Fault Diagnosis and Recovery of Transmission Networks Using Improved Ant Colony Optimization Algorithm (ACO)

In response to the problems of low diagnostic accuracy and low recovery efficiency in current research on fault diagnosis and recovery in transmission networks, this paper used an improved ant colony optimization algorithm to study it and improve the accuracy of fault diagnosis and recovery efficiency. It updated the pheromones of traditional ant algorithms and calculated the transition probability to find the optimal solution. The parameters of transmission line components are calculated and various parts of the system topology to quickly find the optimal recovery path and improve recovery efficiency are analyzed. Through experiments, it was found that the fault diagnosis accuracy of the method studied in this article was above $\mathbf{9 2. 4 7 \%}$. After 10 experiments, the average fault diagnosis accuracy was $\mathbf{9 4. 2 9 \%}$. The method studied in this article has achieved significant results in fault diagnosis and recovery of transmission networks, effectively improving the reliability and stability of the power grid.