Study On Multi-objective Optimization Design Method Of Wind Turbine Airfoil

Wind power as a kind of less pollution, lower costs of renewable energytechnologies has good prospects and economic value， and wind powertechnology has attracted more and more attention around the world. Blade is animportant part to capture wind energy in the wind turbine system, and itsproduction values accounts for about one-fifth of the total wind turbine value. Inaddition, airfoil is the most basic component elements in the blade structure, thepros and cons of its aerodynamic performance will directly affect the quality ofthe aerodynamic characteristics of the blade. Therefore, we should betterimprove airfoil geometric shape and design a dedicated airfoil of wind turbine. Ithas a great significance to improve the wind power utilization of wind turbinesand promote the development of wind power industry in China.In this paper, based on the current demands for wind turbine airfoilaerodynamic performance optimization design and problems existing in theoptimization study, the RBF-MOPSO methods, the radial basis function (RBF)model coupling multi-objective particle swarm optimization (MOPSO)algorithm, have been put forward in airfoil multi-objective optimization design. Firstly, Optimal Latin Hypercube Design was used to obtain more uniformairfoil samples in the airfoil geometry design space. The modified Hicks-Hennefunction was used to establish parametric model of airfoil geometry shape. Theresult displayed that modified Hicks-Henne function can improve the airfoilsamples overlap problem in airfoil trailing edge. Therefore, more completeairfoil parametric model can be obtained in the optimization design of airfoil.Secondly, the Computational Fluid Dynamics (CFD) method was used tocalculate airfoil aerodynamic performance, and the calculated results werecompared with experimental data. The radial basis function model wasestablished to replace the complex and time-consuming airfoil aerodynamiccharacteristics analysis model. The model can improve the efficiency of airfoiloptimization. Finally, multi-objective particle swarm optimization algorithm wasused to optimize the model. On this account, it can obtain the global optimalsolution in the scope of the design.Using the above methods, the main aerodynamic characteristics parametersof airfoil, for example the lift coefficient Cland the lift to drag ratio Cl/Cd, wasused as optimization goal, and controls parameter ckin parameterized modelingof airfoils was used as design variable. Then single objective and multi-objectiveoptimization were studied on wind turbine airfoil NACA4418and special airfoilFFA-W3-301. CFD numerical simulation calculation method was used to verifythe accuracy of the results. Optimization results show that establishedRBF-MOPSO airfoil multi-objective optimization method in this paper can optimize the main airfoil aerodynamic performance parameters. Airfoil liftcoefficient Cland lift to drag ratio Cl/Cdwere improved, and the calculationerrors were smaller. Wind turbine airfoil aerodynamic performance gets a boost.Optimization results validate that the RBF-MOPSO method has a certainvalidity and practicality, and also provides an effective means in optimizationdesign of airfoil.