Software-in-the-loop combined machine learning for dynamic responses analysis of floating offshore wind turbines

Peng Chen, Changhong Hu, Zhiqiang Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Artificial intelligence (AI) brings a new solution to overcome the challenges of Floating offshore wind turbines (FOWTs) to better predict the dynamic responses with intelligent strategies. A new AI-based software-in-the-loop method, named SADA is introduced in this paper for the prediction of dynamic responses of FOWTs, which is proposed based on an in-house programme DARwind. DARwind is a coupled aero-hydro-servoelastic in-house program for FOWTs, and a reinforcement learning method with exhaust algorithm and deep deterministic policy gradient (DDPG) are embedded in DARwind as an AI module. Firstly, the methodology is introduced with the selection of Key Disciplinary Parameters (KDPs). Secondly, Brute-force Method and DDPG algorithms are adopted to changes the KDPs' values according to the feedback of 6DOF motions of Hywind Spar-type platform through comparing the DARwind simulation results and those of basin experimental data. Therefore, many other dynamic responses that cannot be measured in basin experiment can be predicted in good accuracy with SADA method. Finally, the case study of SADA method was conducted and the results demonstrated that the mean values of the platform's motions can be predicted with higher accuracy. This proposed SADA method takes advantage of numerical-experimental method, basin experimental data and the machine learning technology, which brings a new and promising solution for overcoming the handicap impeding direct use of conventional basin experimental way to analyze FOWT's dynamic responses during the design phase.

Original languageEnglish
Title of host publicationStructures, Safety, and Reliability
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791885123
DOIs
Publication statusPublished - 2021
Event2021 40th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2021 - Virtual, Online
Duration: Jun 21 2021Jun 30 2021

Publication series

NameProceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE
Volume2

Conference

Conference2021 40th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2021
CityVirtual, Online
Period6/21/216/30/21

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Energy Engineering and Power Technology
  • Mechanical Engineering

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