Multiple parameters analysis for energy efficiency of building air-conditioning systems

Multiple parameters statistical analysis is proposed for the diagnosis of energy performance of airconditioning systems. Hourly data output of a building energy simulation is provided for the validation of this proposed method. The annual hourly complex energy data are processed to create Bin parameters such as Bin temperatures and Bin enthalpy difference. The results of the Bin parameters analysis show that air-conditioning systems can be diagnosed for comparison or verification of real-time performance. The research also shows that outdoor dry bulb and wet bulb, and also the indoor outdoor enthalpy difference Bin parameters, are the important parameters for diagnosing the system performance factor (SPF) of the air-conditioning system. It has been found that for the same temperature and enthalpy Bins, the SPF values obtained are close. In general the higher the enthalpy difference the higher SPF is obtained. Frequency of the occurrence of the Bin parameters is also discussed. Hourly air-conditioning energy use is also analyzed corresponding to different Bins of the parameters. The method of diagnosis as proposed can be used in comparing system performance such as green building energy saving retrofitting.