Modeling of Wake Effects on Power Loss, Fatigue Damage and Noise on a Cluster of Wind Turbines
风力发电机组功率损耗、疲劳损坏和噪声的尾流效应建模
基本信息
- 批准号:RGPIN-2017-03935
- 负责人:
- 金额:$ 2.7万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2017
- 资助国家:加拿大
- 起止时间:2017-01-01 至 2018-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Wake effects of a wind turbine (WT) are related to a decreasing velocity and an increasing turbulence intensity downstream of the rotating blades of a WT. This typically results in a 10%~20% decline in the total wind farm power production and a 5%~15% increase in the WT blade fatigue load. In addition, WT wakes also influence the sources of aeroacoustic noise generation (particularly, low-frequency noise in the frequency range from about 20-160 Hz and infrasound with frequencies less than about 20 Hz) in a cluster of WTs close to residential areas. This has become an issue of growing importance as it can potentially affect human health. This is commonly referred to as the “wind turbine syndrome”. It is against this background that a research program is proposed which involves the development of a new “aeroelastic actuator line” (AAL) wake model and the subsequent integration of this model into an in-house Computational Fluid Dynamics (CFD) code STREAM developed by the PI’s group. As the predictability of AAL is sensitive to the choice of turbulence models, a new turbulence model based on the Partially Resolved Numerical Simulation (PRNS) approach will be proposed. The solution accuracy and computational efficiency will be enhanced by implementing the adaptive mesh refinement (AMR) algorithm in order to properly resolve each WT blade. In order to estimate fatigue damage and lifespan of isolated and clusters of WTs, fatigue models based on M-N and S-N curves (where M, S and N denote the moment, stress and number of load cycles, respectively) will be interfaced with the structural component in AAL. Finally, an acoustic code based on the hydrodynamic/acoustic splitting technique will be developed and coupled to STREAM to predict WT noise.
风力涡轮机的尾迹效应与风力涡轮机旋转叶片下游的速度下降和湍流强度增加有关。这通常会导致风电场总发电量下降10%~20%,风力涡轮机叶片疲劳负荷增加5%~15%。此外,小波尾迹还会影响靠近居民区的小波尾迹群的航空声噪声源(特别是频率约为20-160 Hz的低频噪声和频率小于20 Hz的次声)。这已成为一个日益重要的问题,因为它可能影响人类健康。这通常被称为“风力涡轮机综合症”。正是在这种背景下,提出了一项研究计划,该计划涉及开发一种新的“气动弹性致动器线”(AAL)尾流模型,并随后将该模型集成到PI小组开发的内部计算流体动力学(CFD)代码流中。由于AAL的可预测性对湍流模型的选择比较敏感,本文提出了一种基于部分解析数值模拟(PRNS)方法的湍流模型。通过引入自适应网格细化(AMR)算法,对小波变换叶片进行正确解析,提高求解精度和计算效率。在AAL中,将基于M-N和S-N曲线的疲劳模型(其中M、S和N分别表示弯矩、应力和载荷循环次数)与结构构件相结合,以估计孤立和集群WTs的疲劳损伤和寿命。最后,将开发一种基于水动力/声分裂技术的声学代码,并将其与STREAM相结合以预测小波噪声。
项目成果
期刊论文数量(0)
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专利数量(0)
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{{ truncateString('Lien, FueSang', 18)}}的其他基金
Modeling of Wake Effects on Power Loss, Fatigue Damage and Noise on a Cluster of Wind Turbines
风力发电机组功率损耗、疲劳损坏和噪声的尾流效应建模
- 批准号:
RGPIN-2017-03935 - 财政年份:2021
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
Modeling of Wake Effects on Power Loss, Fatigue Damage and Noise on a Cluster of Wind Turbines
风力发电机组功率损耗、疲劳损坏和噪声的尾流效应建模
- 批准号:
RGPIN-2017-03935 - 财政年份:2020
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
Modeling of Wake Effects on Power Loss, Fatigue Damage and Noise on a Cluster of Wind Turbines
风力发电机组功率损耗、疲劳损坏和噪声的尾流效应建模
- 批准号:
RGPIN-2017-03935 - 财政年份:2019
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
Modeling of Wake Effects on Power Loss, Fatigue Damage and Noise on a Cluster of Wind Turbines
风力发电机组功率损耗、疲劳损坏和噪声的尾流效应建模
- 批准号:
RGPIN-2017-03935 - 财政年份:2018
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
Multiscale Modeling of Wind Turbine Wake Effects on Short-term Wind Power Forecasting and Wind Farm Layout Planning
风力发电机尾流效应对短期风电预测和风电场布局规划的多尺度建模
- 批准号:
RGPIN-2016-04015 - 财政年份:2016
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
Numerical prediction of wind turbine noise using large eddy simulation
使用大涡模拟的风力涡轮机噪声数值预测
- 批准号:
203459-2011 - 财政年份:2015
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
Numerical prediction of wind turbine noise using large eddy simulation
使用大涡模拟的风力涡轮机噪声数值预测
- 批准号:
203459-2011 - 财政年份:2014
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
Computational modelling of heat transfer in heat exchangers with high Prandtl number fluids
高普朗特数流体热交换器中传热的计算模型
- 批准号:
454251-2013 - 财政年份:2013
- 资助金额:
$ 2.7万 - 项目类别:
Engage Grants Program
Numerical prediction of wind turbine noise using large eddy simulation
使用大涡模拟的风力涡轮机噪声数值预测
- 批准号:
203459-2011 - 财政年份:2013
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
CFD modeling of surge tank degassing process
调压罐脱气过程的 CFD 建模
- 批准号:
453186-2013 - 财政年份:2013
- 资助金额:
$ 2.7万 - 项目类别:
Engage Grants Program
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Modeling of Wake Effects on Power Loss, Fatigue Damage and Noise on a Cluster of Wind Turbines
风力发电机组功率损耗、疲劳损坏和噪声的尾流效应建模
- 批准号:
RGPIN-2017-03935 - 财政年份:2018
- 资助金额:
$ 2.7万 - 项目类别:
Discovery Grants Program - Individual
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风力发电机尾流效应对短期风电预测和风电场布局规划的多尺度建模
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