Edge intelligence for smart grid: a survey on application potentials

• Main Authors: Gooi, Hoay Beng, Wang, Tianjing, Tang, Yong
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Article
• 語言: English
• 出版: 2024
• 主題: Engineering::Electrical and electronic engineering; Artificial Intelligence; Edge Computing
• 在線閱讀: https://hdl.handle.net/10356/173134

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.