边云协同智能技术在电力领域的应用

doi:10.11959/j.issn.2096-3750.2021.00204

物联网学报 ›› 2021, Vol. 5 ›› Issue (1): 62-71.doi: 10.11959/j.issn.2096-3750.2021.00204

• 专题：物联网边缘智能与雾计算 • 上一篇下一篇

边云协同智能技术在电力领域的应用

韩青¹, 高昆仑², 赵婷², 陈江琦², 杨新宇¹, 杨树森¹

¹ 西安交通大学，陕西西安 710049
² 全球能源互联网研究院有限公司，北京 102209

修回日期:2021-01-26 出版日期:2021-03-30 发布日期:2021-03-01
作者简介:韩青（1994- ），女，西安交通大学计算机学院博士生，主要研究方向为边缘计算、边云协同智能系统与算法
高昆仑（1972- ），男，全球能源互联网研究院有限公司教授级高级工程师、博士生导师，主要研究方向为电力大数据与人工智能、网络安全
赵婷（1981- ），女，全球能源互联网研究院有限公司教授级高级工程师，主要研究方向为电力大数据与人工智能、网络安全
陈江琦（1991- ），男，全球能源互联网研究院有限公司工程师，主要研究方向为电力大数据与人工智能
杨新宇（1974- ），男，博士，西安交通大学教授，主要研究方向为边缘计算、人工智能、计算机网络与安全
杨树森（1984- ），男，博士，西安交通大学教授，主要研究方向为分布式网络（5G、边云协同网络）和数据科学（大数据、分布式机器学习、联邦学习）等
基金资助:
国家重点研发计划(2017YFB1010004);国家自然科学基金资助项目(61772410);国家自然科学基金资助项目(61802298);国家自然科学基金资助项目(U1811461);国家自然科学基金资助项目(11690011);中央高校基本科研业务费资助项目(xjj2018237);中国博士后科学基金资助项目(2020T130513);中国博士后科学基金资助项目(2019M663726);中国博士后科学基金资助项目(2017M623177)

Application of edge-cloud collaborative intelligence technologies in power grids

Qing HAN¹, Kunlun GAO², Ting ZHAO², Jiangqi CHEN², Xinyu YANG¹, Shusen YANG¹

¹ Xi’an Jiaotong University, Xi’an 710049, China
² Global Energy Interconnection Research Institute Co., Ltd., Beijing 102209, China

Revised:2021-01-26 Online:2021-03-30 Published:2021-03-01
Supported by:
The National Key R＆D Program of China(2017YFB1010004);The National Natural Science Foundation of China(61772410);The National Natural Science Foundation of China(61802298);The National Natural Science Foundation of China(U1811461);The National Natural Science Foundation of China(11690011);The Fundamental Research Funds for the Central Universities(xjj2018237);The China Postdoctoral Science Foundation(2020T130513);The China Postdoctoral Science Foundation(2019M663726);The China Postdoctoral Science Foundation(2017M623177)

摘要/Abstract

摘要：

随着电力物联网规模的不断扩大和部署在电力系统各环节的设备数量的快速增加，海量边缘设备所产生的数据呈指数级爆炸增长。海量边缘数据的高效、快速和安全处理与分析给传统的云计算智能技术带来极大挑战，而边云协同智能技术因节省带宽、减少时延、保护数据隐私等优点具有深度助力电力领域发展的巨大潜力。首先，对边云协同智能的概念和研究现状进行了介绍，阐述了边云协同智能的特征和优势，并对其赋能电力领域进行了适用性探讨。然后，结合电力系统的建设需求，讨论了面向电力场景的边云协同智能关键技术，接着针对电力领域的两个典型场景，分别给出了基于边云协同智能技术的解决方案，并搭建仿真实验进行效果验证。最后，对全文进行了总结并对下一步的研究方向进行了简要的展望。

关键词: 智能电网, 电力物联网, 人工智能, 边缘计算, 边云协同智能

Abstract:

With the continuous development of the Internet of things on electricity (IoTE) and large-scale deployment of intelligent edge devices, an explosively increasing amount of data are being generated at the network edge.The efficient, fast and secure processing and analysis of the massive edge located data brings great challenges for the traditional cloud computing-based intelligence technologies.Instead, edge-cloud collaborative intelligence (ECCI) technologies can significantly outperform the cloud computing-based intelligence in terms of the network bandwidth saving, delay reduction and privacy protection, and therefore have shown a great potential in boosting the development of power grids.To investigate the application of ECCI in power grids, the concept and research progress of ECCI were firstly introduced.The characteristics and advantages of ECCI were summarized and its applicability in the power grids were discussed.Secondly, the key technologies of ECCI applications for power grids were discussed and the solutions based on ECCI technologies for two typical scenes were proposed respectively.Finally, a brief discussion of future work was given.

Key words: smart grid, Internet of things on electricity, artificial intelligence, edge computing, edge-cloud collaborative intelligence

中图分类号:

TM862

韩青, 高昆仑, 赵婷, 陈江琦, 杨新宇, 杨树森. 边云协同智能技术在电力领域的应用[J]. 物联网学报, 2021, 5(1): 62-71.

Qing HAN, Kunlun GAO, Ting ZHAO, Jiangqi CHEN, Xinyu YANG, Shusen YANG. Application of edge-cloud collaborative intelligence technologies in power grids[J]. Chinese Journal on Internet of Things, 2021, 5(1): 62-71.

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电力发展的需求	边云协同智能的优势
海量泛在接入	低带宽成本
数据价值待有效挖掘	小样本AI算法
应用的敏捷响应	高实时性
打破数据“孤岛”和业务“壁垒”	数据隐私安全

方案	带宽/MB	响应时间/s	准确率
边云协同智能算法	63.21	3.73	89.2%
云智能算法	303.83	82.04	97.6%
边智能算法	0	14.81	68.7%

边云协同智能技术在电力领域的应用

Application of edge-cloud collaborative intelligence technologies in power grids

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