Construction of Distribution Network Fault Detection Model Based on Artificial Intelligence Algorithm

In recent years, with the continuous development of power grid system, China has built the largest and most complex power grid system in the world. How to ensure the stability of power supply and find and solve power grid faults in time has become the main problem to be solved urgently. In this paper, a new fault detection model of distribution network is constructed based on AI (Artificial intelligence) algorithm in order to diagnose power network faults effectively and timely. Based on the principle of system energy conservation, the model takes the arc suppression coil as a branch to participate in the analysis of fault lines, avoiding the limitation of only using transient energy of fault branches and non-fault branches to select lines, and improving the accuracy of line selection. The simulation results show that the error of this algorithm is reduced by about 10.12% compared with the traditional method. The algorithm avoids the generation of infeasible solutions, is easy to be combined with various intelligent algorithms, and improves the efficiency of optimization. Compared with the traditional NN algorithm, the fault detection model of distribution network has obvious advantages in performance, which can give early warning of faults in time and greatly improve the efficiency of fault diagnosis of power network. Thus, the reliability and economy of the distribution network are further improved.