Non-intrusive load decomposition technology is an important part of the smart grid technology system. As the existing decomposition methods perform low identification accuracy for similar power or low power load, this paper proposes a non-intrusive load decomposition algorithm based on time partition and V-shaped particle swarm optimization. Firstly, the clustering analysis of load power characteristics is conducted through the density-based spatial clustering of applications with noise to obtain the power feature template of the load, and then, the typical working time of load is solved to obtain the time characteristic template of the load. Moreover, considering power and time characteristics, the objective function of the V-shaped particle swarm optimization algorithm is constructed to achieve load decomposition. Finally, the simulation is implemented on the AMPds2 public data set and compared with the hidden Markov model to verify the effectiveness of the proposed method in this paper.