Wind energy is a kind of clean energy with abundant resources.Since the current world energy situation is tight,large-scale development of wind energy has important economic and ecological significance.The thesis focuses on blades and airfoils of horizontal axis wind turbines.Combining airfoil parameterization with genetic algorithms to optimize two-dimensional airfoil,and regenerating wind turbine blades to improve wind turbine power output;Combining the trailing edge flap modification with the particle swarm optimization algorithm to obtain an optimized flap airfoil and apply it to the blade tip,thereby reducing the extreme load and fatigue load of large wind turbine blades.The pressure field distribution and load characteristics before and after the optimization of the airfoil and blade are explored,and the purpose is to provide a basis for the performance optimization and load reduction of large wind turbines.The main work content of the thesis:(1)Starting from the blade engineering design process,the development of wind turbine airfoil improvement methods,blade optimization and flow control development are analyzed and summarized.The research content,research process and methods are given.(2)The wind turbine blade was revised and designed based on Wilson blade design theory.For the airfoil constituting different parts of the blade,according to its operating characteristics and functions,different optimization methods are adopted.The CST parameterization method was coupled with genetic algorithm to optimize the blade tip and the central airfoil.The results show that after optimization,the lift coefficient and lift-to-drag ratio increase at each angle of attack,the drag coefficient decreases to a certain extent,and the maximum relative thickness and position change are controlled within a certain range,ensuring the continuity of the optimized blade span.Combining the trailing edge asymmetric thickening method with genetic algorithm to optimize the airfoil near the root of the blade.The results show that the lift coefficient has been greatly improved,up to 16.49% at the design angle,and the drag coefficient has also increased,but the increase is less than the lift coefficient.(3)The optimized airfoil was applied to the original blade.Simulation results show that the rated power was increased by 87.9k W,which has an increase of 12.33%.The pressure of pressure surface at the leading edge between the 70% of the blade expansion has been greatly increased,and the pressure near the middle of the blade tip has also increased.The area of the leading edge pressure at the tip of the suction surface and the 70% of the blade expansion increased,the minimum pressure decreased,and the blade trailing edge pressure decreased accordingly.The pressure difference between the pressure surface and the suction surface increases,which can provide more lift.(4)With the increase in the size of wind turbines,the ultimate and fatigue loads on blades have increased significantly.By adding the trailing edge flaps to the 70% position of the blade expansion,and coupling the trailing edge flap modification method with the particle swarm optimization algorithm,taking the total lift coefficient in a specific angle of attack as the optimization target,the optimal characteristics under different flap deformation angles are obtained.The optimized airfoil was applied to a 10 MW wind turbine,and the aeroelastic simulation code h GAST was used to assess its load alleviation capability.The simulation results show that before the rated wind speed,setting the active flaps did not show a significant load reduction effect,and the blade root torque increased.However,at this time,the blade is subjected to a small load and a small swing amplitude,which does not cause severe load on the blade.After the rated wind speed,the wind turbine is in the pitch operation state,and the blade torque fluctuates between the maximum load and the reverse maximum load.When the trailing edge flap is set,the maximum torque is reduced,and the torque variation range is also reduced,which shows the characteristics of reducing the ultimate load and the fatigue load. |