Offshore Floating Wind Turbine Operation & Maintenance

海上浮动风力发电机运行

• 批准号: 2488840
• 金额: --
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2488840
• 关键词: Offshore; Floating; Wind; Turbine; Operation

The mix of energy supply worldwide has changed dramatically in the last few decades. Worldwide, in order to tackle climate change and increasing energy consumption, there has been a clear movement from fossils towards renewable and sustainable energy sources. Wind energy, for example, has generated 98% of Scottish electricity demand in October 2018, which has established a world-class record.Compared with onshore wind turbines, offshore wind could provide relatively larger capacity and a lower level of noise pollution, etc. As the wind industry moving to deeper water depth, fixed type wind turbines are no longer suitable, floating wind turbines must be applied. On the other hand, unlike onshore wind turbines, due to the harsh environment they are operating environment and the multifaceted structural components, the model of dynamics for offshore floating wind turbines, especially in the O&M phase needs to be developed.This project will first investigate the simulation of wind turbine operations based on advanced numerical methods. This work will also focus on developing a detailed model for the dynamics of wind turbines, including a comprehensive simulation of the mechanical part (i.e. aero-hydro-servo-elastic, AHSE). Through the simulated load effects, responses in normal operation and extreme conditions will be solved by a coupled model of the wind turbine system, which is significant for operation and maintenance. Meanwhile, the fast-growing of data science, which will still be a promising field over the next 10 years, especially in the wind energy sector, will be applied in this project together with the development and analysis of the AHSE model for speed/power forecasting & predictions and fault detection & diagnosis.

在过去几十年中，全球能源供应的结构发生了巨大变化。在世界范围内，为了应对气候变化和能源消耗增加，已经出现了从化石转向可再生和可持续能源的明显趋势。例如，风能在2018年10月已经产生了苏格兰98%的电力需求，创造了世界级的纪录。与陆上风力涡轮机相比，海上风力可以提供相对更大的容量和更低的噪音污染水平等。随着风力产业向更深的水深发展，固定式风力涡轮机不再适合，必须应用浮动式风力涡轮机。另一方面，与陆上风力发电机不同的是，海上漂浮式风力发电机的运行环境恶劣，结构部件复杂，需要建立海上漂浮式风力发电机的动力学模型，特别是在运行和维护阶段。本项目将首先研究基于先进数值方法的风力涡轮机运行模拟。这项工作还将侧重于开发风力涡轮机动力学的详细模型，包括机械部分（即气动液压伺服弹性，AHSE）的全面模拟。通过模拟负载效应，建立风力机涡轮机系统的耦合模型，求解正常运行和极端工况下的响应，对运行和维护具有重要意义。与此同时，数据科学的快速发展，在未来10年内仍然是一个很有前途的领域，特别是在风能领域，将与AHSE模型的开发和分析一起应用于该项目，用于速度/功率预测和故障检测与诊断。