Bottom-up engineering models are an emerging approach for evaluating energy efficiency solutions at district or regional scales. More flexible than statistical models, bottom-up models allow planners to quantitatively evaluate energy efficiency and supply options, leading to more effective policies and energy demand solutions that better reflect our changing climate. This thesis compares two bottom-up methods for exploring resource and emission reduction strategies in the institutional sector: the Wireframe method and the Reference method. These methods are compared by predicting the annual consumption of post-secondary student residences in Southern Ontario and measuring the error of each, compared with the 2013 mandatory energy report data from the Ministry of Energy of Ontario. Both methods produced aggregate energy error ranges of 5% to 12% in a detailed analysis, suggesting that they are both effective for large-scale energy reduction studies.