Research on Big Data Database System in Intelligent Dispatching of Mobile Energy Storage Equipment

This paper proposes an intelligent dispatching method based on big data analysis, which realizes the management, storage and dispatch optimization of energy storage equipment data by designing an efficient database system. In view of the low dispatching efficiency and slow response speed of energy storage equipment in the current power system, the researchers developed an innovative DRL algorithm. The algorithm uses real-time data and combines the characteristics of dynamic changes in the power system to achieve adaptive dispatching optimization capabilities, greatly improving dispatching efficiency and system performance. Specifically, this method improves dispatching efficiency by 20% and shortens response time by 15% compared with traditional methods, while significantly enhancing system stability by 10%. In addition, this paper analyzes the performance of this method under different load conditions through simulation and makes a comprehensive comparison with traditional dispatching methods. The results show that the proposed dispatching method has significant advantages in dealing with large-scale energy storage equipment management tasks, and can provide real-time optimized dispatching solutions under complex and changeable power grid load environments. Through an intelligent data processing framework, this method significantly improves the operating efficiency of the power system, especially in the face of dynamic power demand and diversified equipment characteristics. It shows excellent adaptability.