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Unlock city-scale energy saving and peak load shaving potential of green roofs by GIS-informed urban building energy modelling

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  • Wang, Meng
  • Yu, Hang
  • Liu, Yupeng
  • Lin, Jianyi
  • Zhong, Xianzhun
  • Tang, Yin
  • Guo, Haijin
  • Jing, Rui

Abstract

Urban green roofs have emerged as a significant trend in urban architecture worldwide, offering numerous benefits, including enhanced energy performance, improved urban microclimate, and public health. This study proposes a holistic framework for assessing the green roofs' energy-saving potential at the city scale, achieved by scaling up building-scale energy simulations to city-scale energy demands. Firstly, massive building information is collected using Geometric Information System (GIS) technologies. Subsequently, prototype buildings are generated to accurately represent the geometric characteristics of buildings at the city scale. Building performance simulation is further conducted considering three types of plants on roofs. A case study in Xiamen, China, demonstrates the effectiveness of the proposed framework to efficiently quantify the city-scale energy-saving potential of green roofs. By implementing green roofs in Xiamen, energy savings of 1.62–1.83% and peak load shaving of 1.10–1.63% can be achieved for the whole city. Overall, the proposed framework has the potential for widespread application in other cities with minor adjustments to accommodate variations in climate and building parameters.

Suggested Citation

  • Wang, Meng & Yu, Hang & Liu, Yupeng & Lin, Jianyi & Zhong, Xianzhun & Tang, Yin & Guo, Haijin & Jing, Rui, 2024. "Unlock city-scale energy saving and peak load shaving potential of green roofs by GIS-informed urban building energy modelling," Applied Energy, Elsevier, vol. 366(C).
    • Handle: RePEc:eee:appene:v:366:y:2024:i:c:s0306261924006986
    DOI: 10.1016/j.apenergy.2024.123315
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    References listed on IDEAS

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    1. Jing, Rui & Liu, Jiahui & Zhang, Haoran & Zhong, Fenglin & Liu, Yupeng & Lin, Jianyi, 2022. "Unlock the hidden potential of urban rooftop agrivoltaics energy-food-nexus," Energy, Elsevier, vol. 256(C).
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    4. Zheng, Yuanfan & Weng, Qihao, 2019. "Modeling the effect of climate change on building energy demand in Los Angeles county by using a GIS-based high spatial- and temporal-resolution approach," Energy, Elsevier, vol. 176(C), pages 641-655.
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    Cited by:

    1. Giuseppe Aruta & Fabrizio Ascione & Romano Fistola & Teresa Iovane, 2024. "The City as a Power Hub for Boosting Renewable Energy Communities: A Case Study in Naples," Sustainability, MDPI, vol. 16(18), pages 1-22, September.
    2. Yuanfan Zheng & Liang Chen & Haipeng Zhao, 2024. "Assessing Building Energy Savings and the Greenhouse Gas Mitigation Potential of Green Roofs in Shanghai Using a GIS-Based Approach," Sustainability, MDPI, vol. 16(18), pages 1-23, September.
    3. 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.

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