Research On Dynamic Air Conditioning Load Prediction And Energy Saving Optimization Of Electric Equipment Room In Metro Station

With the continuous progress of society,urban rail transit has ushered in the rapid development,but its energy consumption problem is increasingly significant.Ventilation and air conditioning system is an essential part of subway system design.According to statistics,the energy consumption of ventilation and air conditioning in subway stations accounts for40%-50% of the total energy consumption of subway stations.The subway station ventilation air conditioning system energy saving research focus in the public area ventilation and air conditioning system,the energy saving research of equipment management USES a room is relatively lack,and equipment management USES a room ventilation air conditioning system energy consumption is mainly from electrical equipment room,such as can effectively reduce energy consumption of this part,to the subway station ventilation and air conditioning system energy saving.This paper,taking a subway station in Guangzhou as the research background,aiming at the subway station of cold energy of buildings for the electrical equipment of the mismatch between supply and demand,operation strategy problem such as unreasonable,through in-situ test,model test and numerical simulation method of combining the,for the purpose of ventilation and air conditioning system energy saving,electrical equipment room in metro station for all-year hourly air conditioning cooling load simulation,The dynamic air conditioning load prediction model is established,and the annual energy consumption of ventilation and air conditioning system of electrical equipment room in subway station under three different operating modes is analyzed.Firstly,this paper uses Energy Plus load simulation software to simulate the cooling load of air conditioning in a typical island subway station in Guangzhou,and obtains the distribution and variation of cooling load of air conditioning in the electrical equipment room of the station,and analyzes its load characteristics.Secondly,set up the electrical equipment room air conditioning load prediction model of BP neural network,the use of SPSS software for pretreatment of the sample data,get the input layer of the model parameters,by analyzing the principle and advantages and disadvantages of the model,by using the genetic algorithm to optimize the BP neural network weights and threshold method,improve the model generalization ability,By comparing the errors of the two models before and after,the accuracy and feasibility of the model are verified.The prediction results show that the optimization of BP neural network model by genetic algorithm is an effective method,and the prediction accuracy of the model is high,and the desired effect is achieved.Finally,aiming at the subway station housing problems existing in the operation of electrical equipment,electrical equipment in a subway station in Guangzhou housing for the case analyses the ventilation and air conditioning system energy saving potential,through the simulation analysis of the whole air conditioning energy consumption operation mode,based on outdoor air condition point operation mode and based on the operation mode of annual energy consumption of air conditioning load forecasting,the results show that the Compared with the full air conditioning mode,the outdoor air status point operation mode saves 17.9%of the annual energy,the air conditioning load prediction mode saves 23.1% of the annual energy,and the air conditioning load prediction mode saves 6.3% of the annual energy.