Enhancing building energy efficiency by adaptive façade: A computational optimization approach

• Published in: Applied energy Vol. 265; p. 114797
• Main Authors: Bui, Dac-Khuong, Nguyen, Tuan Ngoc, Ghazlan, Abdallah, Ngo, Ngoc-Tri, Ngo, Tuan Duc
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2020
• Subjects: Adaptive façade; algorithms; automation; Building energy efficiency; Building performance simulation; buildings; case studies; climatic factors; computer simulation; computer software; energy efficiency; Façade optimization; Modified firefly algorithm; Smart windows; transmittance; Building energy efficiency; Smart windows; Façade optimization; Building performance simulation; Modified firefly algorithm; Adaptive façade
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2020.114797

•A computational optimization approach is proposed to support adaptive façade design.•Two case studies are used to validate the capacity of the proposed approach.•The effects of the adaptive façade system are analyzed and discussed.•The proposed approach could reduce energy consumption by 14.2–29.0%.•The study facilitates the exploration of next-generation adaptive façade concepts. The energy consumption in buildings, which accounts for approximately one-third of the total energy used in the world, can be reduced significantly by employing adaptive façades. In this study, a computational optimization approach is proposed to enhance the energy efficiency of buildings based on the design of an adaptive façade system, which can adapt its thermal and visible transmittance for dynamically varying climatic conditions. The engine of the adaptive façade design approach is an automated optimization process, which combines the building energy simulation program (EnergyPlus) with an optimization technique through Eppy, a powerful Python toolkit. The modified firefly algorithm, an in-house optimization tool, is employed to design the adaptive façade system in this study. However, our proposed method is not tied to any particular optimization tool and does not impose any restrictions on a type of building. To this end, the capability of the proposed method for enhancing building energy efficiency is validated by two case studies, namely a typical single office room and a medium office building. We found that the proposed adaptive façade system can reduce the energy consumption by 14.9–29.0% and 14.2–22.3% for the first and second case study, respectively, compared to the static façades. These significant findings demonstrate the potential of adaptive façades to enhance the energy efficiency of buildings.