Determination of the Influence of Outdoor Air Intake Fraction on Choosing Independent Variable for Cooling Regression Modeling in Hot and Humid Climates

摘要

On the establishment of a reliable baseline for energy savings estimation, one or more variables are usually used to determine a model by regression analysis. These regression models generally use one or more independent variables, such as outdoor air temperature (OAT), degree days, or a combination of these with occupancy or humidity. Based on a calibrated multifunction building energy simulation in a hot and humid climate, in this paper the study of the influence of outdoor air intake fraction on the selection of the best parameter to develop change-point regression modeling for cooling energy use was evaluated. A comparison among regressions based on three variables, two regularly used in measuring and verification (M&V) process (OAT and outdoor air enthalpy [OAE]), plus the addition of an operational enthalpy was carried out. The study included variations of the outdoor air intake fraction in the range of 10%-100% and the development of the corresponding patterns of regression models for each of the parameters. The results indicated clearly the advantage of the use of the operational effective enthalpy (OEE) cooling regression modeling, which produced a lower coefficient of variation of the root mean square error (CV-RMSE) and higher coefficient of determination (R~2), when outdoor air intake fraction is greater than approximately 15%.