A system architecture that combined 5G power virtual private network and digital twins was designed in this paper, and the construction method of synchronization during the digital twins of terminals was considered. Then, a hierarchical multi-agent reinforcement learning algorithm was proposed to determine the allocation of resources to power user terminals and the placement of digital twins. The upper layer achieved the allocation of sliced communication resources through deep Q network, and the lower level achieved the placement of digital twins in power user terminals through multi-agent deep reinforcement learning. The experimental results show that the proposed hierarchical multi-agent algorithm can achieve better system benefits when the synchronization strength of the digital twin of the power user terminal is reached.