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Optimal design of an Origami-inspired kinetic façade by balancing composite motion optimization for improving daylight performance and energy efficiency

Author

Listed:
  • Le-Thanh, Luan
  • Le-Duc, Thang
  • Ngo-Minh, Hung
  • Nguyen, Quoc-Hung
  • Nguyen-Xuan, H.

Abstract

This article presents a novel concept for an Origami-inspired shading device based on dynamic daylight that can be used to improve the daylight performance of a target building and reduce the energy consumption for the building. The daylight performance is evaluated based on the Leed v4 (Leadership in Energy and Environmental Design) daylight criterion. The proposed shading device is experimented in an office located in Ho Chi Minh City, Vietnam, where there is a tropical monsoon climate being hot and humid by the year. To investigate the effectiveness of the proposed design in acting as a sun shading system for the office, we consider eight cases corresponding to eight directions which are South, North, East, West, South-East, North-East, South-West, and North-West. An automatic simulation optimization procedure is developed by combining a daylight simulation tool called DIVA and an optimization method called Balancing Composite Motion Optimization (BCMO). BCMO is used to find the optimal design for the proposed kinetic shading device which will help the building to improve daylight performance. It must be noted that the proposed framework is not necessarily tied to any particular optimization tool or type of building. The results show that the proposed kinetic device has outstanding performance as it helps the building to achieve 2, 3 points in Leed v4 for four different directions, including North, North-East, South, North-West.

Suggested Citation

  • Le-Thanh, Luan & Le-Duc, Thang & Ngo-Minh, Hung & Nguyen, Quoc-Hung & Nguyen-Xuan, H., 2021. "Optimal design of an Origami-inspired kinetic façade by balancing composite motion optimization for improving daylight performance and energy efficiency," Energy, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:energy:v:219:y:2021:i:c:s0360544220326645
    DOI: 10.1016/j.energy.2020.119557
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    References listed on IDEAS

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    1. Bui, Dac-Khuong & Nguyen, Tuan Ngoc & Ngo, Tuan Duc & Nguyen-Xuan, H., 2020. "An artificial neural network (ANN) expert system enhanced with the electromagnetism-based firefly algorithm (EFA) for predicting the energy consumption in buildings," Energy, Elsevier, vol. 190(C).
    2. Su-Ji Choi & Dong-Seok Lee & Jae-Hun Jo, 2017. "Method of Deriving Shaded Fraction According to Shading Movements of Kinetic Façade," Sustainability, MDPI, vol. 9(8), pages 1-19, August.
    3. Joud Al Dakheel & Kheira Tabet Aoul, 2017. "Building Applications, Opportunities and Challenges of Active Shading Systems: A State-of-the-Art Review," Energies, MDPI, vol. 10(10), pages 1-32, October.
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    Citations

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    Cited by:

    1. Qibo Liu & Xiao Han & Yuheng Yan & Juan Ren, 2023. "A Parametric Design Method for the Lighting Environment of a Library Building Based on Building Performance Evaluation," Energies, MDPI, vol. 16(2), pages 1-20, January.
    2. Angeliki Kitsopoulou & Evangelos Bellos & Christos Tzivanidis, 2024. "An Up-to-Date Review of Passive Building Envelope Technologies for Sustainable Design," Energies, MDPI, vol. 17(16), pages 1-55, August.
    3. Gonçalves, M. & Figueiredo, A. & Almeida, R.M.S.F. & Vicente, R., 2024. "Dynamic façades in buildings: A systematic review across thermal comfort, energy efficiency and daylight performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
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    5. Tyler R. Stevens & Behzad Parsi & Rydge B. Mulford & Nathan B. Crane, 2024. "Dynamic Radiant Barrier for Modulating Heat Transfer and Reducing Building Energy Usage," Energies, MDPI, vol. 17(16), pages 1-19, August.
    6. Yijun Lu & Wei Wu & Xuechuan Geng & Yanchen Liu & Hao Zheng & Miaomiao Hou, 2022. "Multi-Objective Optimization of Building Environmental Performance: An Integrated Parametric Design Method Based on Machine Learning Approaches," Energies, MDPI, vol. 15(19), pages 1-23, September.

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