Research on Optimization Algorithm Design Model of Mobile Energy Storage Equipment for User-Side Services

This paper proposes a new method of optimizing mobile energy storage equipment for customer service, which is based on the optimization of power scheduling and user load. An optimal scheduling model is proposed based on demand response and equipment state, and a combination of heuristic and deep learning is put forward. The results show that the algorithm is effective under several typical load situations. Compared with the traditional method, the power demand response of the algorithm is 15% higher, and the energy waste is reduced by 18%. Compared with the current model, the optimized energy storage system scheduling algorithm can increase the stability and reliability by about 12%. Moreover, the computation time of this algorithm is 20% less than that of the conventional algorithm, and it is highly efficient. Experiments show that the optimized algorithm is of great practical value, and it can offer efficient scheduling strategy for the users, and it can also provide powerful support for the load management.