基于数据挖掘的大用户用电特征分类方法研究

Research on the classification method of power consumption characteristics of large users based on data mining

为更好掌握大用户对象的耗电行为,实现对电力资源的按需分配,提出基于数据挖掘的大用户用电特征分类方法。计算大用户对象的集中用电量,通过划分用户消耗行为的方式,确定具体的耗电周期数值。在此基础上,研究用电用户所属类别,按照高维负荷数据的降维需求,提取用电行为模式的实际特征,实现基于数据挖掘的大用户用电特征分类方法的顺利应用。对比实验结果表明,应用新型特征分类方法后,大用户对象的平均耗电周期缩短至6.48 min,而最大电压升值却只能达到56.7 V,可准确掌握大用户对象耗电特征。

In order to better grasp the power consumption behavior of large user objects and realize the ondemand allocation of power resources,a classification method of large user power consumption characteristics based on data mining is proposed.Calculate the concentrated power consumption of large user objects,and determine the specific power consumption cycle value by dividing the user’s consumption behavior.On this basis,the categories of power users are studied,and the actual characteristics of power consumption behavior patterns are extracted according to the dimensionality reduction requirements of high-dimensional load data,and the successful application of the classification method of power consumption characteristics of large users based on data mining is realized.The comparison experiment results show that after applying the new feature classification method,the average power consumption period of large user objects is shortened to 6.48 min,while the maximum voltage appreciation can only reach 56.7 V,which can accurately grasp the power consumption characteristics of large user objects.