Abstract: In order to meet the blade design challenge brought by the development of super large wind turbines,the aerodynamic and structural optimization design of the large-scale downwind flexible blade is studied emphatically by the multi-objective design method.The parametric models of chord length,twist angle and flapping stiffness are established. The NREL 5 MW downwind wind turbine blade is optimized based on the Non-dominated Sorting Genetic Algorithm to achieve the maximum annual energy production（AEP）and the minimum blade root flapping bending moment（BRFBM）. A Pareto optimal solution set is obtained,and three representative optimal solutions are selected for analysis. The analyses show that the BRFBM of the downwind blade will be greatly reduced because the centrifugal moment can offset part of the flapping bending moment. For A-blade,the BRFBM and the blade flapping stiffness are reduced by 7.951% and 27.071% respectively at the cost of 0.963% AEP loss,thereby can achieve the lightweight optimization design of an extreme-scale downwind flexible blade. Furthermore,the influence mechanisms of chord length,twist angle and flapping stiffness on the optimization goal are analyzed,and it is found that the flapping stiffness parameter has the greatest influence on the two optimization goals.