5G电力虚拟专网和数字孪生相结合的系统架构和构建

设计了一种5G电力虚拟专网和数字孪生相结合的系统架构,并考虑了终端数字孪生时同步的构建方法,提出了一种分层多智能强化学习算法。该算法决定分配给电力用户终端的资源和数字孪生体的放置,上层通过深度Q网络实现切片通信资源的分配,下层通过多智能体深度强化学习实现电力用户终端的数字孪生体放置。实验结果表明,所提出的分层多智能体算法在电力用户终端数字孪生体的同步强度上能获得较好的系统收益。

Research on the System Architecture and Construction Method of Combining 5G Power Virtual Private Network and Digital Twin

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 Qnetwork, 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.