基于大数据的园区用户负荷特性分析

Analysis of Customer Load Characteristics in the Zone Based on Big Data

文章给出了基于大数据开展的园区用户负荷特性分析研究的基本方法和步骤,选择确定了负荷特性特征向量与算法,构建了基于K﹣means聚类算法的负荷特性分析模型。在此基础上,对北京某园区中不同用户实际运行数据进行分析。结果表明,用户的聚类效果在合理的范围,可精准挖掘、定量描述每类用户的用电行为特点,支撑园区运营商为用户提供定制化的服务和营销策略。

This paper presents the basic methods and steps for conducting research on the load characteristics of park users based on big data,selects and determines the load characteristics feature vectors and algorithms,and constructs a load characteristics analysis model based on the k﹣means clustering algorithm.On this basis,the actual operation data of different users in a park in Beijing are used for analysis.The results show that the clustering effect of users is within a reasonable range,which can accurately mine and quantitatively describe the characteristics of each type of user’s electricity consumption behavior,and support park operators in providing customized services and marketing strategies for users.