A Coupled Framework for Short-Term Mooring Tension Prediction and Ballast Control for Floating Offshore Wind Turbines

Floating offshore wind turbines (FOWTs) experience six-degree-of-freedom motions and related forces acting on their mooring systems. Under combined wind, wave, and current loading, platform motions and mooring line tensions are dynamically coupled. To support ballast control decisions without repeatedly running high-fidelity coupled simulations, this paper developed a specialized computational framework combining FAST-AQWA time-domain simulation, short-term mooring tension prediction, and ballast control optimization. Five predictive models were trained and evaluated using the same sliding window dataset. After training, the predicted mooring tension data were used for ballast control calculations. In this study, the bidirectional long short-term memory (BiLSTM) model showed the highest prediction accuracy for mooring tension and the Model Prediction Control (MPC) produced a smoother control action and significantly reduced the amplitude of low-frequency roll and pitch. The proposed framework provides a practical approach for combining short-term response prediction with ballast control and demonstrates that explicit mooring tension constraints must be incorporated into the design considerations of subsequent control systems.