A New Energy Grid-Connected UAV Auxiliary Network Average Information Age Minimization Strategy

In new energy grid-connected systems, real-time monitoring and rapid response are essential to optimize operational decisions and improve system efficiency. In view of the real-time monitoring requirements of new energy facilities, this paper proposes a strategy to minimize the average information age of UAV auxiliary network connected to the new energy grid, which effectively improves the real-time update ability of UAV by jointly optimizing the flight trajectory, wireless charging strategy and energy supply scheme of UAV. Firstly, a minimization model focusing on information timeliness is established, and the task scheduling problem of UAV is modeled as a Markov decision-making process to cope with the uncertainty in the process of wireless energy supply and data acquisition. Secondly, this paper uses a DQN-based algorithm to optimize the operation strategy of the UAV, so that it can effectively reduce the average information age while maintaining energy efficiency. The simulation results show that compared with the traditional method, the proposed strategy reduces the average information age of the system by 12.7% to 70.9%, and significantly enhances the data freshness and response speed of the new energy grid-connected system.