Research On Control And Optimization Of High-rise Central Heating System Based On Insect Intelligent Technology

Centralized heating is mainly used in winter in northern China.Because the indoor temperature of heating is affected by many factors,the traditional control method of central heating system cannot guarantee the indoor comfortable temperature of building groups.Circulating water pumps in residential heat exchanger stations cannot effectively distribute the workload of circulating water pumps according to the heating demand of building groups,resulting in a large amount of energy waste.Therefore,how to achieve lower heating energy consumption and higher indoor thermal comfort is of great significance.Based on new generation Intelligent building platform techniques,the intelligent control method of central heating system group is proposed in this paper.The group intelligent room temperature model predictive control is used to predict and group control the room temperature of central heating building,and the group intelligent optimal control of circulating water pump is carried out according to the amount of heating water needed after the control,so as to solve the shortage of centralized control.Focusing on this goal,this thesis focuses on the group intelligent control and optimization of the central heating system in the residential building of the South Campus of Xi'an University of Architecture and Technology.The main research work as follows:(1)In this paper,the influence factors of indoor thermal environment are analyzed by mechanism modeling,and the thermal balance model at room temperature is established by state space method.After that,the thermal characteristic index of the room is solved by characteristic method,and the indoor temperature prediction model is established.The comparison between the simulation model experiment and the measured data shows that the indoor temperature prediction model can correctly reflect the actual situation of the system,and the prediction effect is accurate.(2)Using the building energy simulation software TRNSYS to establish a centralized heating group intelligent control simulation system based on the topological structure of the high-rise central heating system.The building units and heating equipment in the system are equipped with distributed controllers to form intelligent equipment,and the control signal is transmitted to the radiator valve to operate,thereby changing the indoor temperature of the corresponding building.The TRNSYS is used to control the traditional temperature control valve PID control and group intelligent model for the residential building in winter.The results show that the group intelligent model predictive control can keep the room temperature within the set range,the control effect is more stable than the traditional control mode,and the energy consumption of heat energy consumption can be reduced.(3)According to the group intelligent room temperature model predictive control of the radiator valve opening degree,in the case of setting the water supply temperature constant and without the heat loss,calculate the radiator circulation water volume of each room according to the radiator dynamic model,and The circulating water volume of the high-rise building is summed to obtain the total circulating water required for the secondary network of the district heat exchange station.The group intelligent algorithm is used to optimize the parallel water pump of the district heat exchange station.The results show that the individual efficiency and overall efficiency of the parallel pump optimized by the group intelligent algorithm are smaller than the traditional centralized control method,which reduces the energy consumption of the heat exchange station.Through research,it is found that the room temperature value obtained by mechanism modeling and the room temperature correlation coefficient collected by the real environment are 0.887,which can be used as the basis for predictive control of room temperature model.The room temperature predicted by the group intelligent model can be maintained within the set range,and the building heating water demand is saved by 22.09% of the water consumption compared to the traditional control.After intelligent optimization of the circulating water pump of the heat exchange station,the efficiency of the parallel pump is improved by 16.74% before optimization.