This article focuses on the problem of voltage drop in low-voltage distribution systems and proposes a dynamic monitoring and edge intelligent compensation strategy. During the operation of the distribution network, the problem of line loss is becoming increasingly prominent due to factors such as equipment aging and load fluctuations, which seriously affects the quality of power supply and system economy. To improve the safety and energy efficiency of the distribution network, this article designs a line loss automation management system based on edge intelligent sensing technology. The system achieves real-time collection of electrical energy parameters through the deployment of intelligent sensors, and combines big data analysis and deep learning (DL) algorithms to achieve accurate identification of line losses, abnormal warning, and optimized control functions. Specifically, the system introduces a voltage control strategy based on the Deep Deterministic Policy Gradient (DDPG) algorithm, which enhances the system's adaptive regulation capability. The results show that compared with traditional methods, our system has stronger robustness and higher precision in complex environments, can effectively reduce line losses, ensure voltage stability, and provide strong support for the intelligent and refined management of low-voltage distribution networks (LVN).
Jianyu Luo (Sun,) studied this question.