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Validation of a lookup-table approach to modeling turbine fatigue loads in wind farms under active wake control

机译:验证主动唤醒控制下风电场涡轮机疲劳负荷的查找表方法

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Wake redirection is an active wake control (AWC) concept that is known to have a high potential for increasing the overall power production of wind farms. Being based on operating the turbines with intentional yaw misalignment to steer wakes away from downstream turbines, this control strategy requires careful attention to the load implications. However, the computational effort required to perform an exhaustive analysis of the site-specific loads on each turbine in a wind farm is unacceptably high due to the huge number of aeroelastic simulations required to cover all possible inflow and yaw conditions. To reduce this complexity, a practical load modeling approach is based on “gridding”, i.e., performing simulations only for a subset of the range of environmental and operational conditions that can occur. Based on these simulations, a multi-dimensional lookup table (LUT) can be constructed containing the fatigue and extreme loads on all components of interest. Using interpolation, the loads on each turbine in the farm can the be predicted for the whole range of expected conditions. Recent studies using this approach indicate that wake redirection can increase the overall power production of the wind farm and at the same time decrease the lifetime fatigue loads on the main components of the individual turbines. As the present level of risk perception related to operation with large yaw misalignment is still substantial, it is essential to increase the confidence level in this LUT-based load modeling approach to further derisk the wake redirection strategy. To this end, this paper presents the results of a series of studies focused on the validation of different aspects of the LUT load modeling approach. These studies are based on detailed aeroelastic simulations, two wind tunnel tests, and a full-scale field test. The results indicate that the LUT approach is a computationally efficient methodology for assessing the farm loads under AWC, which achieves generally good prediction of the load trends.
机译:唤醒重定向是一个主动唤醒控制(AWC)概念,已知具有增加风电场的整体电力生产的高潜力。基于具有故意偏航的涡轮机的涡轮机以避免绕下游涡轮机唤醒,这种控制策略需要仔细关注负载影响。然而,由于需要覆盖所有可能的流入和偏航条件所需的巨大空气弹性模拟,对风电场中每个涡轮机上的每个涡轮机上的每个涡轮机上的特定场地特定载荷进行详尽分析的计算工作是不可接受的。为了降低这种复杂性,实际的负载建模方法基于“网格”,即,仅针对可能发生的环境和操作条件范围的子集进行模拟。基于这些模拟,可以构建多维查找表(LUT),其中包含对所有感兴趣的所有组件上的疲劳和极端负载。使用插值,可以预测农场中每个涡轮机上的负载可以预测整个预期条件范围。使用这种方法的最近的研究表明,唤醒重定向可以增加风电场的整体电力生产,同时降低各个涡轮机的主要部件上的寿命疲劳负载。由于与具有大偏航失值的操作相关的风险感知水平仍然很大,因此必须增加基于LUT的负荷建模方法中的置信水平,以进一步驾驶唤醒重定向策略。为此,本文提出了一系列研究的结果,重点是LUT负荷建模方法的不同方面的验证。这些研究基于详细的空气弹性模拟,两个风洞试验和全规模的场地测试。结果表明,LUT方法是用于评估AWC下的农场负荷的计算有效方法,这实现了对负荷趋势的良好预测。

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