Investigating Wind Farm Wake Interactions by Leveraging a Viscous Vortex Particle Method

利用粘性涡旋粒子法研究风电场尾流相互作用

• 批准号: 2006219
• 负责人: Andrew Ning
• 金额: $ 30万
• 依托单位: Brigham Young University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2006219&HistoricalAwards=false
• 关键词: Investigating; Wind; Farm; Wake; Interactions

One major impediment in the wind energy field is managing the power losses (10-30%) that occur in a wind farm because of wake interference. Mitigating these losses by even a few percent would have a major impact on our ability to abundantly produce clean energy and reduce greenhouse gas emissions. Reducing these losses requires untangling the complexities of wind farm flow behavior. Wind farms typically consist of 10s or 100s of turbines, with rotating blades creating wakes that mix and interact, affected by terrain and atmospheric behavior across many scales. Vortex particle methods have been demonstrated to be an effective approach for simulating wake-dominant flows in adjacent fields (e.g., rotorcraft) and can potentially offer insight into wind farm flow fields at much faster computational speeds compared to traditional methods. However, efficiently propagating vortex particles around viscous walls (e.g., terrain, other turbines) remains a challenge that is a focal point of this proposal. The fundamental methodology could potentially be useful in other wake-dominant flow fields like simulating aircraft, underwater vehicles, the motion of water or smoke around other objects, etc. The project will also facilitate the development of a learn-by-doing platform to introduce students to computational aerodynamics—like a Codecademy® for aerodynamics.The viscous vortex particle method is based on solving the vorticity form of the Navier-Stokes equations, and, using a meshless Lagrangian scheme, which can accurately preserve vortical structures and improve computational efficiency by placing particles only where needed. The first objective is to extend the methodology to allow for efficient propagation of particles around viscous walls. The second objective is to leverage the speed of the proposed methodology to create a new analytical wake model appropriate for mixed height wind farms. Recent work has demonstrated that mixed height wind farms have the potential for a significant increase in power production. Existing analytical wake models are often not appropriate for these scenarios as they do not include important coupling effects such as mixing and entrainment. So, the third objective is to conduct broad sensitivity studies to identify the most relevant parameters and strategies to mitigate the negative effects of partial waking. Wind turbines often encounter incoming wakes over just a portion of the rotor disk causing asymmetric loading and potentially increased fatigue damage and noise. The proposed methodology provides a good balance between capturing the fidelity in flow physics with prediction speed to enable a robust exploration of wake interactions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

风能领域的一个主要障碍是管理由于尾流干扰而在风电场中发生的功率损耗（10-30%）。 即使将这些损失减少百分之几，也会对我们大量生产清洁能源和减少温室气体排放的能力产生重大影响。减少这些损失需要解开风电场流动行为的复杂性。 风力发电场通常由10或100个涡轮机组成，旋转的叶片产生混合和相互作用的尾流，受到地形和大气行为的影响。 涡粒子方法已被证明是一种有效的方法，用于模拟相邻场中的尾流主导流（例如，旋翼机），并且与传统方法相比，能够以快得多的计算速度潜在地提供对风电场流场的洞察。 然而，有效地传播粘性壁周围的涡流颗粒（例如，地形、其他涡轮机）仍然是一个挑战，这是本提案的重点。 基本的方法可能在其他尾流主导的流场，如模拟飞机，水下航行器，水或烟雾在其他物体周围的运动，该项目还将促进一个边做边学平台的开发，向学生介绍计算空气动力学-如空气动力学的Codecademy®。粘性涡粒子方法基于求解Navier方程的涡量形式，Stokes方程，并使用无网格拉格朗日格式，它可以精确地保留涡结构，并通过仅在需要的地方放置粒子来提高计算效率。第一个目标是扩展的方法，以允许有效的传播周围的粘性壁的颗粒。 第二个目标是利用所提出的方法的速度来创建适合于混合高度风电场的新的分析尾流模型。最近的工作表明，混合高度风力发电场有可能显着增加发电量。 现有的分析尾流模型往往不适合这些情况下，因为它们不包括重要的耦合效应，如混合和夹带。 因此，第三个目标是进行广泛的敏感性研究，以确定最相关的参数和策略，以减轻部分清醒的负面影响。风力涡轮机通常仅在转子盘的一部分上遇到进入的尾流，从而导致不对称负载以及潜在地增加的疲劳损伤和噪声。所提出的方法提供了一个很好的平衡之间捕获的保真度在流物理与预测速度，使一个强大的探索尾interactions.This奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。