Application and practice of ubiquitous power Internet of things in marketing services

周 翔; 叶子强; 周贤富; 来心怡; 彭双武; 王 苗

doi:10.3969/j.issn.1009-1831.2019.S1.006

您当前的位置：

首页 >

文章列表页 >

Application and practice of ubiquitous power Internet of things in marketing services

更新时间：2026-03-05

- Application and practice of ubiquitous power Internet of things in marketing services
- Vol. 21, Issue S1, (2019)
- 作者机构：
  
  1. 国网浙江省电力有限公司青田县供电公司,浙江,丽水,323900
  2. 国网浙江省电力有限公司丽水供电公司,浙江,丽水,323000
  3. 国网浙江省电力有限公司杭州市富阳区供电公司,杭州,311400
  4. 浙江华云信息科技有限公司,杭州,310052
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2019.S1.006
  CLC：
- Published：2019
- 稿件说明：
移动端阅览
周翔, 叶子强, 周贤富, et al. Application and practice of ubiquitous power Internet of things in marketing services[J]. 2019, 21(S1).
DOI：

周翔, 叶子强, 周贤富, et al. Application and practice of ubiquitous power Internet of things in marketing services[J]. 2019, 21(S1). DOI： 10.3969/j.issn.1009-1831.2019.S1.006.

摘要

随着领先行业在服务体验的不断提升和持续优化，客户对办电服务的体验要求越来越高。遵循“三型两网”发展战略，探索泛在电力物联网在营销服务中的应用

实现电力用户的数据交互和良性互动，浙江公司基于物联网技术、业扩报装技术等，以提升办电效率为目的，研发用户业扩信息互动系统，形成“互动、留痕、倒逼、增值”业扩服务新模式，实现信息全景展示、互动友好高效、环节倒逼提速、痕迹溯源可控，提升了客户的办电体验，缩短了业务办理时间，提高了业扩办电效率。

Abstract

As the leading industry continues to improve and optimize the service experience

customers have higher and higher requirements on the experience of office electricity service. Following the development strategy of“three-type and two-network”and exploring the application of ubiquitous power Internet of things in marketing services

with the basis of Internet of things technology and industry expansion and packaging technology and the purpose of improving the efficiency of power - making

Zhejiang company has developed a user - expanded information interactive system to form a new model of“interaction

retention

reluctance

value-added”industry expansion services to achieve panoramic information display

interactive and efficient. The trace traceability is controllable. The customer’s power -on experience is improved and the industry’s expansion efficiency is improved.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Power supply demand division method for end users based on big data mining

Electricity load price forecasting based on sparse autoencoder nonlinear auto-regressive network

Key technologies of load forecasting in distribution network based on big data platform

Preliminary study on the construction of support platform for power marketing data sharing ecology

Life prediction of electric energy meter based on shared data sources and combined life stress model

Related Author

柳伟

张重阳

王云飞

姜世公

赵冬

胡丹蕾

王欣

史大洋

Related Institution

国网经济技术研究院有限公司

南京理工大学自动化学院

山东省建筑设计研究院有限公司

国网山东省电力公司淄博供电公司

国网河南省电力公司电力科学研究院

AI问答

⁰