The multiple linear regression models of heat load for air-conditioned room

Abstract

© 2020 This study developed a heat load model of an air-conditioned room using multiple linear regression. A sensitivity analysis was first used to simplify the heat load model by neglecting the less sensitive levels of independent variables. The experiments were tested in three thermostat setting conditions of 25, 26, and 27 °C. The experimental data were collected to determine normalized sensitivity coefficients and regression coefficients of the heat load model. The sensitivity analysis results showed that the radiation parameters had a major impact on heat load. Furthermore, the air-conditioned room properties did not give a significant difference in the heat load as compared to other parameters. Moreover, the heat load model with the regression coefficients was reported, as well as the correlation coefficient. This model gave a good prediction of the heat load with an error of 0.15%.