Research on Computing and Network Convergence Resource Allocation Based on Stackelberg Game for New Power System

With the development of new power system and computing and network convergence technology, the number of intelligent power communication devices is increasing exponentially. On the one hand, the upgrading of microprocessor technology has provided the possibility for devices to handle high energy consumption and fast response applications. On the other hand, the maturity of Device to Device (D2D) technology provides computing and network convergence support for the implementation of short distance, low latency, and low energy data transmission. This article studies on adjusting the price of computing resources for service-oriented users in new power system, while using KM algorithm to match SU and RU, to achieve effective computing resource allocation and improve user experience. Considering that idle devices require energy consumption to provide computing services for RU devices, in order to ensure the efficiency of SU, it is necessary to charge for computing resources and optimize the price of computing resources based on Stackelberg game to improve the efficiency of SU. And we optimize user unloading direction based on KM algorithm at a given price. Simulations show that the proposed strategy has high efficiency of computing resource allocation for new power system.