Research on Intelligent Scheduling Algorithm of Mobile Energy Storage Equipment for User-Side Services

A kind of intelligent scheduling algorithm based on deep reinforcement learning is presented, which is to improve the efficiency and service quality of the user. This algorithm combines the demand forecast with the dynamic optimization of the energy storage device. It can make real-time adjustment of charging and discharging policy for energy storage devices, and maximize the overall efficiency of the system. The experimental results show that the proposed algorithm outperforms the conventional one in power distribution efficiency, response time and user satisfaction. In particular, in terms of optimizing the charging and discharging strategy, 15 rounds later. The proposed algorithm can increase the efficiency of the system by 12.5%, and reduce the requirement response time by 20%. The proposed algorithm is robust in all kinds of load conditions, and it is able to deal with the fluctuation of system load and the variation of customer demand. Experiments show that the intelligent scheduling algorithm is feasible and superior in practice.