Research on Dynamic Reconstruction Technology of Low-Voltage Transparent Substation Based on Digital Twin and Edge Computing

The role of low-voltage transparent substations in the digital power grid is becoming increasingly significant. However, traditional methods still face challenges, such as slow response times and high costs. To address the specific needs of the Zhongshan region in Guangdong, this paper proposes a dynamic reconstruction method for low-voltage substations by integrating Digital Twin and Edge Computing technologies. The study introduces a “Perception-Decision-Reconstruction” closed-loop control framework to optimize the operation of these substations. Through the integration of multi-source data, including voltage, current, and topology information, edge computing is utilized for load forecasting and fault management. Additionally, three-dimensional modeling and dynamic simulation are employed to enhance the coordination between the primary distribution system and microgrids. In terms of algorithmic design, this study leverages convex optimization and game theory to enhance decision-making efficiency and ensure optimal resource allocation. The effectiveness of the proposed methodology is validated through MATLAB simulations. In practical implementation, the Zhongshan Power Supply Bureau’s pilot stations achieved a 100% reduction in tripping incidents, an 80% improvement in response speed compared to traditional Supervisory Control and Data Acquisition (SCADA) systems, and a 30% reduction in investment costs. Experimental results indicate that this approach significantly enhances power supply reliability and effectively reduces operation and maintenance costs, providing a practical solution for the intelligent transformation of low-voltage transparent substations.