基于电力数据的重点人群在室用电行为分析方法研究及应用

Analysis and application of indoor electricity behavior of key population based on electricity data

挖掘电力大数据蕴含丰富的隐藏信息是当前重要研究方向。针对市域治理中重点人群漏管、脱管、失控等管理难题,应用电力大数据融合驱动的理念,开展基于电力行为分析模型的重点人群在室监测技术研究。首先,结合市域治理需求构建基于多维电力大数据的分析应用框架;其次,创新性提出基于“电力行为-在室行为”异常分析模型,通过熵权法对用电特征向量信息进行动态权重分配形成动态加权余弦相似度分析模型,并对以历史样本相似度规律形成判断阈值,实现重点人群在室用电态势感知和异常研判;再次,面向多源系统及多方服务应用主体,进行了“平台流-技术流-业务流”三流合一的工程应用架构设计;最后,分析南京江北的公安数字化市域治理项目的应用成效,验证电力大数据深度挖掘对推动科技强警的重要作用。

Presently mining the rich hidden information contained in power big data is one of the important research directions. Aiming at the management problems such as leakage, out-ofcontrol, and out-of-control of key populations in urban governance,it is an important research direction to apply the concept of power big data fusion-driven and mining the rich hidden information contained in power big data.Firstly, the analysis and application framework based on multidimensional power big data is constructed according to the needs of municipal governance;Secondly, an anomaly analysis model based on“electricity behavior-in door behavior”is innovatively proposed, and form a dynamically weighted cosine similarity analysis model through the entropy weight method to dynamically distribute the power feature vector, so as to form a judgment threshold based on the similarity law of historical samples to realize the situation awareness and abnormal judgment of in-door electricity behavior of key populations. Thirdly, the engineering application architecture of“platform flow-technology flow-business flow”is designed for multi-source systems and multi-service application subjects. Finally, it introduces the application effect of the public security digital city project in Jiangbei, Nanjing, and verifies the important role of power big data deep mining in promoting the strengthening of the police through science and technology.