摘要
基于上海地区居民与工商业用户的海量用电数据,利用大数据多维属性,采用局部线性插值法进行了异常值处理;结合数理统计、聚类等数据挖掘方法,开展了用户行为的特征分析,发掘了行业间的关联关系,为进一步指导用户个性化智能用电,提高电网需求侧能效管理水平具有建设性意义。
Based on massive electricity consumption data of residents and industrial and commercial customers in Shanghai,consumer behavior is analyzed by data mining. The piecewise-linear-interpolation method is taken to revise the outliers,and the characteristic of customer behavior is studied by mathematical statistics and cluster method. This research provides constructive guidance for the personalized intelligent electricity use and the energy efficiency management improvement.
出处
《华东电力》
北大核心
2014年第12期2922-2925,共4页
East China Electric Power
关键词
大数据
电网
需求侧
用户行为
big data
power grid
demand side
consumer behavior
