摘要
基于智能电网的双向通信基础设施与先进量测设备,个性化推荐技术从收集的需求侧大数据中获取知识,为优化电网运营提供有力支持,并向终端用户推荐面向能源的产品/服务/建议。研究首先探讨了个性化推荐技术的原理以及在需求侧中引入个性化推荐技术的前景;其次,介绍了实现智能电网需求侧推荐系统的关键技术,并对现有研究工作以及未来构建的需求侧个性化推荐系统进行分析;最后,讨论了实现需求侧个性化推荐系统可能遇到的挑战。
Driven by the climate change and energy shortage, smart grid has obtained rapid growth worldwide as a solution for the sustainable development of human society. How to extract information from the demand side big data and optimize the grid operation based on the two-way communication infrastructure and advanced metering infrastructure of the smart grid has become an important research topic. As a technology of data analysis and information filtering, personalized recommendation technology is expected to support the information retrieval from the grid data, and recommend energy-oriented products/services/suggestions to the end user. This paper firstly introduces the basic principles of personalized recommendation technology as well as the prospect of introducing this technology into the demand side. Then, some key technologies of implementing the personalized recommendation systems in the smart grid are presented. Furthermore, this paper reviews the existing research in this field and discusses some potential and promising demand side recommendation systems in future. Finally, some challenges of practically deploying the personalized recommendation systems in the smart grid are examined.
作者
王喜宾
文俊浩
廖臣
赵瑞锋
WANG Xibin;WEN Junhao;LIAO Chen;ZHAO Ruifeng(School of Data Science,Guizhou Institute of Technology,Guiyang 550003,P.R.China;School of Big Data&Software Engineering,Chongqing University,Chongqing 401331,P.R.China;Information Center of Guizhou Power Grid Corporation,Guiyang 550005,P.R.China;Electric Power Dispatching and Control Center of Guangdong Power Grid Corporation,Guangzhou 510600,P.R.China)
出处
《重庆大学学报》
CSCD
北大核心
2022年第1期38-49,共12页
Journal of Chongqing University
基金
国家自然科学基金资助项目(61672117)
贵州省科技厅人才项目([2017]5789-21)
贵州理工学院高层次人才项目(XJGC20190929)。
关键词
个性化推荐
需求侧管理
智能电网
推荐系统
需求侧响应
大数据
personalized recommendation
demand side management
smart grid
recommendation system
demand response
big data