改进型模糊C均值聚类算法的电力负荷特性分类技术研究

模糊C均值聚类算法(FCM)是目前应用较多的电力负荷分类算法,但FCM算法存在着对初始聚类中心敏感及需要人为确定聚类数目的问题,针对这个问题,提出了先采用一种快速算法来确定负荷聚类数目和聚类中心,将得到的聚类中心和聚类数目作为FCM的初始输入,再用FCM对负荷进行分类的改进型FCM分类方法,以此减少聚类数目较多时大量的人工参与及分析工作,并通过实际算例分析验证了所提出的分类方法的正确性。

Power Load Characteristic Classification Technology Research Based on An Improved Fuzzy C-means Clustering Algorithm

Fuzzy C-means Clustering is the general load classification algorithm, However, the FCM is sensitive to the initial clustering center and cannot automatically determine the clustering number. In order to solve the problem, this paper proposes a modified FCM clustering method. The modified FCM clustering method utilizes an fast algorithm to determine the clustering center curve and clustering number firstly, the computer result is treated as the initial input of FCM, then use FCM to classify the power load. The modified FCM clustering method can reduce largely manual handling works. The practical examples verify the correctness of the proposed clustering method.