Semimonthly

ISSN 1000-1026

CN 32-1180/TP

+Advanced Search 中文版
Analysis of Key Issues and Prospect for Digital Transformation of Distribution Networks Based on Edge Computing
Author:
Affiliation:

1.Novel Electric Power System (Beijing) Research Institute of China Southern Power Grid, Beijing 102209,China;2.Key Laboratory of the Ministry of Education on Smart Power Grid (Tianjin University), Tianjin 300072, China

Abstract:

Distribution network have become one of the most critical and vigorous sectors in developing new power systems. Digital transformation is a widely recognized way to solve the complex operation and control problems of distribution networks. Edge computing is an effective means to utilize the massive data resources and physical resources in digital distribution networks. It also provides a comprehensive platform for implementing operation functions on the edge side, which promotes the development and transformation of the operation architecture for the distribution network. This paper focuses on the digital transformation issues of distribution networks driven by the edge computing technology. The essential technical requirements for edge computing devices in the distribution network are presented. The technical positioning of edge computing and its support to the technical architecture of digital distribution networks are analyzed. Especially aiming at the operation issues of digital distribution networks, starting from three typical features of clustering, distribution, and flexible definition, key issues and technical research directions are summarized and discussed, including typical modes such as edge-side cluster local control, edge-edge cooperative control and cloud-edge cooperative operation.

Keywords:

Foundation:

This work is supported by National Key R&D Program of China (No. 2020YFB0906000, No. 2020YFB0906002).

Get Citation
[1]LI Peng, XI Wei, LI Peng, et al. Analysis of Key Issues and Prospect for Digital Transformation of Distribution Networks Based on Edge Computing[J]. Automation of Electric Power Systems,2024,48(6):29-41. DOI:10.7500/AEPS20221129005
Copy
Share
History
  • Received:November 29,2022
  • Revised:September 22,2023
  • Adopted:September 25,2023
  • Online: March 15,2024
  • Published: