针对同调动态等值法中的同调发电机分群问题，提出了基于粒子群优化( PSO)的模糊c 均值聚类( FCM) 算法来识别同调发电机．该算法将聚类中心数作为粒子进行编码，利用粒子群优化的并行性和全局搜索能力，通过不断更新粒子的速度和位置实现寻优，克服了模糊c 均值聚类对初值的依赖和易陷入局部极值的缺点．文中还构造了聚类有效性函数来进行聚类效果的评价．IEEE10 机39 节点系统仿真表明，该算法具有快速、准确、简单、易实现的特点，有效解决了同调发电机的识别问题，可用于电力系统不同运行方式下同调发电机的分群．

In order to solve the partition problem of coherent generators in the dynamic equivalent method based oncoherency,an algorithm marked as PSO-FCM,namely,the fuzzy c-means clustering ( FCM) based on the particleswarm optimization ( PSO) ,is presented.In this algorithm,the cluster center is taken as a particle for encoding,and the parallel property and the global searching capacity of the PSO algorithm are applied to the optimizationthrough continuously renewing the velocity and position of the particle. Thus,the dependency of the FCM algorithmupon the initial value and the risk of falling into local optimization are overcome. Moreover,in order to evaluate theclustering validity,a validity function is constructed. Simulated results on IEEE 10-generator 39-bus system showthat the PSO-FCM algorithm is suitable for the partition of coherent generators of electric power systems in variousoperation modes because it is of simplicity,easy realization,high accuracy and high speed.