In-Stream Hydrokinetic Turbine Fault Detection and Fault Tolerant Control - A Benchmark Model
In-Stream Hydrokinetic Turbine Fault Detection and Fault Tolerant Control - A Benchmark Model
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DOI：
10.23919/acc.2019.8815231
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发表时间：
2019-07
期刊：
影响因子：
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通讯作者：
Yufei Tang;James H. VanZwieten;Brock Dunlap;David A. Wilson;C. Sultan;N. Xiros
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文献类型：
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作者：
Yufei Tang;James H. VanZwieten;Brock Dunlap;David A. Wilson;C. Sultan;N. Xiros
对可再生能源生产的兴趣增加，产生了对新的发电方法的需求。由于在与电网隔离的地方进行低成本发电的潜力很大，因此流中水力涡轮机可以帮助满足这一不断增长的需求。与其他可再生能源相比，水力涡轮机由于其孤立的性质和恶劣的操作环境而具有更高的操作和维护（O&M）成本。因此，必须开发技术，通过应用容错控制（FTC）和机器状态监测（MCM）来降低这些成本，以提高可靠性和维护预测。因此，本文的主要目的是解决流体动力涡轮机研究中的一个关键限制：缺乏广泛可用的数据，用于开发模型，进行FTC和MCM。为此，一个20千瓦的研究流体动力学涡轮机在疲劳空气动力学结构和湍流（FAST）的实施，并在Matlab/Simulink环境中。本文详细介绍了高保真仿真平台的开发以及生成数据的特点，重点是未来的FTC和MCM的实现。
Increased interest in renewable energy production has created demand for novel methods of electricity production. With a high potential for low cost power generation in locations otherwise isolated from the grid, in-stream hydrokinetic turbines could serve to help meet this growing demand. Hydrokinetic turbines possess higher operations and maintenance (O&M) costs due to their isolated nature and harsh operating environment when compared with other sources of renewable energy. As such, techniques must be developed to mitigate these costs through the application of fault-tolerant control (FTC) and machine condition monitoring (MCM) for increased reliability and maintenance forecasting. Hence, the primary objective of this paper is to address a key limitation in hydrokinetic turbine research: the lack of widely available data for use in developing models by which to conduct FTC and MCM. To this end, a 20 kW research hydrokinetic turbine implemented in Fatigue Aerodynamics Structures and Turbulence (FAST) is presented and housed within the Matlab/Simulink environment. This paper details the high-fidelity simulation platform development together with the characteristics of generated data with a focus on future FTC and MCM implementation.