Wind farm wake behaviour and forecasting is gaining the importance recently. It is especially relevant in the German Bight where space for wind farm clusters is limited, and wind farm wake lengths of up to 60 km have been measured. In this investigation newly proposed simple wind farm far-field recovery analytical wake model called SWIFFR is compared to the analytical EFFWAKE ( Emeis, 2010) (Efficiency and Wake) wind farm wake model and the established Frandsen model ( Frandsen et al., 2006). The models in this study are compared to measured in‑situ airborne data, captured during the WIPAFF (wind park far field) project. Three specific flights are shown and compared to the respective model result of each analytical model. The SWIFFR model is derived from the Reynolds-averaged Navier-Stokes equation for the momentum conservation. It describes the wind speed recovery, as for example, in the wake of a wind farm from an atmospheric point of view, by acknowledging turbulent momentum from the atmosphere aloft of the wind farm wake and from the sides as well. A gain in accuracy in comparison to the EFFWAKE model is achieved. Analytical models provide computationally inexpensive results based on some assumptions and simplifications of the governing equations, which distinguishes this approach from purely empirical models.

中文翻译：

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提高风电场赤字衰减模型的准确性——比较

风电场尾流行为和预测最近变得越来越重要。这在德国湾尤其重要，那里风电场集群的空间有限，并且测量到的风电场尾流长度长达 60 公里。在这项研究中，新提出的简单风电场远场恢复分析尾流模型（称为 SWIFFR）与分析 EFFWAKE（Emeis，2010）（效率和尾流）风电场尾流模型和已建立的 Frandsen 模型（Frandsen 等，2006）进行了比较。本研究中的模型与 WIPAFF（风电场远场）项目期间捕获的现场机载测量数据进行了比较。显示了三个特定航班，并将其与每个分析模型的相应模型结果进行比较。SWIFFR 模型源自动量守恒的雷诺平均纳维-斯托克斯方程。例如，它从大气的角度描述了风电场尾流中的风速恢复，通过承认来自风电场尾流高处大气以及侧面的湍流动量。与 EFFWAKE 模型相比，精度有所提高。分析模型基于一些假设和控制方程的简化提供了计算成本低廉的结果，这将这种方法与纯经验模型区分开来。