The Research Of Operational Control Of The Ventilation And Air Conditioning System Based On Measured Data From Hongtudi Station

With the rapid development of subway construction,the improvement of subway operation capacity is very important.The environmental control system has created a suitable operating environment for the subway.At the same time,long-term high-energy operation has become the focus of subway operation,so the control performance of the environmental control system directly determines the pros and cons of the subway environment and the system energy consumption.In order to realize the energy-saving operation target of the subway station,this paper combines the measured data to carry out in-depth study on the dynamic load change and optimal operation control mode of the ventilation and air-conditioning system of the station public area,and proposes an energy-saving control strategy that is compatible with the engineering characteristics.In this paper,a one-year hot and humid environment of Chongqing Rail Transit Line 6 Hongtudi Station was tested and analyzed in detail.It was concluded that in the summer,due to the long fresh air shaft,the fresh air temperature decreased by 3.9°C,the relative humidity increased by 14.4% on average,and the station hall and platform are 4.1°C and 3°C lower than the design value respectively with greater energy saving potential.In addition,the temperature of the long inlet and outlet passages meets the design requirements,although there is no air conditioner at the initial stage of operation.The monitoring results of the annual temperature change in the track area indicate that the temperature of the track area in the initial stage of operation is not exceeded.For Chongqing Rail Transit Line 6 Hongtudi Station,the minimum fresh air volume of the public area should be 10% of the air supply in the air-conditioning season by calculation and comparison.Moreover,due to the station hall equipment load accounted for the largest proportion,the daily variation of the passenger flow load has a greater impact on the platform.Besides,according to the characteristics of the station,the selection of fresh air parameters at the bottom of the fresh air shaft can reduce the fresh air design load by 47.6%,the air design parameters of the track area are turn to the measured parameters,and the screen door load is reduced by 27.1%.In order to realize the energy-saving operation of the subway station,this paper proposes an optimized ventilation mode for the single-fan operation of the dual-fan configuration for the existing station.After calculating the total number of hours of 78.7% in Chongqing in the whole year,the single-fan operation can be realized,and the energy-saving rate reached 39.1%.By comparing the end control logic,it was concluded that the control effect of simultaneous adjustment of air volume and water volume is better and the energy saving rate of the conveying equipment can reach 31.7%.Finally,the BP neural network based on genetic algorithm optimization is used to predict the end-flow of the fan and pump,and the system simulation platform is used to verify the neural network feedforward control.The results show that the neural network feedforward predicts the output flow with a relative error of less than 5%,and the end device adjustment runs smoothly.So the control mode is reasonable.After online learning optimization,the training accuracy of the neural network is improved,and the predicted output error is ±2%.