Kheiri, Farshad (2020-11). An Improved Method for the Estimation of the Energy Consumption and Savings of Code-Compliant Office Buildings in Different Climates. Doctoral Dissertation.
Degree day methods are used in the estimation of building energy consumption and climate classification for buildings (e.g. in ASHRAE Standard 169-2013, which is adopted in ASHRAE Standard 90.1-2016). This study, first assessed the effectiveness of the conventional degree days in estimating building energy consumption in different moisture regimes. The analysis was done by comparing the energy performance of the DOE/PNNL medium office prototype building models in the 801 locations in the U.S. The results revealed large variations in the annual energy consumption of the models in the different moisture regimes within each climate zone. Furthermore, large differences in the estimated energy savings by utilization of daylight were shown in different locations. In addition, detailed pairwise analyses were performed to analyze the large variation in the cooling or heating energy consumption in sites with similar Cooling Degree Days (CDD) or Heating Degree Days (HDD), respectively. The analysis revealed that the influential weather parameters that affected the building energy consumption were not fully accounted for in a conventional degree day method. In other words, the level of aggregation of the data in the conventional degree day method masks some of the informative characteristics of the outdoor dry-bulb temperature. To resolve these discrepancies, a split-degree day method was proposed to calculate the split-Cooling Degree Days (sCDD) and the split-Heating Degree Days (sHDD). The results show that in the regression models using the split degree days compared to the conventional degree days, the coefficient of determination of the estimations of the energy consumption increased for the total annual energy use (from 0.913 to 0.965), the heating energy use (from 0.891 to 0.981), the cooling energy use (from 0.979 to 0.982), and the fan energy use (from 0.383 to 0.722). Similar results were shown for the models with higher thermal mass. The proposed method can be used for building energy consumption estimation, weather-normalized building energy savings calculation, and climate classification. Moreover, a new adjustment method was developed using the proposed split-degree day method that reduces the variations in the above code values in the performance compliance path in different locations from 14% to 2%.