基于大数据的丽水电力运营监测分析

发布时间：2018-04-19 08:58

本文选题：容量变更 + 缴费行为　；参考：《华北电力大学(北京)》2017年硕士论文

【摘要】：国网公司在企业经营、运行过程中,产生了大量运营数据,也积累了海量的业务信息,随着公司经营活动和信息化的持续发展,各类数据高速增长。面对数据的汪洋大海,如何实现数据价值挖掘由“大海捞针”到“有的放矢”的转变?是我们面临的重大课题。数据是电力企业珍贵的财富,通过“大数据”技术,深入研究电力企业的各个专业,利用数据挖掘客户用电行为、负荷影响因素、电力设备隐患、物资供应问题等广泛领域,使其发挥出巨大的价值。基于公司较为完善的信息系统,以在线数据监测、分析为手段,深入发掘数据价值,依托各级专业部门的深度参与和闭环协作,对数据分析进行实际验证和应用,通过一系列数据分析方向、方法和具体案例从而为公司领导决策提供支撑。本课题通过对客户用电行为特征的监测分析,对公司进一步做好安全生产、电网规划、优质服务等工作具有重要的意义。本课题的数据主要来源于电力营销业务应用系统、用电信息采集系统、95598系统,应用了tableau等大数据分析软件,主要运用了聚类分析、分布分析、趋势分析、归因分析、相关分析等分析方法。
[Abstract]:In the course of enterprise operation and operation, the national network company has produced a large number of operation data and accumulated massive business information. With the continuous development of the company's business activities and information, all kinds of data are growing at a high speed.Facing the vast sea of data, how to realize the change of data value mining from "looking for a needle in a haystack" to "targeting"?It is a major task facing us.Data is the precious wealth of electric power enterprises. Through "big data" technology, we deeply study the various specialties of electric power enterprises, use data to mine customers' electricity consumption behavior, load influence factors, hidden trouble of electric power equipment, material supply problems, and so on.To bring it into full play.Based on the company's relatively perfect information system, with on-line data monitoring and analysis as a means to explore the data value in depth, relying on the deep participation and closed-loop cooperation of professional departments at all levels, the actual verification and application of data analysis are carried out.Through a series of data analysis directions, methods and specific cases to provide support for corporate leadership decisions.Through monitoring and analyzing the characteristics of customer's electricity consumption behavior, this project is of great significance for the company to do a good job in production safety, power network planning, quality service and so on.The data of this subject mainly come from the electric power marketing service application system, the electric power information collection system, the electric power information collection system, the power consumption information collection system and so on big data analysis software, mainly has used the cluster analysis, the distribution analysis, the tendency analysis, the attribution analysis, has used the cluster analysis, the distribution analysis, the tendency analysis, the attribution analysis.Correlation analysis and other analytical methods.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F426.61

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