Active Power Distribution Hierarchical Energy Optimal Management of IoT Smart Power System

With the development of modern power systems, the research on energy optimization management at the distribution level has also become a hot topic in recent years. In the microgrid system, two safety indicators, load power shortage rate and energy waste rate, are considered and incorporated into the model as constraints. The proposed energy optimization management method is verified by Python programming. To verify the advantages of the particle swarm optimization algorithm used in this paper in energy optimization management, the method in this paper is compared with the traditional real-time one-step optimization method. In this paper, the particle swarm algorithm is used, and the average node voltage deviation is about 0.01pu. The overall voltage evaluation index obtained is 25.86% lower than that of one-step optimization, and the overall optimization effect of reactive power voltage is better.