使用各种湍流模型对 NREL 第六阶段风力涡轮机性能进行计算流体动力学 (CFD) 研究

IF 2.8 4区 工程技术 Q2 ENGINEERING, CHEMICAL
Processes Pub Date : 2024-09-16 DOI:10.3390/pr12091994
Abobakr Al-Ttowi, Akmal Nizam Mohammed, Sami Al-Alimi, Wenbin Zhou, Yazid Saif, Iman Fitri Ismail
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引用次数: 0

摘要

本研究对 NREL 第六阶段风力涡轮机的空气动力性能进行了详细的计算流体动力学 (CFD) 调查,重点是不同湍流模型下的扭矩和发电量。主要目的是分析各种湍流模型及其对风力涡轮机扭矩产生的影响。此外,它还研究了距离对风速不足的影响。研究利用 S809 机翼和全转子的二维和三维模拟,检验了 k-epsilon、k-omega 和 k-omega SST 湍流模型的预测能力。研究结合了实验验证和使用高斯尾流模型进行的尾流分析,以评估风速缺陷。模拟的风速范围为(6-10 米/秒),结果表明 k-epsilon 模型与实验数据的匹配度最高,尤其是在目标范围内的较高风速下。尽管 k-epsilon 的结果与实验数据的一致性更好,但从理论上讲,k-omega(SST)的性能应该更好,因为它结合了 k-epsilon 和 k-omega 的优势,可以预测无论距离墙壁多远的气流。然而,在使用 k-omega(SST)的模拟中,只有在风速达到或超过 10 米/秒时,才能看到气流分离和剪应力瞬变。另一方面,研究发现,风浪效应会在涡轮机后方造成显著的速度损失,并呈现指数衰减模式。研究结果为通过湍流模型选择和尾流影响分析提高风力涡轮机性能提供了宝贵的见解,为未来风能优化提供了实用指南。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational Fluid Dynamics (CFD) Investigation of NREL Phase VI Wind Turbine Performance Using Various Turbulence Models
This study presents a detailed computational fluid dynamics (CFD) investigation into the aerodynamic performance of the NREL Phase VI wind turbine, focusing on torque and power generation under different turbulence models. The primary objective was to analyse the effect of various turbulence models and their responses in wind turbine torque generation. Furthermore, it also investigates the distance effect on wind velocity deficit. The research utilizes 2D and 3D simulations of the S809 airfoil and the full rotor, examining the predictive capabilities of the k-epsilon, k-omega, and k-omega SST turbulence models. The study incorporates both experimental validation and wake analysis using the Gaussian wake model to assess wind velocity deficits. Simulations were conducted for a wind speed range of (6–10 m/s), with results indicating that the k-epsilon model provided the closest match to experimental data, particularly at higher wind speeds within the targeted range. Even though k-epsilon results had better agreement when validated with experimental data, theoretically k-omega (SST) should perform better as it combines k-epsilon and k-omega advantages in predicting the flow regardless of its farness from the wall. However, in simulations using the k-omega (SST), the separation of flow and the shear stress transients were only visible at wind speeds of 10 m/s or higher. Wake effects, on the other hand, were found to cause significant velocity deficits behind the turbine, following an exponential decay pattern. The findings offer valuable insights into improving wind turbine performance through turbulence model selection and wake impact analysis, providing practical guidelines for future wind energy optimizations.
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来源期刊
Processes
Processes Chemical Engineering-Bioengineering
CiteScore
5.10
自引率
11.40%
发文量
2239
审稿时长
14.11 days
期刊介绍: Processes (ISSN 2227-9717) provides an advanced forum for process related research in chemistry, biology and allied engineering fields. The journal publishes regular research papers, communications, letters, short notes and reviews. Our aim is to encourage researchers to publish their experimental, theoretical and computational results in as much detail as necessary. There is no restriction on paper length or number of figures and tables.
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