Research On Cooling Load Zoning Prediction And Air Conditioning System Terminal Optimization Control Of A Terminal Building

With economic development,the construction of domestic terminal buildings has increased,becoming a huge building consumer group of energy with more than 60% energy consumption of central air conditioning system.Therefore,the research on energy saving of air conditioning system in airport terminal can not be ignored.The terminal has the characteristics of large space,dense passenger flow and long operation time.The large area uniform cooling mode adopted by the conventional centralized central air conditioning control system is far from meeting the different cooling load requirements of each area,which makes the uneven distribution of cooling load and poor thermal comfort of personnel more and more serious The "distributed" network structure is the key to solve this kind of control problem.In this paper,the temperature and humidity independent control central air conditioning system of a terminal is taken as the object,and the cooling load zoning prediction and swarm intelligence terminal optimization control strategy are studied.The specific contents are as follows:(1)research on the cooling load zoning of the terminal.Due to the large dynamic change of personnel density and obvious regional difference of solar radiation,the cooling load demand of each area is significantly different.Therefore,considering the different influence of various factors on regional load demand,according to the basic division principle,combined with the calculation method of boundary conditions,the load area is divided,which provides reliable partition results for the load zoning prediction and control of terminal central air conditioning system.(2)The cooling load zoning prediction model is established.Accurate cooling load demand zoning prediction is the premise of load distribution in different regions.Therefore,this paper proposes a short-term cooling load zoning forecasting model based on affinity propagation clustering algorithm(AP)and improved crowd search algorithm radial basis function neural network(ap-fisoa-rbf).The model uses historical load data,weather information and date type as inputs to forecast the cooling load demand of different regions.Compared with the traditional RBF,PSO-RBF and soa-rbf models,the average absolute percentage error of the proposed model is reduced by 93.05%,83.60% and 71.13% respectively,and the average prediction speed is increased by 54.34%,39.25% and 23.96% respectively.The proposed model can effectively overcome the influence of external environment on the prediction accuracy of building cooling load and improve the robustness of the prediction model.(3)Research on partition hierarchical control strategy based on swarm intelligence.Firstly,a fuzzy control algorithm of terminal equipment based on swarm intelligence is designed.Secondly,according to the mechanical and electrical equipment of air-conditioning terminal in different areas,the CPN network topology of swarm intelligence is established,and the swarm intelligence control platform is built.Then,by analyzing the control priority order of various terminal equipment in the same area,a terminal equipment partition of central air-conditioning system based on swarm intelligence is formulated Finally,combined with the forecast demand of cooling load partition,taking the comfort and energy consumption of personnel as the evaluation index,the simulation experiment of equipment energy-saving optimization control is carried out.The experimental results show that,compared with the traditional centralized control,the hierarchical fuzzy control strategy of air conditioning terminal equipment based on swarm intelligence in this paper realizes the distributed and intelligent precise control of swarm intelligence,and enhances the high adaptability of terminal equipment to the dynamic change of indoor load.It improves the hermal comfort requirements of personnel in different areas,the balance of load supply and demand.Considering the changing characteristics of indoor load in the terminal,forecasting the cooling load zoning prediction under summer conditions,and thinking about better load supply strategies,and terminal optimization control strategy under summer conditions.Taking the predicted cooling load as the demand,the group intelligent partition hierarchical optimization control can effectively realize the partition control of indoor hot and humid climate environment.To sum up,the content of this paper is of great significance to the realization of energy saving and consumption reduction,personnel thermal comfort of the terminal,and has guidance and reference for the optimal operation of the terminal central air conditioning system.