A dynamic probabilistic analysis method for wind turbine rotor based on the surrogate model

Abstract

Due to the long and flexible characteristics of the wind turbine blade, the influence of the fluid–structure interaction (FSI) on the dynamic response results cannot be ignored. The dynamic analysis of the wind turbine rotor based on the fluid–structure interaction is very computationally expensive, and the dynamic reliability analysis considering the influence of randomness usually requires a large number of computational samples. In this study, a surrogate model-based dynamic probabilistic analysis method for the characteristics of the wind turbine rotor was established, combining numerical simulation, intelligent algorithms, and data mining methods for wind turbines. This method allows for fast and inexpensive reliability and sensitivity analysis by building accurate surrogate models with a limited number of expensive fluid–structure interaction (FSI) samples. In the case of a 5 MW wind turbine rotor, the average relative error of the test was 0.093%, the reliability was 0.9515, and two variables insensitive variables were found. The results showed that this method could effectively analyze the reliability and sensitivity of the wind turbine rotor, adapted well to the nonlinear and high dimensional characteristics of the wind turbine rotor, and reduced the cost of wind turbine research by controlling the number of expensive samples. In addition, this research provided a reference for using intelligent algorithms and data mining methods in wind turbine design.