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AI-enabled design and optimization of fully coupled wind-wave integrated floating energy system

CORDIS · observation · Publication date unknown

ility, which requires a proper combination of FOWT and WECs. This project aims to construct an optimization design framework for cost-effective, high-efficiency and stabilized wind-wave IFES based on artificial intelligence (AI) techniques by: i) developing a fully coupled modelling methodology for considering the aero-hydro-servo-elastic effects; ii) developing a real-time hybrid testing method overcoming the conflicts between different scaling laws to validate the numerical model; iii) understanding the interaction mechanism between WECs and FOWT under different environmental loads and operating states; iv) developing a novel machine learning model to efficiently predict dynamic responses of IFES by introducing signal processing algorithms into convolutional neural network and bidirectional long-short term memory model with attention mechanism; v) determining Pareto solution sets using improved non-dominated sorting genetic algorithm. The outcome of this research will help to facilitate the development of offshore wind and wave energy resources in deep sea areas. This project will

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recordType

award

status

SIGNED

region

EU

value

276187.92

unit

EUR