Keywords
geographical locations, sensitivity analysis, retrofit, windows
Abstract
The study of building energy consumption has gained immense significance in recent times due to the burgeoning global population and the rapid depletion of energy resources. The present research focuses on analyzing individual parameters that impact building energy usage and devising methods and strategies to reduce energy consumption. An existing office building in Philadelphia was chosen as a reference for simulation in TRNSYS. The factors that affect the building, such as ambient temperature, solar radiation, building envelope, wind speed, and internal gains, were studied and defined according to the existing building standards. Predictive modeling is performed with these inputs for a range of infiltration rates – 0.25 ACH to 0.85 ACH, considering the variability of the parameter. The validated model was subjected to a sensitivity analysis by changing one potential parameter at a time to examine the influence of variation of these parameters on energy usage. The analysis found that the highest energy reduction is executed by replacing double-glazing windows with triple-glazing, with an energy saving of 8.43%. To evaluate the effect of location, a similar sensitivity study is conducted for the same office building in Edmonton and Mexico City. It is found that by replacing the same triple-glazing window with double-glazing, a 12.3% and 5.44% energy saving is achieved for the building in Edmonton and Mexico City, respectively. Henceforth, depending on electricity prices for the respective cities, building in Philadelphia, Edmonton and Mexico City is found to have a monthly savings of $3,133, $7582, and $1,552, respectively (all $ in USD). When considering identical parametric inputs, distinct energy savings are observed across varying locations. These statistics serve as valuable tools for making well-informed and rational decisions regarding investments in energy-efficient technologies and the pursuit of Net Zero energy buildings.
Primary Advisor
David Ting
Co-Advisor
Jacqueline Stagner
Program Reader
Beth-Anne Schuelke-Leech
Additional committee member(s)
Rajeev Ruparathna
Degree Name
Master of Applied Science
Department
Mechanical, Automotive and Materials Engineering
Document Type
Major Research Paper
Convocation Year
2023