PCA-ANN integrated NSGA-III framework for dormitory building design optimization: Energy efficiency, daylight, and thermal comfort

Afshin Razmi, Morteza Rahbar and Mohammadreza Bemanian

Applied Energy, 2022, vol. 305, issue C, No S0306261921011569

Abstract: “Framework” and “case-study” are the two most prominent features in the optimization of architectural building design. The first can improve the speed of the process, the accuracy and integration of the outcome. The second can evolve the design knowledge of the various types of buildings in practice. This paper presents the “PCA-ANN integrated NSGA-III” framework that is a fast, accurate, and integrated solution for practical, erosive, and complicated building performance optimization problems, especially when the case study is a multi-type building such as a dormitory. The novelty and contribution of this paper exist in all three phases of its research framework. First, the dormitory building was parametrically modeled as a case study in two conventional dormitory building types. Second, an artificial model called PCA-ANN is presented in which problems that have a more complicated and practical case study with a multi-type building can be solved simply, integratively, and accurately. Third, the capabilities of NSGA-III are introduced and showed that it could be more accurate in comparison with NSGA-II, and then NSGA-III was integrated with the PCA-ANN model to solve the many-objective problem posed in this study. R2 score for PCA-ANN in the best-presented structure reached 0.99. In the overall best building alternative, energy efficiency and daylight performance for the whole year and thermal comfort performance in the free running period improved by 41.27%, 42.24%, and 15.57%, respectively, compared to its reference model. The presented framework can be applied and generalized to building energy optimization problems in practical and complex cases.

Keywords: Artificial intelligence; Multi-objective optimization; Dormitory building; Energy; Daylight; Thermal comfort (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.apenergy.2021.117828

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