The penetration of renewable energy resources for distribution networks can significantly impact the security of power supply systems. To improve the penetration efficiency, a hierarchical optimization planning for a distributed generation (DG) network using the improved sand cat swarm optimization (ISCSO) is proposed to determine the optimal location and capacity of DG into the distribution network. Firstly, the sensor is used to collect data, and the ISCSO algorithm is used to construct a complex nonlinear DG planning problem, thus reducing the impact of DG uncertainty. Second, a DG hierarchical planning model is established to select the optimal location and capacity of DG access to the distribution network. Finally, in the classical test system, the effectiveness of the proposed model is verified by setting up multiple cases. The test results confirm that the total annual cost and power loss of the DG system can be reduced by 13.1 and 40.5%, respectively.