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Multi-Objective Optimization of Bifacial Photovoltaic Sunshade: Towards Better Optical, Electrical and Economical Performance

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Listed:
  • Chunying Li

    (School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
    Shenzhen Key Laboratory of Architecture for Health & Well-Being (in Preparation), Shenzhen 518060, China)

  • Wankun Zhang

    (School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
    Shenzhen Key Laboratory of Architecture for Health & Well-Being (in Preparation), Shenzhen 518060, China)

  • Fang Liu

    (School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
    Shenzhen Key Laboratory of Architecture for Health & Well-Being (in Preparation), Shenzhen 518060, China)

  • Xiaoyu Li

    (School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
    Shenzhen Key Laboratory of Architecture for Health & Well-Being (in Preparation), Shenzhen 518060, China)

  • Jingwei Wang

    (School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
    Shenzhen Key Laboratory of Architecture for Health & Well-Being (in Preparation), Shenzhen 518060, China)

  • Cuimin Li

    (School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China)

Abstract

Bifacial photovoltaic sunshade (BiPVS) is an innovative building-integrated photovoltaic (BIPV) technology. Vertically mounted BiPVS is capable of converting part of the incident solar radiation into electricity, regulating the indoor heat gain from solar penetration and improving daylighting. An excellent BiPVS design should comprehensively consider its impact on building performance and economic viability. This study aims to address this issue by proposing a parametric design-based multi-objective optimization (MOO) framework to maximize indoor useful daylight illuminance, minimize air-conditioning energy consumption, and shorten the payback period by optimizing BiPVS design parameters. The framework utilizes the Ladybug, Honeybee, and Wallacei plugins on the Rhino-Grasshopper simulation platform. It validates the optimization potential of BiPVS in a typical office located in a hot summer and warm winter zone. The results indicate that BiPVS has significant energy-saving and daylighting potential. Compared to the baseline model without BiPVS, useful daylight illuminance is increased by 39.44%, air-conditioning energy consumption is reduced by 12.61%, and the economically satisfactory payback period is 4.80 years. This study provides a practical solution for the competing objectives of daylighting and energy saving in buildings with significant renewable energy utilization. The developed framework is highly efficient and versatile and can be applied to other BIPV designs, which benefits the realization of carbon-neutral goals in the building sector.

Suggested Citation

  • Chunying Li & Wankun Zhang & Fang Liu & Xiaoyu Li & Jingwei Wang & Cuimin Li, 2024. "Multi-Objective Optimization of Bifacial Photovoltaic Sunshade: Towards Better Optical, Electrical and Economical Performance," Sustainability, MDPI, vol. 16(14), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:5977-:d:1434206
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    References listed on IDEAS

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    1. R. Kopecek & J. Libal, 2018. "Towards large-scale deployment of bifacial photovoltaics," Nature Energy, Nature, vol. 3(6), pages 443-446, June.
    2. Li, Zihao & Zhang, Wei & He, Bo & Xie, Lingzhi & Chen, Mo & Li, Jianhui & Zhao, Oufan & Wu, Xin, 2022. "A comprehensive life cycle assessment study of innovative bifacial photovoltaic applied on building," Energy, Elsevier, vol. 245(C).
    3. Taveres-Cachat, Ellika & Lobaccaro, Gabriele & Goia, Francesco & Chaudhary, Gaurav, 2019. "A methodology to improve the performance of PV integrated shading devices using multi-objective optimization," Applied Energy, Elsevier, vol. 247(C), pages 731-744.
    4. Khoroshiltseva, Marina & Slanzi, Debora & Poli, Irene, 2016. "A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices," Applied Energy, Elsevier, vol. 184(C), pages 1400-1410.
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