Research On Air Conditioning Energy Saving System Based On Person Flow Perception In Subway Station

With the development of economy and the progress of society,the trend of large-scale urbanization in China is becoming more and more obvious.This phenomenon of large-scale urbanization migration not only brings considerable economic benefits and urban vitality,but also brings certain pressure to urban traffic.Therefore,in order to alleviate the current situation of urban public traffic congestion,China’s major cities will take the subway as an important means of transportation.However,in the process of subway operation,the energy consumption of air conditioning system in subway station accounts for 40% ～ 50% of the total energy consumption,which greatly affects the economy of subway operation.Therefore,it is urgent and necessary to study the energy saving measures of air conditioning system in subway station.According to the survey,most of the subway station air-conditioning systems in China adopt all-weather constant temperature control in the station,and do not use advanced energy-saving systems and devices,and do not fully consider the impact of heat load caused by irregular changes in the number of passengers in the subway station,resulting in low thermal comfort in the station and high energy consumption of the air-conditioning system.In view of the above problems,the main research contents of this paper are as follows:By consulting the relevant information,we can understand the operation mode of the air conditioning system in the subway station,the influencing factors of heat load and the theory of human comfort,and investigate the typical daily passenger flow changes of a subway station in summer.The research results show that there are obvious peak and valley periods in the subway station,and with the real-time change of the number of passengers,the heat load in the station also changes.By getting familiar with the design structure of the subway station,using Solid Works three-dimensional modeling software to establish the three-dimensional model of the subway platform and the human body,using the geometry subroutine of ANSYS software to establish the air flow model in the station,using mesh subroutine to divide the grid,and using fluent subroutine to set the conditions such as the wind speed and temperature inside the fluid,the number of 10% and 90% human body in the subway station is finally compared and analyzed The influence of load on station environment.The numerical simulation shows that when the population in the station changes,if the air control is still maintained at the current level,the control is not timely and effective,and the energy can not be fully utilized.Therefore,it is necessary to further set up and optimize the air conditioning and ventilation system to cope with the change of heat load caused by different passenger flow.By understanding the principle of deep learning,a pedestrian flow recognition system is built based on convolutional neural network model,and human body recognition is carried out with Ubuntu operating system and Tensor Flow machine learning framework.Finally,the passenger flow data of the subway station on a typical working day in summer is obtained.Finally,this paper designs a new intelligent air conditioning control system based on the main energy consumption units and operation of air conditioning in subway station.The system can adjust and control the fan,frequency converter and refrigeration unit timely according to the change of the passenger flow in the station,so as to achieve the appropriate station environment.The theoretical calculation shows that the new regulating system can save about 13% energy.In general,with the popularity of intelligent life,technology and people are more and more closely linked.Providing passengers with the most suitable subway ecological environment,saving resources and protecting the environment is an important guarantee for people’s urban transportation and life.