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大型风电场的动态等值和建模是研究多时空尺度风电场并网问题的基础,建立精度较高的等值模型是其中的关键问题.以双馈风电机组为研究对象,针对直接聚合等值成单机存在的动态误差较大的问题,建立了一种结合粒子群优化算法的等值模型来提高动态等值精度.首先采用先聚合后优化的思想,将风电场参数聚合等值成单机,分别对电气参数、无功参考值、有功控制器参数、有功直流电压控制器参数运用粒子群算法进行优化,对比各种等值模型与详细模型在三相短路故障时的动态等值误差.研究结果表明,对有功和直流母线电压控制器参数优化后的等值模型能够准确地反映双馈机组风电场并网点的动态特性.“,”Dynamic equivalence and modeling of the wind farm are the basis of multiple spatiotemporal scales wind power integration studies;establishing higher accuracy equivalent model is one of the key issues.Because equivalent to one-DFIG model makes large dynamic error,a one-DFIG equivalent model combined with particle swarm algorithm is proposed in this paper to improve dynamic equivalence accuracy.Based on one-DFIG equivalent model,these factors including electrical parameters,reactive power reference value,active power controller parameters and DC bus voltage controller parameters are optimized.Dynamic equivalence error of each equivalent model is compared with detailed model in the setting of threephase short circuit fault.The conclusion is that optimizing active power controller parameters and DC voltage controller parameters equivalent model can accurately reflect the dynamic characteristics of integration point of doubly-fed induction generator sets.