论文部分内容阅读
由于在非定常气动环境下运行的风力机会受到非定常气动载荷的作用,采用2种降阶模型(ARMA模型和Volterra级数模型)对风力机翼型的非定常气动载荷进行了预测,并将预测结果与CFD仿真结果进行比较,以验证模型对非定常气动载荷的预测能力.结果表明:在流动附着工况下,ARMA模型有较好的预测能力,在流动分离工况下Volterra级数模型的精度较高;这2种降阶模型能够在相对较小的计算成本条件下给出不同工况下风力机随时间变化的气动特性,为风力机气动弹性方面的设计与优化提供参考.
Due to unsteady aerodynamic loads on wind turbines operating in unsteady aerodynamic environments, unsteady aerodynamic loads on wind turbine airfoils are predicted using two reduced-order models (ARMA model and Volterra series model) The prediction results are compared with the CFD simulation results to verify the model’s ability to predict unsteady aerodynamic loads.The results show that the ARMA model has good predictive ability under the condition of flow attachment and the Volterra series model Which can provide the aerodynamic characteristics of the wind turbine with time under different conditions and provide reference for the design and optimization of the aeroelasticity of the wind turbine under the relatively small computational cost.