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Unlock the hidden potential of urban rooftop agrivoltaics energy-food-nexus

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  • Jing, Rui
  • Liu, Jiahui
  • Zhang, Haoran
  • Zhong, Fenglin
  • Liu, Yupeng
  • Lin, Jianyi

Abstract

Climate change and population growth pose fundamental challenges to urban food and energy resilience and intensify the land-use competition. By co-locating photovoltaic with vegetation on urban rooftops offers an Agrivoltaics solution to achieve sustainable cities with clean energy supply and ‘zero food mile’ vegetable production. However, the first and foremost question is on how much food and energy can the Agrivoltaics nexus produce. This study proposes a multi-disciplinary assessment framework to unlock the potential of urban rooftop Agrivoltaics by integrating Geographic Information System (GIS), biogeochemical simulation, and solar power simulation. A case study in Shenzhen, China, reveals that bringing the Agrivoltaics (e.g., planting lettuce under photovoltaic panels) on the 854,000 number of rooftops (i.e., 105 km2 identified) can yield 9.84 × 105 tonnes/year lettuce to fulfil the whole city's demand. Meanwhile, the solar PV installed capacity is 2106 MW on average with 1899 GWh/year generated electricity, which is equivalent to 0.2% of the whole city's electricity demand. Besides, 4.11 × 106 tonnes/year extra freshwater is needed for irrigation. Overall, the Agrivoltaics indicates greater contribution to the Sustainable Development Goals (SDGs) and the proposed integrated framework provides an overall picture and assessment tool to explore the urban Agrivoltaics as a key multifunctional land-use mechanism for urban sustainability.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:256:y:2022:i:c:s0360544222015298
    DOI: 10.1016/j.energy.2022.124626
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    Cited by:

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    3. Liu, Jiang & Wu, Qifeng & Lin, Zhipeng & Shi, Huijie & Wen, Shaoyang & Wu, Qiaoyu & Zhang, Junxue & Peng, Changhai, 2023. "A novel approach for assessing rooftop-and-facade solar photovoltaic potential in rural areas using three-dimensional (3D) building models constructed with GIS," Energy, Elsevier, vol. 282(C).
    4. Ren, Haoshan & Sun, Yongjun & Norman Tse, Chung Fai & Fan, Cheng, 2023. "Optimal packing and planning for large-scale distributed rooftop photovoltaic systems under complex shading effects and rooftop availabilities," Energy, Elsevier, vol. 274(C).

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