Model Optimization Of Existed Central Air-conditioning System Based On Lumped Parameter And Its Application

Building air-conditioning load changes with outdoor weather condition, indoor personnel mobility and indoor heat source, and the traditional air-conditioning system is designed for the best operation based on rated condition, which results in a lower operating efficiency under part load. Therefore, it is needed to study the operating rule and energy-saving optimization control strategy of air-conditioning system under part load, which is easy to be realized by simulation. For existed central air-conditioning system, however, it is difficult to obtain the specific structural parameters of each component in the system, which leads to the accurate simulation on basis of the specific structural parameters hard to achieve. To solve above problems, this paper combines the theoretical analysis, numerical simulation and experimental research, builds the simulation model of central air-conditioning system based on the lumped unknown structure parameters. And a data selection method to improve the accuracy of the model in a large number of measured data is proposed by studying the influence of measured data on the model accuracy. On this basis, the integrated control strategy of energy-saving optimization on the central air-conditioning system under part load is studied to make the overall system run best.The paper acquires the model parameters by lumping unknown structure parameters of each component in the system, which can be got with actual operating data of the system, and the model of each component in central air-conditioning system including water chiller, surface air cooler, cooling tower, conveying equipment are built. Finally, the simulation model of central air-conditioning system based on the lumped parameters is established according to the actual operation characteristic of air-conditioning system.The comprehensive performance test platform of central air-conditioning system is constructed, and the influence of measured data on the model parameter determination and the model accuracy is studied. The result shows that the accuracy of the model can be improved significantly by selecting 5 working conditions X 2 groups of measured data rather than 2 working conditions X 5 groups of measured data, the average relative error of main performance parameters of the system with the former is less than 12.9%, while the latter is less than 16.2%. And the number of different experimental conditions is the main factor which affects the accuracy of the system model, so the experimental conditions should be obtained as much as possible in order to ensure a higher accuracy of the system model when solving the model parameters.Based on the simulation model of central air-conditioning system whose accuracy meets the requirement, the effect of changing single operation condition on the performance of air-conditioning system is studied to guide the formulating of the energy-saving optimization operating integrated control strategy for air-conditioning system under part load. Considering two main factors causing the change of the air-conditioning load, which are outdoor weather condition and indoor load, the integrated control strategies of the two cases are simulated and analyzed to provide suggestions for the optimization control of the air-conditioning system energy-saving operation. When the outdoor weather condition changes, in meet the dehumidification requirement, the comprehensive efficiency of the system is 9.5% higher when selecting the integrated control strategy of variable compressor frequency, variable chilled water flow and variable air volume of AHU rather than selecting the integrated control strategy of variable compressor frequency and variable air volume of AHU. And when the indoor load changes, the system has a higher comprehensive efficiency and desiccant ability under the whole load conditions when selecting the integrated control strategy for variable air volume of AHU rather than selecting the integrated control strategy for variable the outlet dry bulb temperature of AHU.