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摘要
The challenge of wind turbine blade design is to balance the conflict between high capacity and heavy system loads introduced by the large scale rotor. To solve this problem, we present a multi-objective optimization method to maximize the Annual energy production (AEP) and minimize the blade mass. The well-known Blade element momentum (BEM) theory is employed to predict the aerodynamic performance and AEP of the blade. The blade is simplified as a thin Bernoulli beam. The cross section is modelled as a combination of composite layer, shear webs and spar caps typically. The strain of every cross section has been considered as a constraint to minimize the spar cap thickness for minimizing the blade mass. An improved genetic algorithm (NSGA-II) is applied to obtain the Pareto front set. Several solutions of the Pareto set are selected to compare with the reference blade (NREL 5MW blade). Performance of the rotors on design condition is simulated by STAR-CCM+ to verify the results of BEM theory. Optimal results show that the present blade, which is fully superior to the reference blade, can be selected from the Pareto set. The optimization design method can provide a superior blade with an increase by 2.48% of AEP and a reduction by 5.52% of the blade mass. It indicates the present optimization method is effective. Results of numerical simulations show that the spanwise flow would be increased obviously in tip region of the reference blade. The reason is that chord length variation in blade tip affects the flow and causes minor stall. The abrupt change of chord distribution in blade tip should be avoided to reduce the spanwise flow in initial blade design.
- 出版日期2016-8
- 单位上海理工大学
