Edge Intelligence for Smart Grid: A Survey on Application Potentials

Hoay Beng Gooi; Tianjing Wang; Yong Tang

doi:10.17775/CSEEJPES.2022.02210

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Edge Intelligence for Smart Grid: A Survey on Application Potentials

Regular Papers | 更新时间：2026-10-15

- Edge Intelligence for Smart Grid: A Survey on Application Potentials
- CSEE Journal of Power and Energy Systems Vol. 9, Issue 5, Pages: 1623-1640(2023)
- 作者机构：
  
  1. Nanyang Technological University,Singapore,Singapore
  2. China Electric Power Research Institute,Beijing,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2022.02210
  CLC：
- Published：01 September 2023
- 稿件说明：
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Hoay Beng Gooi, Tianjing Wang, Yong Tang. Edge Intelligence for Smart Grid: A Survey on Application Potentials[J]. CSEE Journal of Power and Energy Systems, 2023, 9(5): 1623-1640.
DOI：

Hoay Beng Gooi, Tianjing Wang, Yong Tang. Edge Intelligence for Smart Grid: A Survey on Application Potentials[J]. CSEE Journal of Power and Energy Systems, 2023, 9(5): 1623-1640. DOI： 10.17775/CSEEJPES.2022.02210.

摘要

Abstract

With the booming of artificial intelligence (AI)

Internet of Things (IoT)

and high-speed communication technology

integrating these technologies to innovate the smart grid (SG) further is future development direction of the power grid. Driven by this trend

billions of devices in the SG are connected to the Internet and generate a large amount of data at network edge. To reduce pressure of cloud computing and overcome defects of centralized learning

emergence of edge computing (EC) makes the computing task transfer from the network center to the network edge. When further exploring the relationship between EC and AI

edge intelligence (EI) has become one of the research hotspots. Advantages of EI in flexibly utilizing EC resources and improving AI model learning efficiency make its application in SG a good prospect. However

since only a few existing studies have applied EI to SG

this paper focuses on the application potential of EI in SG. First

the concepts

characteristics

frameworks

and key technologies of EI are investigated. Then

a comprehensive review of AI and EC applications in SG is presented. Furthermore

application potentials for EI in SG are explored

and four application scenarios of EI for SG are proposed. Finally

challenges and future directions for EI in SG are discussed. This application survey of EI on SG is carried out before EI enters the large-scale commercial stage to provide references and guidelines for developing future EI frameworks in the SG paradigm.

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references

9. I. Stoica, D. Song, R. A. Popa, D. Patterson, M. W. Mahoney, R. Katz, A. D. Joseph, M. Jordan, J. M. Hellerstein, J. E. Gonzalez, K. Goldberg, A. Ghodsi, D. Culler, and P. Abbeel. ( 2017, Dec. ). A Berkeley view of systems challenges for AI . [Online ] . Available: https://arxiv.org/abs/1712.05855

10. Gartner. ( 2019, Nov. ). 5 Trends emerge in the Gartner hype cycle for emerging technologies . [Online ] . Available: https://www.gartner.com/smarterwithgartner/5-trends-emerge-in-gartner-hype-cycle-for-emerging-technologies-2018/

25. IEC white paper edge intelligence . [Online ] . Available: https://www.iec.ch/system/files/2019-–09/content/media/files/iec_wp_edge_intelligence_en_lr.pdf

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