Optimization Of Energy Saving And Control Of Central Air Conditioning System Based On Parameter Lumping

The load of central air-conditioning system is affected by outdoor climate and indoor usage conditions.However,the design of air-conditioning system is based on optimal operation in rated condition,which leads to the efficiency decrease in partial load condition.As a result,it is significant to study the control strategy when the air-conditioning system operates in partial load condition.Analog simulation is an effective method because there are many control parameters and each parameter has different effect on the system.So far,two normal ways have been widely used to study the air-conditioning system,one is accurate simulation based on structure parameters and the other is carried out by experimental data and empirical formulas.However,normal ways cannot apply to the air-conditioning system as structure parameters and experimental data are difficult to obtain.According to the above problems,this paper lumps the unknown structural parameters of each component based on the coupling relationship of the components in the central air conditioning system and form the performance simulation model of the central air conditioning system.The central air conditioning system performance experiment device is constructed to verify the air conditioning system model.On the basis of this,the paper analyzes the influence of performance through different control strategies,the priority control strategy and the global optimization control strategy of the control parameters with the system integrated efficiency EER as the evaluation standard are put forward.At the same time,studying the energy saving effect of the single variable control and multivariable joint control.Finally,optimizing the control of the actual air conditioning system and analyzing of the energy efficiency after the implementation.Based on the parameter lumping method,the main equipments of air conditioning system are modeled,such as chiller,air handling box,cooling tower and conveying equipment,and the performance simulation model of central air conditioning system is formed according to the coupling relationship of each component.The performance simulation device of the central air conditioning system is built and the measured data of different air conditions are collected to verify the performance simulation model of the air conditioning system.The results show that the error between the simulation and the experiment is within 13%.Through the performance simulation model of the central air conditioning system,the influence of the chilled water flow,the cooling water flow rate,the air volume of air conditioning box and the air volume of cooling tower on the system performance of the air conditioning system performance experiment device is analyzed to determine the single variable operation priority control strategy.On this basis,the optimal operation conditions of multi-component control under different load are simulated to determine the optimal control strategy of chilled water system,cooling water system and global multi-variable joint control.The energy saving effect of the single variable,two-variable and multivariable optimal control strategies is analyzed and the results show that the best energy saving effect is optimized.Based on the above control strategy optimization research method,the energy-saving optimization operation of air-conditioning system of Wuxi HuaqingBridge subway station is studied.The operation rules of subway air conditioning system are analyzed through the parameters of equipment,typical meteorological parameters and load.Through the discussion of the effects of chilled water flow,chilled water supply temperature,air volume air of conditioning box and air volume of cooling tower on system performance,a single variable priority control strategy is obtained.At the same time,the global optimization control analysis is carried out and the optimal operation strategy is proposed when the load rate is 0.75 and 0.9.The results of the implementation show that 2016 air-conditioning quarter electricity consumption compared to the same period in 2015 decreases by 14.4%.