Get started
Work

Thermal modeling, analysis of MUN CSF building, and feasibility study of space heating using electricity

Year: 2024
Type: dissertation
Abstract: Globally, buildings represent 30% of total energy demand, and in Canada, they contribute 25% to final energy consumption, predominantly in space heating, constituting about 60% of this consumption. This underscores a substantial opportunity for significant energy and cost savings. While many buildings are transitioning to electric heating for efficiency and cost-effectiveness, a thorough analysis, considering technological and financial aspects, is essential to explore the outcomes of such transitions. The current study focuses on the Core Science Facility at Memorial University, evaluating the feasibility of transitioning to electric resistive heating. Initial steps involve scrutinizing 2022 energy data, comparing it with similar buildings, and performing a calculation to gauge potential savings based on existing tariffs and transition costs. Subsequent phases include creating a thermal energy model using Energy3D and conducting a feasibility analysis with RETScreen Expert. OpenStudio is then utilized to develop a Building Energy Model for a comprehensive assessment of the transition's advantages. The final step extends this model to analyze the transition's impact under a potential future switch from a flat rate to a time-of-use electricity tariff in Newfoundland. The Core Science Facility’s current energy consumption exceeds the national median for university buildings. Transitioning to electric resistive heating, akin to current rates, can yield energy cost savings. A RETScreen feasibility study forecasts substantial annual cost reductions compared to 2022 data. The OpenStudio-derived Building Energy Model indicates additional energy savings. However, analysis of Time of Use and Flat Rate tariffs suggests potential benefits may not be realized. Comprehensive surveys covering occupancy, electricity usage, operational schedules, and construction details can enhance the energy model's accuracy. Further improvements can identify energy-saving measures and optimize operational strategies for the building.
DOI: 10.48336/kkfr-1v10
Language: English
Open Access status: green
OpenAlex ID: W6929015181
Cites:
Cited by:
Related to: