Reliability-Based Predictions of Extreme and Fatigue Responses of Utility-Scale Wind Turbines through Advanced Modeling and Simulations

通过高级建模和仿真对公用事业规模风力涡轮机的极端和疲劳响应进行基于可靠性的预测

• 批准号: 1029922
• 负责人: Xinzhong Chen
• 金额: $ 24.05万
• 依托单位: Texas Tech University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1029922&HistoricalAwards=false
• 关键词: Reliability; Based; Predictions; Extreme; Fatigue

The research objective of this award is to develop advanced modeling and simulation approaches for accurately quantifying extreme and fatigue responses of utility-scale wind turbines. The rapidly evolving wind turbine technology currently faces many technical challenges in its trouble-free operations. Breakdowns of large wind turbine due to extreme loading conditions and fatigue failures are common place as these extreme conditions cannot be accurately predicted with the existing approaches. Three specific research objectives of the project are to develop: 1) efficient extrapolation methods and numerical frameworks for simulating extreme responses for turbines under operational and parked conditions; 2) response combination schemes for calculating the extreme responses for turbine designs; and 3) a methodology to include the non-Gaussian wind characteristics that can occur on some sites in extreme response calculating methods. Various possible wind occurrence scenarios will be considered to provide data for performance-based designs of turbines with enhanced reliabilities. The numerical framework developed in this project will permit the calculation of the design responses and data for fatigue failure estimations considering the extreme turbine response conditions. The findings of this project will result in improved designs of wind turbines with reduced risk and enhanced efficiency for energy generation. This project will help to improve current turbine design standards and state-of-the-art tools for assessing turbine performance under various wind conditions. The advanced modeling and simulation tools for land-based turbines developed in this project can be also applied to offshore wind turbines by further incorporating the effects of hydrodynamic interactions. U.S. turbine firms will be able to use these tools to optimize turbine performance to enhance their competitiveness in the domestic and global wind energy markets. The research results and findings can also be adopted for reliability analysis and design of other structural systems under extreme dynamic loadings. The educational and outreach activities include the establishment of a novel portable bench-scale instructional wind tunnel testing program that is expected to effectively enhance classroom education in aerodynamics and wind engineering and will be beneficial for many universities. The project will also provide advanced education and training to graduate and undergraduate students involved in the project.

该奖项的研究目标是开发先进的建模和仿真方法，以准确量化公用事业规模风力涡轮机的极端和疲劳响应。快速发展的风力发电技术在实现无故障运行方面面临着诸多技术挑战。大型风力发电机由于极端载荷和疲劳失效而发生故障是常见的，因为这些极端条件无法用现有的方法准确预测。该项目的三个具体研究目标是开发：1)有效的外推方法和数值框架，用于模拟涡轮机在运行和停放条件下的极端响应；2)涡轮设计极限响应计算的响应组合方案；3)在极端响应计算方法中包含可能出现在某些地点的非高斯风特征的方法。将考虑各种可能的风发生情况，为基于性能的涡轮机设计提供数据，提高可靠性。在这个项目中开发的数值框架将允许计算设计响应和考虑极端涡轮响应条件的疲劳失效估计数据。该项目的研究结果将改进风力涡轮机的设计，降低风险，提高发电效率。该项目将有助于改进当前的涡轮机设计标准和最先进的工具，以评估各种风力条件下的涡轮机性能。本项目开发的陆基涡轮机先进的建模和仿真工具，通过进一步纳入水动力相互作用的影响，也可以应用于海上风力涡轮机。美国涡轮机公司将能够使用这些工具来优化涡轮机性能，以提高他们在国内和全球风能市场上的竞争力。研究结果和发现也可用于其他结构体系在极端动荷载作用下的可靠性分析和设计。教育和推广活动包括建立一种新型的便携式台式教学风洞测试程序，该程序有望有效地加强空气动力学和风工程的课堂教育，并将使许多大学受益。该项目还将为参与该项目的研究生和本科生提供高级教育和培训。