Akomolafe, Marvelous I and Covenant University, Theses (2023) ASSESSMENT AND OPTIMISATION OF COOLING LOADS FOR OPTIMAL BUILDING ENERGY EFFICIENCY USING GREYTAGUCHI AND ANOVA METHODS. Masters thesis, Covenant University Ota.
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Abstract
Amid the escalating global energy usage and carbon dioxide (CO2) emissions originating from buildings, energy efficiency has become a topmost concern for energy policies across various nations. The problem is further amplified by the rapid surge in the usage of air conditioning systems, predominantly in the developing countries' infrastructure, influenced by higher living standards, modern architectural designs, and a preference for cooler indoor environments. The central aim of this research is to devise a cooling prediction model utilizing Taguchi orthogonal array and ANOVA techniques to optimise cooling loads in buildings, using Covenant University as a case study. The study primarily targets the compelling issue of energy inefficiency in selected buildings in Covenant University, with a special focus on improving energy efficiency through cooling load optimisation. Results of the investigation offered a predictive model which accounted for an impressive 98.51% of the cooling load variation, underpinned by an R2 value of 98.51% and an adjusted R2 value of 98.08%. The study further illuminated that the application of the model to the selected buildings showcased mixed outcomes. The university library's cooling load, originally at 137582.31W, was refined to 136816.11W, reflecting a 0.56% MAPE. The university chapel, starting with a cooling load of 149224.61W, experienced an optimisation down to 143776.22W, showcasing a 3.65% MAPE. Cafeteria 1 underwent a transition from its 110380.99W to a lower 108323.48W, marking a 1.86% MAPE. For the university Guest House, its initial cooling load of 89953.43W was pruned to 85393.19W, translating to a 5.07% MAPE. However, the Health Centre's cooling load escalated from 52494.41W to 53748.80W, resulting in a 2.39% MAPE. Further illuminating the study, the influence of key factors on the cooling load was discerned. The area of the roof (Ra) emerged as the most potent influence, followed closely by the number of occupants (Np), the wall area (Aw), and the power rating of equipment (Pe). Beyond pure statistics, the exploration extended into tangible engineering solutions conducive for energy conservation in the studied buildings. Techniques encompassed retrofitting with energy-efficient windows, the inclusion of dynamic building shading, optimisation of HVAC system operations, the integration of automated lighting and energy management systems, and the contemplation of alternative cooling mechanisms, such as evaporative cooling. Conclusively, this research not only furthers the understanding of building energy efficiency but also furnishes a blueprint for the effective application of energy conservation policies amidst the global urgency for sustainable practices. The data-driven insights presented here are crucial for energy planners, architects, and university authorities, laying a foundation for more energyefficient building operations.
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
| Depositing User: | nwokealisi |
| Date Deposited: | 11 Sep 2023 11:05 |
| Last Modified: | 11 Sep 2023 11:05 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/17294 |
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