Robust Quantile Regression Based Operation Energy Efficiency Analysis of Split Air Conditioner in Smart Buildings

Split air-conditioner is an important part in smart building, and its operation energy efficiency analysis plays a critical role in energy management and real-time operation of a smart building. In recent years, the energy efficiency of split air conditioners has usually been evaluated using a linear regression method. However, linear regression only studies the relationship between the independent variable and the conditional expectation of the dependent variable, it is impossible to comprehensively analyze the energy efficiency of real split air-conditioner. In this paper, a new method based on robust quantile regression is proposed to evaluate the energy efficiency of split air-conditioner. This method analyzes how the independent variables affect the median and multiple quantiles of the dependent variable. In addition, the proposed method does not require that the resultant statistical errors follow any Gaussian distribution. The simulation results show that the proposed method has stability and robustness in the energy efficiency assessment of split air-conditioners, so it has high application potential in smart buildings.