Establishment and Analysis of Energy Consumption Prediction Model of Air Conditioning System in Subway Station

The energy consumption of subways in the operation process is relatively large. With the continuous development and expansion of China's rail construction, the problem of energy saving has become more and more prominent. The air-conditioning system is a large energy-saving potential in the process of subway operation. It is necessary to optimize the design of the air-conditioning system to find energy-saving and emission reduction measures for subway operation. Therefore, it is a very important research topic to reduce the energy consumption of the system by optimizing the ventilation and air-conditioning design of the subway. In this paper, according to the proportion of energy consumption, the energy consumption prediction model of BP neural network with step of 10 minutes is firstly established, and then the seasonal air conditioning energy consumption prediction model is established. The research results of BP neural network model in this paper provide a reference for the energy saving control of subway stations and provide research mothod for other central air conditioning systems.