Strategy for mitigating wake interference between offshore vertical-axis wind turbines: Evaluation of vertically staggered arrangement

摘要

Wake interference between wind turbines potentially decreases the power output of offshore wind farms. While the staggered arrangement shows promise for mitigating this interference, the understanding of the impact of vertically staggered setup remains ambiguous, especially in the case of vertical-axis wind turbines (VAWTs). Also, the difference between horizontally and vertically staggered arrangements needs to be clarified. This study aims to shed light on these ambiguities, systematically evaluating the effectiveness of vertically staggered arrangement in mitigating wake interference between offshore VAWTs. High-fidelity computational fluid dynamics simulations are used to investigate the wake interference between two vertically staggered MW-class VAWTs. Typical separation distances (3D ≤ LS ≤ 7D) and different vertically staggered distances (−0.25H ≤ LV ≤ 0.75H) are considered, where D and H denote the turbine diameter and blade span length, respectively. Employing the Taguchi method, the effectiveness of horizontally and vertically staggered arrangements is compared, and the relatively optimal layout of the turbine array is identified. The results show that the vertically staggered arrangement significantly improves the power performance of the downstream turbine, e.g., the power output increases by 75.96% when LS = 7D and LV = 0.25H. When dealing with smaller LS (e.g., 3D), a negative LV is suggested, which reduces the tower cost while preserving the performance improvement. The vertically staggered arrangement has a greater impact on wake interference than the horizontally staggered arrangement. In terms of the relatively optimal layout, the power output of the turbine array is increased by 46.27%. These findings would contribute to the layout design of offshore wind farms.

Yaoran Chen

Researcher of Artificial Intelligence

我所研究的专业领域涉及计算流体动力学（Computational Fluid Dynamics）、人工智能（Artificial Intelligence）以及它们的交叉方向。目前，我的研究以海洋为应用背景，包含物理信息神经网络、海洋环境信息、海洋可再生能源等。