摘要
随着智能电网建设的深入,许多智能仪表被接入电网以获取用户的实时负荷数据。由于用户数量众多,单独对个体进行数据处理和分析是不现实的,所以需要对用户进行分类。采用模糊聚类算法来处理负荷侧不同用户的用电负荷数据,随机抽取了某小区的25个用户数据,并对其用电行为进行了分类。结合聚类有效性指标得到了算法的最佳聚类数,并进行了仿真分析。结果表明,模糊聚类算法在负荷侧不同用户用电行为分类中有着较好的表现。
With the deepening of smart grid construction, many smart meters are connected to the grid to obtain real-time load data from users. Due to the large number of users, it is unrealistic to in-dividually perform data processing and analysis on individuals. Therefore, users need to be classified. The fuzzy clustering algorithm is used to deal with the user load data, and the user＇ s electricity con-sumption behavior in a certain cell is classified. The optimal clustering number in the FCM algorithm is obtained through the clustering validity index. The experimental simulation analysis shows that the fuzzy clustering algorithm has an excellent performance in the grid user classification.
作者
谷涛
刘大明
GU Tao;LIU Daming(School of Computer Science and Technology,Shanghai University of Electric Power,Shanghai 200090,China)
出处
《上海电力学院学报》
CAS
2018年第5期497-500,共4页
Journal of Shanghai University of Electric Power
关键词
模糊聚类算法
智能电网
电力用户分类
聚类有效性指标
fuzzy clustering mean algorithm
smart grid
power users clustering
cluster validity index
