摘要
在营配数据核查的工作中,出现生产人员无法通过配电自动化系统的间隔名称准确定位到营销系统的对应用户,营销人员也无法通过用户名称准确找到生产侧电源点,电源点和用户溯源难的问题。本文采用简单相关系数算法,基于营销业务应用系统的用户、计量点等档案信息,配电自动化、用电信息采集系统的电流、电压、功率数据,将数据按需接入到数据中台共享层DWS数据库中,通过分析层的Spark等计算分析组件对共享层数据进行加工、分析,构建电源点自动识别模型,分别对比用户和间隔的电流、电压、功率相似度,解决电源点和用户溯源难的问题。结果表明,该算法高效、简洁、精准率高,通过结果分析得出此算法可有效实现电源点和用户的双向溯源,辅助业务人员快速确认生产侧和用户侧拓扑连接准确性。
During the verification of the camp and distribution data,it appeared that the production staff could not accurately locate the corresponding users of the marketing system through the interval name of the distribution automation system,and the marketers could not accurately find the power point of the production side through the user name,and the power point and user traceability were difficult.This paper adopts the simple correlation coefficient algorithm,based on the file information of users and metering points from the marketing business application system,and the current,voltage and power data from the distribution automation and electricity consumption information collection system,the data is connected to the DWS database of the data middle table sharing layer on demand,and the data of the sharing layer is processed and analysed by the Spark and other computational analysis components of the analysis layer,and the automatic identification model of power points is constructed.The current,voltage and power similarity of users and intervals are compared respectively to solve the problem of difficult traceability of power points and users.The results show that the algorithm is efficient,concise and highly accurate.The analysis of the results shows that the algorithm can effectively achieve bi-directional traceability of power points and users,and assist business personnel to quickly confirm the accuracy of topological connections on the production and user sides.
作者
于烨
刘思尧
郭安乐
杨勇
YU Ye;LIU Siyao;GUO Anle;YANG Yong(State Grid Ningxia Electric Power Information&Communication Company,Yinchuan 750001 Ningxia,China;BeiJing China-Power Information Tecnology Co.,Ltd.,of State Grid Info&Telecom Group,BeiJing 102200,China)
出处
《电力大数据》
2021年第2期47-54,共8页
Power Systems and Big Data
关键词
电源点
用户
溯源
台区
间隔
配电自动化
power point
user
traceability
station area
interval
distribution automation
