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CC BY V4.0, Open Access
Thesis
Building Energy Use: Modeling and Analysis of Lighting & Mechanical Systems – a Case Study
Washington State University
Master of Science (MS), Washington State University
2022
DOI:
https://doi.org/10.7273/000005177
Abstract
Understanding how energy is used and where it can be saved in an existing building is critical not only from a cost and environmental standpoint, but for legal compliance as well, as the United States and the rest of the world increasingly have set tighter restrictions on energy usage and carbon emissions. Energy savings can be achieved from installing LED lights and occupancy sensors; however, the exact savings and impact of each method can vary depending on the building in question. The objective of this case study is to perform analysis of the lighting and mechanical systems in Washington State University Tri-Cities' Floyd & East buildings to determine energy savings potential. Lighting systems in each building were broken into several groups based on their operational patterns and then numerically modeled with the aid of Python. The results of this case study shows that 60% energy savings, totaling 350 MWh in a year, can be achieved by retrofitting fluorescent lights with LEDs and occupancy sensors. This energy savings translates to a reduction of 62.4 tonnes of CO2 emissions per year. The results of our cost-analysis in this model shows that the LED light retrofit has a break-even point at 15 months of operation. For the existing mechanical systems, three recommendations were proposed to improve its performance, including: the addition of water treatment for the HVAC process water, replacing pneumatic controls with digital ones, and the installation of variable speed drives.
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Details
- Title
- Building Energy Use
- Creators
- Aron Powers
- Contributors
- Messiha Saad (Advisor)Changki Mo (Advisor)Che-Hao Yang (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Engineering and Applied Sciences (TRIC), School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University
- Number of pages
- 62
- Identifiers
- 99901019236801842
- Language
- English
- Resource Type
- Thesis