Communication Network Resource Allocation for Electric Vehicle Aggregation and Control

In the context of large-scale clean energy access to the grid, the aggregated regulation of electric vehicles is an important way to ensure the balance of electricity supply and demand. The aggregation process of electric vehicles generates a large number of information transmission services, and its strict real-time and accurate interaction requirements pose a severe challenge to the existing network communication performance. Therefore, this paper proposes a communication network architecture of "central cloud platform-edge server-EV user" for information exchange in the process of EV aggregation and regulation, focuses on analyzing the differences in business processing functions and information exchange requirements at each layer, and establishes utility function models for the timeliness and accuracy of information transmission at each layer in the process of demand response. A channel and power resource allocation model is constructed based on the utility function. Channel and power allocation are realized using the dung beetle optimization algorithm, bilateral matching, and improved water-filling algorithm. To expand the randomness of population iteration, a sinusoidal strategy is introduced into the dung beetle optimization algorithm, combined with bilateral matching and an improved water injection algorithm, enabling the model to quickly converge to the maximum utility value and realize the allocation of channel and power resources during the vehicle network interaction process. The simulation results indicate that the algorithm is capable of effectively improving the overall information transmission efficiency of transmission services in the hierarchical aggregation control scenario for electric vehicles.