Dynamic response and power generation of floating offshore wind farms under different wave conditions using an efficient evaluation method

Floating offshore wind farms (FOWFs), as a key technology for harnessing deep-sea wind energy resources, face significant challenges due to the complex environmental loads at sea. Existing commercial software and computational methods often struggle to efficiently and accurately predict the dynamic responses and power generation of FOWFs. To address this, this paper integrates a dynamic wake model, catenary equations, and Morison's formula to propose an efficient evaluation method for studying the dynamic responses and power generation performance of FOWFs under coupled wind–wave–current–mooring loads. Using the Offshore Code Comparison Collaboration Continuation semi-submersible platform equipped with the National Renewable Energy Laboratory 5 MW wind turbine as the research object, the reliability of this method was first validated through free decay tests and motion tests under wave and wind conditions. Furthermore, for an FOWF composed of nine wind turbines, this study focused on the effects of calm water and different wave conditions on the motion characteristics and power generation performance of each wind turbine. The results indicate that wave loads induce wave-frequency motion responses in the turbines, with wave height and wave period primarily affecting the characteristics of the surge motion and power generation curves. Additionally, under different wave directions, the wind turbines exhibit “8-shaped” motion trajectories. For the annual power generation, the front-row wind turbines remain stable across different wave parameters, while the power generation of the rear-row wind turbines shows some variability with changes in wave parameters. Compared to traditional high-fidelity computational fluid dynamics methods, the proposed method significantly reduces computational resource requirements, providing an efficient and practical tool for predicting the power generation of large-scale FOWFs. Therefore, it has huge potential in the layout optimization design and motion control of FOWFs.