Structural Optimization and Influence Factors on Reliability for Composite Wind Turbine Blade

Good structural performance and reliability are two key objectives in design of wind turbine blade. To improve the natural frequency of blades to avoid resonance effectively, but it also increases the weight and direct manufacturing cost of blades. To achieve the best trade-off between mass and first-order frequency of blades, this paper presents a method of structural optimization based on multi-objective genetic algorithm NSGA-II. A small wind turbine blade is taken as case study. The CFD computation is performed to obtain the aerodynamic load, and the FEM is applied to obtain structure responses. With the weight minimization and the first-order frequency maximization of the blade as two goals, the optimization model is constructed and the Pareto solution set of two goals is obtained. Compared with original scheme, the weight of the optimized blade is reduced by about 15%. On the premise of avoiding blade resonance, the solution with the weight as light as possible is selected as the design scheme. The delamination failure, buckling failure, strength failure, and other failure modes of the blade with thin airfoil are analyzed, and the results show that the delamination failure and buckling failure of the blade can be ignored temporarily. Time-varying wind speed and some mechanical parameters of composite materials are taken as random input variables. The reliabilities of the design scheme with multiple failure modes are evaluated, and the reliability sensitivity is analyzed by combining FEM, BP neural network method and Monte Carlo Simulation (MCS) method. The results show that wind speed and longitudinal elastic modulus of uniaxial fiberglass are critical influence factors for affecting reliabilities of the blade. Meanwhile, the results can also provide some references about the timing of shutting down wind turbines and the selection of composite materials.