为解决现有的用于电力系统在线安全分析的估计等值法精度低、收敛性弱的问题，给出了较精细的等值发电机加综合负荷的等值系统模型，以提高等值精度，并提出了基于差分进化( DE) 算法的等值系统参数辨识策略．为解决 DE 存在的早熟收敛问题，构造变异方式不同的两个差分进化群，两群并行进化且定时交换信息，以增加种群的多样性，改善算法的收敛性．仿真结果表明: 改进的双群体 DE 算法有效解决了等值系统的参数辨识问题，算法简单、收敛快，辨识的参数精度高、鲁棒性好; 所建立的等值系统模型更符合电网实际，等值后外部系统的动态特性基本被保留; 所提基于改进DE 的估计等值法可用于在线大规模外部系统的等值化简．

As the existing estimation equivalence method for online safety analysis of power systems is of low accu-racy and weak convergence,a refined model of equivalent system,which comprises the equivalent generator andthe composite load,is proposed to improve the accuracy of dynamic equivalence,and a parameter identificationstrategy based on differential evolution (DE) algorithm is presented,Moreover,in order to overcome the prematureconvergence of DE,two differential evolution swarms with different variations are constructed,which help to in-crease the diversity of swarms and improve the convergence of DE algorithm through parallel evolution and regularmessage exchange.Simulated results show that (1) the improved DE algorithm with parallel swarms is effective inthe parameter identification of equivalent systems and is of simplicity and rapid convergence; (2) it helps to identi-fy parameters with high accuracy and strong robustness; (3) the obtained equivalent system model accords wellwith practical power systems and effectively preserves the main dynamic characteristics of the external system; and(4) the new estimation equivalence method is applicable for the online equivalent simplification of large- scale ex-ternal power systems.