Edge computing and big data analysis integration framework in smart grid edge gateway

This study aims to enhance the data processing efficiency, real-time performance, and system reliability of smart grids by integrating edge computing and big data analysis in smart grid edge gateways. This study shows how advanced technologies like edge devices, edge computing nodes, big data analytics modules, and control systems can be utilized in a real grid setting to enhance operational efficiency and grid prediction ability through a comprehensive architecture design and implementation. In the research, we concentrated on data real-time processing, transmission mechanism, and system architecture design, and we validated the framework's efficiency with real cases. Studies indicate that the integration of edge computing and big data analysis in an organic manner can enhance the data processing abilities of the power grid, decrease delays, and offer robust backing for optimal power grid management. This framework is capable of satisfying the requirements of current smart grids, as well as possessing strong scalability and adaptability, providing a robust groundwork for the advancement of future smart grids.