Energy Usage Modelling for Residences of a South African Academic Institution

In residential buildings, various factors often have a significant impact on a building's energy consumption. This paper aims to utilize various existing models to evaluate the sensitivity and influence of each of these factors on the building's energy usage. The factors considered include: average temperature, heating degree days (HDD), cooling degree days (CDD), number of workdays, number of nonworkdays and building occupancy. The models considered were: linear two variable and multivariable regression, exponential regression and polynomial regression. The data used for the modeling was that of the energy usage of all the residences of a South African University, during the 2017 academic year. The results of this study revealed that the models developed using polynomial regression produced coefficient of determination (R
²
) values ranging from 0.7 to 0.89 in the case of temperature and occupancy, and 0.39-0.69 in the case of workdays and non-workdays, which were the highest model accuracies when compared to those of other models. Analysis of the results also revealed that certain factors such as building occupancy had a greater correlation to the building energy usage. The final model developed (A linear multivariable regression model) achieved an R
²
value of 0.95 indicating the model's high accuracy in predicting the dependent variable (energy consumption) using the factors indicated as independent variables to the model.