Integration of embedded systems and artificial intelligence in electrical automation for smart grid management

Abstract With the continuous progress of social civilization, electricity plays an indispensable role in human life. China is a vast country with wide grid coverage and frequent natural disasters, which cause certain losses to the national economy. Therefore, this paper fully considers the role of meteorological information in the emergency decision-making of smart grid disaster prevention, uses the Dijkstra algorithm to clarify the best path, and integrates many factors such as traffic coefficient, road level, road congestion and road quality to establish the optimal path model, which can effectively improve the management level, reduce the smart grid loss by more than 48 %, protect the residents and industrial electricity consumption, and provide safe operation of the smart grid. Powerful guarantee.