基于多源数据库的居民购电行为多维度分析
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摘要
开展居民购电行为的多维度分析,可以充分了解不同类型的居民购电行为的统计特征以及变化规律。首先,在对居民购电过程分析的基础上,对牵涉到购电流程的一体化平台、售电管理系统、营销管理系统以及采集下发管理系统的字段进行了梳理,选择出反映电力客户属性与购电行为属性的的字段。其次,按照全市居民的用电量阶次比例,兼顾区县、供电所居民户数的占比情况,设计了抽样方案,确定了8000户的居民分析样本。然后,在对数据进行清洗的基础上,对数据库提取的众多字段,按其所代表的含义进行分类,形成行为维、时间维、属性维等多维度的分析体系。借助SPSS数据分析工具软件,对居民购电情况分维度进行深入分析,从而掌握居民在购电笔数、购电金额、购电渠购道以及购电方式、购电时间等方面所呈现出来的变化规律,并了解居民购电行为在不同用电水平之间、不同地域之间差异性。
Developing multi-dimensional analysis of electricity purchase of residents is helpful to understand their characteristics of purchasing behavior and its changing rules. Firstly,based on the analysis of electricity purchase process,the integration platform,the electricity sales management system,the marketing management system,and the metering supervision system,some fields related to electricity purchasing is selected. Secondly,considering the difference in annual electricity consumption and in area residents lived,a mix layered sampling scheme is designed. 8000 households were selected as analysis samples. Then,after data cleaning,four analysis dimensions are determined according to the similarity principle of fields,including behavior dimension,time dimension,and attribute dimension. Using SPSS as analysis tool,every dimension of electricity purchasing behavior are analyzed. Therefore,the rules in purchasing frequency,purchasing payment,purchasing channel,purchasing way,purchasing interval are obtained. In addition,the differences in purchasing behavior of residents referred to their classifications are also revealed.
Developing multi-dimensional analysis of electricity purchase of residents is helpful to understand their characteristics of purchasing behavior and its changing rules. Firstly,based on the analysis of electricity purchase process,the integration platform,the electricity sales management system,the marketing management system,and the metering supervision system,some fields related to electricity purchasing is selected. Secondly,considering the difference in annual electricity consumption and in area residents lived,a mix layered sampling scheme is designed. 8000 households were selected as analysis samples. Then,after data cleaning,four analysis dimensions are determined according to the similarity principle of fields,including behavior dimension,time dimension,and attribute dimension. Using SPSS as analysis tool,every dimension of electricity purchasing behavior are analyzed. Therefore,the rules in purchasing frequency,purchasing payment,purchasing channel,purchasing way,purchasing interval are obtained. In addition,the differences in purchasing behavior of residents referred to their classifications are also revealed.
引文
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[5]王继业,季知祥,史梦洁,等.智能配用电大数据需求分析与应用研究[J].中国电机工程学报,2015,35(08):1829-1836.
[6]国网浙江省电力公司.数说电网运营-电网企业运营大数据分析案例集萃[M].北京:中国电力出版社,2017.
[7]国网江苏省电力公司,江苏方天电力技术有限公司.电力营销大数据的研究及应用[M].北京:中国电力出版社,2016.
[8]白杨,李昂,夏清.新形势下电力市场营销模式与新型电价体系[J].电力系统保护与控制,2016,44(05):10-16.
[9]本书编委会,电网企业营配信息集成精益化管理[M].北京:中国电力出版社,2015.
[10]白杨,谢乐,夏清,等.中国推进售电侧市场化的制度设计与建议[J].电力系统自动化,2015,39(14):1-7.
[11]孙岩,江凌.居民能源消费行为研究评述[J].资源科学,2013,35(04):697-703.
[12]王德文,孙志伟.电力用户侧大数据分析与并行负荷预测[J].中国电机工程学报,2015,35(03):527-537.
[13]韩雨,王晓琳,高菊卉等.居民用电客户交费需求分析及渠道建设[J].大众用电,2015,(1),14-15.
[14]李满树,基于大数据分析的电力营业网点优化布置及应用研究[D],北京:华北电力大学,2017.
[15]郝庆利,基于大数据的用电行为分析关键技术研究[D].北京:华北电力大学,2007.
[16]夏清,白杨,钟海旺,等.中国推广大用户直购电交易的制度设计与建议[J].电力系统自动化,2013,37(20):1-7.
[17]国家统计局.网购新消费引领新生活———2017年北京网购调查用户报告.[EB/OL][2018]http:∥zhengwu.beijing. gov. cn/sj/sjjd/t1511679. htm.