Research on Transparent Grid Dynamic Surveillance and Fault Early Warning System for High-Density Distributed Power Supply Access Areas Incorporating Artificial Intelligence Technology
Publicado en línea: 26 mar 2025
Recibido: 02 nov 2024
Aceptado: 23 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0810
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© 2025 Zhongqiang Zhou et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The strategic energy transition has driven the construction of a new type of power system, and the digital transformation of distribution grids has become particularly urgent. The study focuses on building a transparent grid dynamic monitoring and fault warning system for high-density distributed power access areas. The system integrates artificial intelligence technology and designs key functional modules such as real-time data monitoring, intelligent communication, alarm information, and dispatch data. Multiple fault information is obtained from the grid, and the accuracy of the system’s fault warning and localization is measured. Through practical application, the system is further evaluated for its practical value in grid dynamic monitoring and fault warning. The system’s prediction error for faults in high-density distributed power supply access areas is minimal, and it can acquire fault information with accuracy, boasting a fault localization accuracy rate greater than 95%. In terms of application practice, the system can monitor the current and voltage data of the grid system in real time. For example, the system captures a voltage transient drop with a duration of 5 cycles and a drop of more than 45%. In this paper, the power grid dynamic monitoring and fault early warning system designed using artificial intelligence technology has good application performance.
