Simulation Research Of Supply And Return Air Temperature Optimization Control Of Air Conditioning System In Subway Station For Energy-saving

As a fast and safe way of transport,the subway effectively alleviates the ground traffic pressure.However,with the mileage increasing,the rising energy consumption has aroused our attention.As an important guarantee for the subway station environment,the ventilation and air conditioning system consumes the most energy of the entire rail transit.At present,there are many problems about the ventilation and air conditioning system of the subway station.For instance,the equipment selection is too large,the automatic control mode is not fully considered and the station load is currently strong dynamic and so on.As a result,there is a lot of energy-saving space in the ventilation and air conditioning system of the subway station.It is necessary to analyze the energy consumption and optimize control the system.The main researches of this paper are as follows:(1)The energy consumption analysis of the frequency conversion controlled supply and return air temperature in subway station air-conditioning system.Aiming at the dyanmic load of the air conditioning system and the complexity between the controlled variables and the system energy consumption,this change of the system energy consumption with the changed values of controlled variables was studied.Based on the subway ventilation air conditioning training platform in one school of Beijing,this paper built a TRNSYS simulation platform,and selected two typical days in July to control the supply and return air temperature.Then the change of energy consumption with the setting values was analyzed through the combination of the cross-conversion setting values.The results showed that the energy consumption does not increase or decrease monotonically with the setting values when the weather is diffierent.At one time,there exists a combination of the setting values to minimize the energy consumption.(2)Research on the supply and return air temperature and system energy consumption model based on ISOA-LSSVM.In view of the importance of the controlled variables in the air conditioning system and the large hysteresis of the system,in this paper,the correlation among the environment variables,the controlled variables and the system variables and the energy consumption of the system was deeply studied.Secendly,the prediction model between the supply and return air temperature and the system energy consumption based on the least squares support vector machine(LSSVM)was proposed.Finally,due to the slow computation speed,the improved seeker optimization algorithm(ISOA)was proposed to select the parameters of LSSVM and improve the calculation precision and speed.The ISOA improved the fuzzy membership function and search direction of the traditional seeker optimization algorithm.The results showed that the selected model input vector had a good representation according to the correlation analysis.Using ISOA-LSSVM algorithm could predict the energy consumption of the system well.ISOA-LSSVM was 0.228% higher and 10 folds faster than LSSVM.(3)Research on the optimal control of the supply and return air temperature based on the energy consumption model.Aiming at the problems of the optimal control of the controlled variables of the air conditioning system and the SOA is suit for the optimization of the continuous function.In this paper,the energy consumption model by ISOA-LSSVM was used for the objective function of optimal control,and the optimization range of variables was considered with the relative thermal index.The random population by ISOA algorithm was dispersed.Then it was applied to the dispersed functions.Supply and return air temperature of air conditioning system were optimized every hour.The results showed that energy saving rate was improved compared with the constant setting value when operated with frequency conversion.(4)Experiment of optimization control on the subway ventilation air conditioning training platform.The experiment was conducted at the subway ventilation air conditioning training platform in a school of Beijing.Firstly,the supply and return air temperature control system based on PLC and monitoring system were builded.Secondly,the experimental data was collected and processed.Thirdly,the methods of system model based on ISOA-LSSVM and the supply and return air temperature optimization control based on energy consumption model were verified.The results showed that the accuracy and calculation speed of the system based on ISOA-LSSVM were improved compared with other methods.The energy saving rate was improved based on optimized supply and return air temperature.