The increasing integration of intermittent renewable energy sources into distribution networks has exerted significant pressure on the frequency regulation of power systems. Meanwhile, integrating small-capacity battery energy storage systems into distribution network is a growing trend in the construction of virtual power plants (VPPs), which offer great potential advantages in improving the system frequency regulation capabilities. However, the process of power dispatch for VPPs may be hindered by imperfections in the communication network, which affects their frequency control performance. Simultaneously, the economic benefits associated with their frequency control services are often overlooked. As such, we propose a co-design method of power dispatch with dynamic power regulation and communication transmission optimization for frequency control in VPPs. First, a joint design scheme of power dispatch and routing optimization under cloud-edge collaborations is proposed. This scheme encompasses a power dispatch method considering the influences of communication network and a routing optimization policy based on graph convolutional neural networks, both of which are designed to ensure the accurate and real-time frequency control service. Further, we propose a dynamic power regulation strategy under edge-edge collaborations. Specifically, according to the established correction control objective, an adaptive distributed auction algorithm (ADAA) based dynamic power regulation control method is designed to determine the optimal regulation power of VPPs, thereby improving the economic benefits of frequency control service. Finally, the simulation results validate the feasibility and superiority of the proposed co-design method for frequency control.