基于模糊聚类的电力客户用电行为模式画像

A portrait of electricity consumption behavior mode of power users based on fuzzy clustering

随着电力客户数据采集频度不断提高、数据分析维度不断扩展,客户的用电行为变得更加复杂。客户标签和画像技术的发展,给客户用电行为分析带来了更直观、简洁的表现方式。论文基于海量的客户档案、负荷、电量数据,综合考虑客户用电特征、影响因素,建立了客户用电行为标签库,并采用模糊聚类算法进行客户用电模式分析,实现不同类型客户的用电行为模式画像。某地区20 000户工商业客户的用电行为模式画像分析结果表明:文中选取的用电行为标签合理有效、采用的聚类算法效果显著、客户画像精准,能够为电力公司掌握客户用电习性、挖掘客户需求、提高服务水平提供有力支撑。

With the increasing of frequency of data acquisition and the dimension of data analysis,the analysis of household electricity consumption behavior becomes more complex.The development of user tag and portrait technology brings a more intuitive and concise expression to the analysis of electricity consumption of power users.Based on massive user archives,power load and electricity consumption data,considering the electricity consumption characteristics and influencing factors of users,a user behavior tag library is built.Fuzzy clustering algorithm is used to conduct the analysis of electricity consumption mode of users,so as to achieve different types of electricity consumption behavior portraits.The results of 20 000 industrial and commercial users show that the selected tags of electricity consumption behavior is reasonable,the clustering algorithm is effective,and user portraits is precise.The results can provide powerful support for power companies to understand the electricity consumption habits,mine electric power needs of users and improve service level.