Development and characterisation of an AI-in-the-loop testing platform for floating wind turbines PART I : construction, validation, and benchmark testing
Li, Zihao and Tao, Longbin and Chen, Yewen and Zeng, Weiming and Cai, Chang and Zhu, Guibing and Li, Qingan (2024) Development and characterisation of an AI-in-the-loop testing platform for floating wind turbines PART I : construction, validation, and benchmark testing. Ocean Engineering, 297. 116968. ISSN 0029-8018 (https://doi.org/10.1016/j.oceaneng.2024.116968)
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Abstract
Model testing is an inevitable means to verify design optimization because it is more economical than prototype testing and more reliable than numerical simulation. However, in the floating wind turbine experiment, the hydrodynamic Froude number and the aerodynamic Reynolds number cannot satisfy similar rules simultaneously, making the scale effect problem a major difficulty in the experiment. Therefore, this paper innovatively introduces AI-prediction-in-the-loop experimental technologies. The Froude similarity criterion is applied to model production and physical set-up. A Froude-similar wind turbine model (except for the blades) is placed in the wave flume and the floating platform moves. The response measurement data is input into the AI prediction module to perform real-time prediction of aerodynamic loads such as rotor thrust, output the calculation results and control the simulated load of the actuator, thereby realizing aerodynamic-hydrodynamic-structural coupling experiments under Froude's rules. Characterization benchmark and tank tests are carried out to validate the AI-in-the-loop testing methodology, and the results show good agreement between measured and predicted rotor thrust values across both high and low frequencies. Moreover, the time delay and systematic uncertainty of the proposed testing platform are identified for the first time.
ORCID iDs
Li, Zihao, Tao, Longbin ORCID: https://orcid.org/0000-0002-8389-7209, Chen, Yewen, Zeng, Weiming, Cai, Chang, Zhu, Guibing and Li, Qingan;-
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Item type: Article ID code: 88782 Dates: DateEvent1 April 2024Published16 February 2024Published Online30 January 2024Accepted16 November 2023SubmittedSubjects: Technology > Hydraulic engineering. Ocean engineering Department: Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering Depositing user: Pure Administrator Date deposited: 18 Apr 2024 08:37 Last modified: 11 Nov 2024 14:16 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/88782