Modeling the relationship between outdoor meteorological data and energy consumptions at heating and cooling periods: Application in a university building

In this study regression modeling is proposed for calculating the heating and cooling load of the buildings by considering the outdoor meteorological data. For this pupose, Balikesir University Rectorate Building is selected as the case building. In the winter months, measurements were made in the hot water boiler in the basement of the building for the heating energy load. For the cooling energy load, measurements were made in the chiller groups near the building. As climate data, eight variables were considered: outdoor temperature, solar radiation, relative humidity, wind speed, atmospheric pressure, sunshine duration, steam pressure, and 1 m underground temperature. The Minitab statistical analysis program was used to perform the modeling. 55 samples were used for mathematically modeling the heating load, while 37 samples are used for modeling the cooling load. The R\begin{document}$ {}^{2\ } $\end{document}(coefficient of determination) values are calculated as 96.2% and 98.94% for cooling load and heating load, respectively. In addition to these findings, ANOVA results for both models were examined and both models were found to be significant.