Event-Driven Edge Agent Framework for Distributed Control in Distribution Networks

Xianglong Zhang (), Ying Liu, Songlin Gu, Yuzhou Tian and Yifan Gao
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Xianglong Zhang: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China
Ying Liu: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China
Songlin Gu: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China
Yuzhou Tian: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China
Yifan Gao: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China

Energies, 2025, vol. 18, issue 11, 1-23

Abstract: With the large-scale integration of heterogeneous energy resources and the increasing demand for flexible control, centralized control is facing challenges in terms of operational efficiency and system responsiveness when handling high-precision regulation tasks. To address this issue, this paper proposes an event-driven edge agent framework for distributed control in power distribution networks. First, based on the diverse requirements of distributed control in distribution networks, an edge agent architecture is constructed with modular components such as configuration management at its core. Second, considering the hybrid system characteristics of distribution networks, a control configuration technique based on activity-on-edge is designed, which decouples and discretizes continuous control processes through event-driven mechanisms. Furthermore, an edge-oriented automatic differentiation solver and a lightweight web application framework are developed to address the challenges of real-time optimization under resource-constrained environments. Finally, a semi-physical simulation is conducted using station-level economic dispatch as a case study to verify the effectiveness of the proposed technology. The results demonstrate that, compared to centralized control, the designed distributed agent maintains optimization accuracy while reducing event-triggering frequency by 40% and improving communication response speed by 70%, showing strong performance in operational efficiency at the edge.

Keywords: edge agent; distribution network; control configuration; distributed control; event-driven; automatic differentiation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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