Optimization of Power Distribution Network Dispatching Auxiliary Decision-Making and Intelligent Ticketing System Based on PPO Algorithm

The existing intelligent ticketing system has problems such as insufficient automation, weak dynamic adaptability, and limited ability to cope with complex fault scenarios. Based on the PPO algorithm, this paper designs and implements an improved intelligent ticketing system. This paper introduces a graph neural network (GNN) to model the power grid topology, so that the system can dynamically generate operation tickets based on the multi-dimensional state of the power grid. Combined with the exploratory and adaptive nature of the PPO algorithm, it autonomously learns and optimizes the process of generating operation tickets under a changing dispatching environment to reduce the risk of misoperation. In the load experiment, the dispatch success rate of the PPO algorithm under low and medium loads reached 96.5% and 95.3% respectively, maintaining a fast response; under high load, the success rate dropped slightly to 91.8%, but it can still meet the real-time requirements. The fault experiment shows that the success rate of PPO is 98.2% in single-point failures and slightly decreased to 92.5% in multi-point failures, but it has strong robustness. The system achieves a balance between efficiency and safety in complex dispatching tasks.