Abstract: This article proposes a comprehensive optimization method based on graph theory, fuzzy comprehensive evaluation, deep reinforcement learning, and digital twin technology to meet the flexible configuration requirements of smart grid for substation main wiring. By studying the modeling of the main wiring topology, equipment status evaluation, and wiring optimization, a flexible configuration scheme that dynamically adapts to the needs of multiple scenarios has been achieved. The experimental results show that this method is superior to traditional solutions in terms of power supply reliability, power quality, and economy, significantly improving the flexibility and intelligence level of substation operation.