Study On Operation Parameters Optimization Of Air Conditioning Refrigeration System In A Shopping Mall In Kunming

With the rapid development of national economy,the proportion of public buildings in civil buildingshas been increased.As the energy consumptiona of public buildings are usually high,so energy saving in public buildings has become the mainstream research topic in the field of building energy conservation.As one of the types of high energy consumption in public buildings,it is imperative to save energy in shopping malls.The central air conditioning system is the largest energy consumption system in shopping malls,and its total energy consumption can reach to about 35% of the total energy consumption of shopping malls.The energy consumption of air conditioning refrigeration system accounts for about 60% of the total energy consumption of central air conditioning system.The optimization of its operation parameters will directly affect the energy consumption of the whole central air conditioning system and even the whole shopping mall.Therefore,the optimization of operation parameters of air conditioning refrigeration system in shopping malls is of great significance to the energy saving of the mall.In this paper,the central air conditioning refrigeration system of a shopping mall in Kunming is taken as the research object,and the unreasonable operation problems such as excessive small temperature difference between supply and return chilled water and return water supply,excessive evaporation temperature and condensation temperature are too high or too low.Combined with the algorithm research,the operation parameters of the refrigeration system have been optimized in order to provide a reference for the efficient operation of the air conditioning refrigeration system in the shopping mall in different load ranges.The main work of this paper is as follows:(1)The mathematical model which is suitable for the refrigeration system equipments of shopping mall was selected,and the historical operation data of the air conditioning system were collected.Combined with the specification and related literature,the operation status of each equipment in refrigeration system was evaluated and studied.(2)Taking a refrigeration system as an example,based on the original record data from the energy mornitoring platform,the chilled water flow rate,cooling water flow rate,evaporation temperature,evaporator inlet temperature and condenser inlet temperature were selected by kernel principal component analysis(KPCA)as input parameter variables.Evaporation temperature and condensation temperature were classified according to temperature and load rate,and the mapping relationship between input parameters and energy efficiency of refrigeration system were obtained by using neural network algorithm.The mapping relation was used as the fitness function of genetic algorithm.Based on genetic algorithm,the original data were optimized and analyzed.According to optimized data,the load rate is determined by neural network.Finally,the optimum energy efficiency value and the best parameter value under certain load rate in each load rate interval were obtained.Compared with the original data,the error between the optimized energy efficiency and the actual energy efficiency is less than 5%,and it is more than 12.3% higher than the optimal energy efficiency value calculated by the original data.(3)TRNSYS platform was employed to simulate and verify the original data.It was found that the error between the simulated model and the actual model is less than 10%,which showed that the established TRNSYS model was appropriate to use.Eleven groups of operation parameters with the load rate of 80% were designed,and the operation energy efficiency of 81% load rate was compared with that of 81% load rate in algorithm optimization.It was found that the energy efficiency of the parameters optimized by the algorithm was still the highest in the model,which proved that the global optimization performance of the algorithm was better.The optimization method proposed in this paper has good energy saving effect and can provide theoretical basis and reference for the optimal control of refrigeration system in shopping malls.