Theory And Application Research On Operation Energy Efficiency Optimization For Air Conditioning Cooling Sources Of A Shopping Mall

With the acceleration of urbanization process in China, the number and size of shoppingmalls, have entered a period of rapid development, improving people’s living standard, butalso consuming a lot of energy. The energy consumption of central air-conditioning systemaccounts for a considerable proportion in the building of shopping mall. Therefore, exploringa optimized operation methods to maximum find the energy saving potential from centralair-conditioning system and reduce the energy consumption, has very important implicationsfor shopping mall building energy saving.In this paper, the operating parameters nature of the air conditioning cooling sourcesystem in a shopping mall is studied to establish identification model and discusses theoptimization control method. The application research of the online optimization control ofthe air conditioning cooling source system in a shopping mall, which is based on themanagement control system in this shopping mall, will provides references to the applicationof the online saving energy control of the air conditioning cooling sources system. The studyis summarized as follows:（1）The air conditioning cooling source system equipment model is developed based onthe experimental data of cooling source system, and it shows high precision and predictionprecision.（2）The simulator of air conditioning cooling source system is established which canstudy the energy consumption in different control methods.（3）Based on the simulator of air conditioning cooling source system, the coolingsource system energy saving operation optimization parameters of the shopping mall havebeen confirmed using genetic algorithm, and the result shows that the method is feasible.（4）A dynamic online identification method has been proposed to solve the problem ofthe energy efficiency model changed with the time. Based on the management control systemof the shopping mall, the online optimization control is achieved, and the result shows that theenergy efficiency of cooling source system is improved by5.86%.