Abstract: Conventional single-object design methods which have been adopted previously should not meet the requirements universally because of the diversity of wind turbines blade design-objectives. Therefore, the contradiction between high capacity and heavy load of large-scale wind turbines must be balanced. In order to solve the mention challenge, design blades of a 5 MW wind turbine with taking the maximum annual energy production(AEP) and the minimum blade mass as the optimization objectives based on multi-objective genetic algorithm, and get the Pareto-optimal solutions. Comparing with the blade of National Renewable Energy Laboratory(NREL) 5 MW wind turbine, the results show that the Pareto-optimal solutions are better than the reference blade. The maximum increased amount of AEP achieves 3.3% and the decrement reaches 8.7%. The design purpose is reached showing by one of the Pareto sets with 3% higher annual energy production and mass reduction about 3.8%. Optimal blades have smaller thrust coefficient and root bending moment with higher maximum coefficient of power in rated wind speed, the power characteristics are little different from the reference blade in design wind-speed range, but these have higher output power and smaller thrust coefficient in low wind speeds.

Key words: genetic algorithm, multi-object optimization, Pareto solutions, wind turbine blade