Research on service strategy recommendation model of electric power customers on the background of new electricity system reform

孔月萍; 吴飞; 陈新崛; 黄茜; 庞芹; 李洁莹; 韩琳; 章劲秋

doi:10.3969/j.issn.1009-1831.2019.01.017

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Research on service strategy recommendation model of electric power customers on the background of new electricity system reform

更新时间：2026-03-05

- Research on service strategy recommendation model of electric power customers on the background of new electricity system reform
- Vol. 21, Issue 1, (2019)
- 作者机构：
  
  1. 国网江苏省电力有限公司电力科学研究院客户服务中心,南京,210000
  2. 朗新科技股份有限公司,杭州,310012
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2019.01.017
  CLC：
- Published：2019
- 稿件说明：
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孔月萍, 吴飞, 陈新崛, et al. Research on service strategy recommendation model of electric power customers on the background of new electricity system reform[J]. 2019, 21(1).
DOI：

孔月萍, 吴飞, 陈新崛, et al. Research on service strategy recommendation model of electric power customers on the background of new electricity system reform[J]. 2019, 21(1). DOI： 10.3969/j.issn.1009-1831.2019.01.017.

摘要

新电改的深化推进加快了市场“多买多卖”格局形成，基于数据挖掘的精准电力营销对加强电力企业客户关系管理、增强市场竞争力具有重要作用。基于服务策略清单梳理成果，抽取江苏武进区样本大客户作为训练样本，选用基于随机森林推荐算法的大数据分析方法，探索并构建了服务策略推荐模型，实现面向不同属性客户的服务策略略差异化精准推送。

Abstract

The deepening of the new electricity system reform has accelerated the formation of a pattern of more buying and selling in the market. Precision power marketing based on data mining plays an important role in strengthening customer relationship management and enhancing market competitiveness of power enterprises. Based on the service policy list combing results

sample customers in Jiangsu Wujin are taken as training samples

big data analysis method based on random forest recommendation algorithm is adopted

the service policy recommendation model is explored and constructed

differentiated and precise push of service strategies for customers with different attributes is realized.

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