In order to solve the problem that high structural redundancy can meet the low accuracy requirements, resulting in a large increase in computing time, the method of intelligent distribution network state estimation based on deep learning is proposed. The structure and input-output properties of single-layer linear neural networks and the IEEE 30 node reliability test system were simulated using the Matlab neural network toolbox. The simulation results show that the single layer linear neural network and the time required is shorter than the bp neural network at the same accuracy, and with the improvement of accuracy, the advantage of computing speed increases significantly. At MSE 0. 4, the single layer linear neural network is 3,814.408s faster than the bp neural network. Single-layer linear neural network is simpler and faster than bp neural network, which can greatly improve the computing speed, and is more suitable for VSSE calculation.