Simulation of distribution network planning model based on mobile IoT and deep learning

Abstract

Distribution network construction is an important work in urban planning and construction, which can provide power supply guarantee for the normal growth of production and living activities, and is the foundation for promoting the rapid and stable growth of urban economy. However, the planning level of the original urban power grid is low, the laying of underground pipelines is not reasonable enough, the quality of power grid equipment can not be guaranteed, and it is prone to operational failures, which leads to great potential safety hazards. As the infrastructure of urban power supply, the power grid's equipment level determines the power supply capacity and affects the security of urban power supply. This paper explores the possible problems in the construction of smart grid, and proposes a power grid planning model based on mobile Internet of Things (IoT) and deep learning, in order to realize the scientific planning and operation of smart power grid as soon as possible. The simulation results show that with the increase of the quantity of experiments, the accuracy of this algorithm is stable at about 94%, and the real-time wavelength tends to be stable, which is 18.64% higher than the traditional algorithm on average. Using this model to transform and brand-new plan the power grid system, research and popularize the automation technology of distribution system, and build a smart grid, it is expected that the smart grid can be more effectively planned and operated.