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Multi-Stage Sensitivity Analysis of the Energy Demand for the Cooling of Grain Warehouses in Cold Regions of China

Author

Listed:
  • Hua Zhang

    (School of Architecture, Henan University of Technology, Zhengzhou 450001, China
    Henan Key Laboratory of Grain and Oil Storage Facility & Safety, HAUT, Zhengzhou 450001, China)

  • Junya Ye

    (School of Architecture, Henan University of Technology, Zhengzhou 450001, China)

  • Kunming Li

    (School of Architecture, Henan University of Technology, Zhengzhou 450001, China
    Henan Key Laboratory of Grain and Oil Storage Facility & Safety, HAUT, Zhengzhou 450001, China)

  • Shujie Niu

    (Department of General Layout Plan and Architecture, Henan University of Technology Design and Research Academy, Zhengzhou 450001, China)

  • Xiao Liu

    (State Key Laboratory of Subtropical Building and Urban Science, South China University of Technology, Guangzhou 510641, China
    School of Architecture, South China University of Technology, Guangzhou 510641, China
    Energy Saving Technology Research Institute, South China University of Technology, Guangzhou 510641, China
    Architectural Design & Research Institute Co., Ltd., South China University of Technology, Guangzhou 510641, China)

Abstract

The early design parameters exert a considerable influence on the cooling energy demand of a granary building in operation. In order to investigate the impact of various parameters on energy use, a grain warehouse energy model was constructed using the Ladybug + Honeybee tools on the Grasshopper platform. Three global energy sensitivity methods were used to analyze the model, and the sizes of the influential parameters were determined and ranked. The study uncovered that the cooling energy demand of the grain warehouse was primarily influenced by factors such as the cooling set-point temperature, roof solar absorptance, roof and exterior wall insulation thickness, window type, and orientation. On this basis, a local sensitivity analysis was conducted for the highly sensitive parameters to identify their influence trend and optimal design range. The results showed that the cooling energy demand of the grain warehouse increases faster as the cooling set-point temperature decreases, with the highest growth rate occurring at a temperature below 18 °C. Lower solar absorptance of the roof is conducive to reducing the cooling energy demand of the grain warehouse. When the thickness of the roof thermal insulation is less than 120 mm and the thickness of the external wall thermal insulation is less than 60 mm, energy use decreases more quickly with greater insulation thickness. It is advisable to use traditional or new windows with thermal insulation and shuttered windows. Furthermore, the optimal position of the long side of the granary was between 10° west and 10° east of north. This research could provide guidance for the energy-saving design and renovation of granary buildings in cold regions of China.

Suggested Citation

  • Hua Zhang & Junya Ye & Kunming Li & Shujie Niu & Xiao Liu, 2024. "Multi-Stage Sensitivity Analysis of the Energy Demand for the Cooling of Grain Warehouses in Cold Regions of China," Agriculture, MDPI, vol. 14(2), pages 1-15, January.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:2:p:193-:d:1327340
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    References listed on IDEAS

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    1. Natanian, Jonathan & Aleksandrowicz, Or & Auer, Thomas, 2019. "A parametric approach to optimizing urban form, energy balance and environmental quality: The case of Mediterranean districts," Applied Energy, Elsevier, vol. 254(C).
    2. Yuqing Zhang & Bin Li & Luca Caneparo & Qinglin Meng & Weihong Guo & Xiao Liu, 2023. "Physical Environment Study on Social Housing Stock in Italian Western Alps for Healthy and Sustainable Communities," Land, MDPI, vol. 12(7), pages 1-27, July.
    3. Naji, Sareh & Aye, Lu & Noguchi, Masa, 2021. "Sensitivity analysis on energy performance, thermal and visual discomfort of a prefabricated house in six climate zones in Australia," Applied Energy, Elsevier, vol. 298(C).
    4. Li, Hangxin & Wang, Shengwei & Cheung, Howard, 2018. "Sensitivity analysis of design parameters and optimal design for zero/low energy buildings in subtropical regions," Applied Energy, Elsevier, vol. 228(C), pages 1280-1291.
    5. Chen, Xi & Yang, Hongxing & Zhang, Weilong, 2018. "Simulation-based approach to optimize passively designed buildings: A case study on a typical architectural form in hot and humid climates," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P2), pages 1712-1725.
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