Research On Energy Efficiency Optimization Of Public Buildings Based On Passenger Flow Forecast

As the process of smart cities accelerates,the energy consumption ratio of public buildings in all buildings continues to increase.As a special public building with a large passenger flow,the waiting room of the railway station is difficult to take into consideration the comfort standards of personnel and energy-saving of the building due to the dense and large changes in the waiting room personnel.Therefore,it is of great significance to carry out energy-saving optimization for such public buildings.In addition,with the rise of energy saving and emission reduction ice storage technology,it is more widely used in the field of air conditioning in railway station buildings.The rational and accurate simulation of the cooling load of the railway station waiting room on the basis of dynamic passenger flow is the prerequisite for optimizing the operation mode of the building ice storage air conditioning.Therefore,this topic is based on the dynamic hourly cooling load value of passenger flow changes,and aims at the highest energy utilization rate and the lowest operating cost.The research on the optimization of ice storage air conditioning in this type of building is as follows:First,based on the historical hourly data of the railway station waiting hall,the shortterm passenger flow forecasting algorithm used in this topic—BP neural network,ARIMA time series and combined forecasting algorithm are determined.Each parameter value,and three algorithms are used to predict historical passenger flow data.Finally,the prediction results of the three algorithms are compared with the actual values,and a conclusion is reached that the combined prediction algorithm has high accuracy.Secondly,using the predicted passenger flow data as a prototype,the qualitative and quantitative analysis of different factors that affect the air conditioning load of the waiting room of the railway station is carried out.The method based on Energy Plus software simulation and model calculation is used to carry out the envelop structure and other factors hourly cooling load simulation,so as to simulate the dynamic hourly cooling load value of the ice storage air conditioning system in the railway station waiting hall.Finally,according to the process flow of the ice storage air conditioning system in the waiting room of the railway station,the operation model of the system—the cooling capacity model,the power consumption model,and the economic model are established.Based on the dynamic hourly cooling load value,the highest energy utilization rate and the lowest operating cost are set as optimization goals,combined with the relevant engineering constraints,the NSGA-II algorithm is used to optimize the operation of the air conditioning system,and the corresponding cooling Volume distribution control strategy.The simulation results show that under the guidance of the control strategy,the operating cost of the system can be saved by 13.0%,and the energy loss rate is reduced by 14.7%.