基于用户用电行为数据分析的电力精准营销研究

基于用户用电行为数据分析的电力精准营销研究(开题报告,论文16000字)
摘要
在电力行业中，随着互联网+能源概念的提出，和智能电网的建设和不断完善，在发电-输电-配电-供电等各个环节中大量的智能监测设备投入使用。这些设备运行过程中，积累了大量的电力信息数据。这些数据中潜藏着大量的有用信息，可以为电力公司的运营管理提供帮助。在互联网快速发展和移动端的普及大形势下，客户资源成了重要的资源，服务成了抢占市场制高点的关键要素。精准营销顺应了这样的趋势，强调为特定客户提供特定服务, 其关键在于准确定位用户。大数据为电力企业分类和定位用户提供了一种经济高效的解决方案，通过运用聚类和关联分析的方式，可以准确的刻画出用户的用电行为特征。电力公司可以确定更加精确地调度区域供电，制定电价策略，为用户提供的个性化、定制化服务。
关键词：电力大数据，精准营销，聚类分析，关联分析 
Research on Power Precision Marketing Based on User Power Behavior Data Analysis
 
ABSTRACT
In the power companies, with the introduction of the concept of Internet plus energy and the construction and continuous improvement of smart grid, a large number of intelligent monitoring devices have been put into use in all aspects of generation, transmission, distribution and power supply. During the operation of these equipments, a large amount of electric power data has been accumulated. There are a lot of useful information hidden in these data, which can provide help for the operation and management of power companies. With the rapid development of the Internet and the popularity of mobile terminals, customer resources have become an important resource, and service has become the key factor to seize the commanding heights of the market. Precision marketing conforms to this trend and emphasizes providing specific services to specific customers. The key is to accurately locate users. Big data provides an economical and efficient solution for power enterprises to classify and locate users. By using clustering and correlation analysis to analyze power consumption data, users'electricity consumption behavior characteristics can be accurately depicted. Power companies can determine more precise dispatch of regional power supply, formulate pricing strategies, and provide personalized and customized services for users.

Key words: big power data, precision marketing, cluster analysis, correlation analysis

目录
摘要    I
ABSTRACT    II
第一章 绪论    1
1.1 问题提出    1
1.2 国内外研究现状    1
1.3论文的主要研究内容和方法    3
第二章 文献综述    4
2.1电力大数据应用研究    4
2.2用户用电行为研究综述    4
2.3 电力精准化营销研究综述    6
第三章 用户用电数据的获取和预处理    8
3.1数据的获取    8
3.2数据的预处理    8
3.2.1 数据清洗    8
3.2.2 数据降维    10
3.2.3数据的标准化    10
第四章 用户用电行为分析    11
4.1聚类处理数据    11
4.1.1 K-means算法简介    11
4.3.2聚类分析流程    11 [来源：http://www.think58.com]
4.2聚类结果分析    12
4.3关联分析    13
4.3.1 Apriori分析流程    13
4.3.2关联规则结果分析    14
第五章 精准化的电力营销策略    16
5.1基于用户分类的营销策略设计    16
5.2 精准营销策略实施问题分析    18
第六章 总结与展望    20
6.1研究总结    20
6.2 研究局限与展望    21
参考文献    22
致谢    26 [资料来源：http://think58.com]