Dynamic Air-conditioning Load Forecasting And Energy-saving Regulation Analysis Of Metro Station

With the development of rail transit technology,people’s travel modes are gradually changing,and the subway has become an indispensable mode of transportation in modern cities.While the metro system is developing,its energy consumption cannot be underestimated.In order to improve the environment in the metro station,the ventilation and air-conditioning system of metro station was born.With the increasing demand for comfort,the energy consumption of ventilation and air-conditioning system of metro station accounts for an increasing proportion of the total energy consumption of the metro system.Therefore,the problem of reducing the energy consumption of ventilation and air-conditioning system of metro station has become more and more important.In order to make ventilation and air-conditioning system of metro station better meet people’s comfort needs,it is first necessary to analyze the environment in the metro station.This paper takes Shuanggang Station and Qingshanhu Avenue Station on Nanchang Metro Line1 as the research objects.First,the heat gain factors of the metro station are analyzed,and then the metro station enclosure structure model is established,and the finite difference method is applied to discrete the mathematical model of the enclosure structure and establish a discrete equation set of nodes of the enclosure structure.Then the model is solved through matlab programming,and the heat transfer of the enclosure structure of the two stations is analyzed.the results show that the transfer of the subway station enclosure has changed small,and basically tends to have a stable value.The main reason for the dynamic change of the cooling load of the air conditioning in the metro station is the time-to-time change of the flow of people.Therefore,it is necessary to analyze the dynamic change of the flow of people in the metro station.In order to establish the human flow forecasting model,this paper conducts in-depth research on the BP neural network forecasting algorithm.Taking into account the limitations of the BP neural network algorithm,genetic algorithm is used to optimize it.Considering the limitations of BP neural network algorithm,genetic algorithm is used to optimize it.Then,based on the historical data of human flow at Shuanggang Station and Qingshanhu Avenue Station,a comprehensive analysis was carried out,and a BP neural network prediction model optimized by genetic algorithm was established,and the analysis results show that the prediction error of the genetic algorithm optimized BP neural network model is reduced by about 10% than the traditional BP neural network model.After that,by analyzing the cooling load of various indoor heat sources and the cooling load of fresh air,the calculation model was obtained.Based on the forecasted human flow data,the cooling load of various indoor heat sources and the fresh air cooling load of Shuanggang Station and Qingshanhu Avenue Station were calculated respectively.The results show that due to the impact of the flow time-on-time change in the subway station,the cooling load of various indoor heat sources and the cooling load of fresh air are constantly fluctuating,and the difference of the cooling load in the peak and low grain is large,and the fluctuates cannot be ignored.In order to achieve the energy-saving goal of the air-conditioning system in the metro station,this paper analyzes the heat exchange process of the air system and the water system of the air conditioning system of metro station respectively,and then analyzes the variable air volume operation mode and the constant air volume operation mode,and establishes the energy consumption calculation model of the air-conditioning system in the metro station.Respectively simulating the energy consumption of the two stations in variable air volume operation mode and constant air volume operation mode.The result shows that the variable air volume operation mode is more energy efficient than the constant air volume operation mode at normal time,while in the peak period,the constant air volume operation mode is more energy efficient than the variable air volume operation mode.Finally,an energy-saving control operation mode combining variable air volume and constant air volume is proposed,and its energy-saving effect is comprehensively analyzed.The result shows that the energy-saving control operation mode is energy efficient by about 4% than the variable air volume operation mode,and is energy efficient by about 17% than the constant air volume operation mode.