, Lin & Gao, Xiaoxia, 2024. "Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms," Renewable Energy, Elsevier, vol. 225(C).
    2. Sun, Shilin & Li, Qi & Hu, Wenyang & Liang, Zhongchao & Wang, Tianyang & Chu, Fulei, 2023. "Wind turbine blade breakage detection based on environment-adapted contrastive learning," Renewable Energy, Elsevier, vol. 219(P2).

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