Adaptive whole-machine loss calculation methodology within sensor-based control framework for large-scale offshore floating wind turbines

As the offshore wind energy sector advances into deeper, remote sea areas with escalating single-turbine power, the capacity of large floating wind turbines has expanded, heightening demands for control system precision. Traditional static loss model-based strategies struggle to meet dynamic operational needs in complex marine settings. This paper introduces a collaborative control method leveraging adaptive modeling of whole-machine dynamic losses. By developing a multi-physics coupling model and integrating real-time condition sensing with adaptive algorithms, it enables dynamic monitoring and active regulation of global losses. This approach combines multi-dimensional parameter online identification, model predictive control, and a multi-actuator collaborative framework, utilizing intelligent algorithms for parameter optimization. Theoretical and simulation analyses—based on the IEA 15 MW reference wind turbine model (simulated via Bladed + MATLAB/Simulink, with environmental parameters: wind speed 3 ~ 25 m/s, wave height 2 ~ 8 m, water temperature 10 ~ 30℃)—confirm improved energy conversion efficiency (+ 3.2% vs. +2.1% in latest studies), reduced fatigue loads (−12.5% vs. −9.8% in peers), and enhanced operational stability. It offers a new avenue for offshore wind power intelligent control.