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A Python-based integrated time domain analysis method for floating wind turbines
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AI
DOI：10.1016/j.oceaneng.2025.120782.png)
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Abstract
En 中文
Integrated analysis and design optimization of floating wind turbines (FWT) is vital for cost reduction and efficiency enhancement. However, existing simulation software faces scalability and efficiency limitations in early design phases and multi-objective optimization. To address these challenges, this study develops a Python-based integrated time-domain simulation method for FWT, named Pywind. The aerodynamic module leverages blade element momentum (BEM) theory with corrections, including dynamic stall, for accuracy under high wind speeds. The hydrodynamic module uses potential flow theory and incorporates viscous effects via Morison's equation. The structural and dynamic modeling employs the Newton-Euler method for single rigid-body dynamics, providing a streamlined yet robust representation of system behavior with high computational efficiency. The mooring system combines a quasi-static catenary approach with a lumped mass method, while the control module supports variable rotor speed and pitch control for constant torque and power output. Verification was conducted using OpenFAST across various aspects, such as system dynamics, external load calculations, and structural responses. The results exhibited strong agreement with OpenFAST, with discrepancies in mean values remaining within 2%. This Python-based implementation offers significant potential for advancing industrial design and optimization of FWT while supporting innovative multi-physics simulation and AI-driven research in academia.
Keywords:
Floating wind turbine
Time-domain method
Integrated analysis
Code-to-code verification
Journal
IF:
5.5
Papers:
5.8K
Citations:
7.6W
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