Date of Publication
11-22-2024
Document Type
Master's Thesis
Degree Name
Bachelor of Science in Mechanical Engineering (Honors) - Ladderized
College
Gokongwei College of Engineering
Department/Unit
Mechanical Engineering
Thesis Advisor
Ivan Henderson V. Gue
Aristotle T. Ubando
Defense Panel Chair
Laurence A. Gan Lim
Defense Panel Member
Gerardo L. Augusto
Conrad Allan Jay R. Pantua
Abstract/Summary
The urgent need to decarbonize existing buildings has led to an increased focus on energy retrofits as a crucial strategy for improving building performance and sustainability. While building energy simulation software offers valuable insights into the effects of various retrofit scenarios, determining the optimal energy retrofit solution remains a significant challenge due to the prohibitive computational costs associated with simulation-based optimization. This study presents an alternative approach to multi-objective design optimization of building energy retrofits involving a building energy simulation surrogate model. A case study of a religious building in Metro Manila, Philippines was used to demonstrate the proposed methodology. The methodology comprises four key steps: 1) a comprehensive building energy simulation database was created using Latin Hypercube Sampling, 2) regression models for energy consumption and thermal comfort were trained using this database, 3) these regression models were coupled with a Genetic Algorithm to perform multi-objective optimization, and 4) ranking of solutions in the Pareto front was demonstrated using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Optimization results were validated with the resulting accuracy and reliability of the surrogate model-based approach being within acceptable limits. The findings of this study suggest that regression surrogate models offer a computationally efficient and effective means of optimizing building energy retrofits. By providing a practical framework for multi-objective optimization. This research contributes to the advancement of sustainable building practices and supports the broader goal of decarbonizing the built environment.
Abstract Format
html
Language
English
Format
Electronic
Keywords
Buildings—Energy conservation
Recommended Citation
Dimaculangan, W. C. (2024). Multi-objective design optimization of building energy retrofit using building energy simulation surrogate model. Retrieved from https://animorepository.dlsu.edu.ph/etdm_mecheng/28
Upload Full Text
wf_yes
Embargo Period
11-22-2025
