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Thermal performance and energy cost of Korean multispan greenhouse energy-saving screens

Author

Listed:
  • Rabiu, Anis
  • Adesanya, Misbaudeen Aderemi
  • Na, Wook-Ho
  • Ogunlowo, Qazeem O.
  • Akpenpuun, Timothy D.
  • Kim, Hyeon Tae
  • Lee, Hyun-Woo

Abstract

Protected agricultural system such as a greenhouse cultivation is increasingly replacing traditional farming systems. Nonetheless, high energy demand in greenhouse farming requires innovative technologies through the use of climate screens to ensure sustainable production. Thus, this study developed a novel methodology for examining the energy retention capacity and economic effectiveness of greenhouse climate screen materials using their thermophysical, radiometric and aerodynamic properties in TRNSYS software. The TRNSYS model was developed to determine the energy consumption, which was validated using a multi-span Venlo-type experimental greenhouse (Yeoju, South Korea). Further analyses on energy saving capacity of different screens and the equivalent energy costs were performed. The results from this research showed that among the fifteen investigated screens, the ensemble screen (M3) saved 34.09 kWh.m−2 of annual energy, equivalent to 60 % of the heating energy demand, and energy cost of 4490.26 Korean won. m−2. Further, the results revealed that the climate screens with multi-layer, thermoreflective, low longwave transmissivity, impermeable and aluminized strips or surface characteristics and features have a considerable impact on reducing greenhouse energy use and desirable for high energy-saving. This research has demonstrated that the techniques and methods utilised can investigate all the types of covering and thermal screens used in greenhouse.

Suggested Citation

  • Rabiu, Anis & Adesanya, Misbaudeen Aderemi & Na, Wook-Ho & Ogunlowo, Qazeem O. & Akpenpuun, Timothy D. & Kim, Hyeon Tae & Lee, Hyun-Woo, 2023. "Thermal performance and energy cost of Korean multispan greenhouse energy-saving screens," Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223029080
    DOI: 10.1016/j.energy.2023.129514
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    References listed on IDEAS

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    1. Iddio, E. & Wang, L. & Thomas, Y. & McMorrow, G. & Denzer, A., 2020. "Energy efficient operation and modeling for greenhouses: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    2. Yongtao Shen & Ruihua Wei & Lihong Xu, 2018. "Energy Consumption Prediction of a Greenhouse and Optimization of Daily Average Temperature," Energies, MDPI, vol. 11(1), pages 1-17, January.
    3. Hyung-Kweon Kim & Geum-Choon Kang & Jong-Pil Moon & Tae-Seok Lee & Sung-Sik Oh, 2018. "Estimation of Thermal Performance and Heat Loss in Plastic Greenhouses with and without Thermal Curtains," Energies, MDPI, vol. 11(3), pages 1-11, March.
    4. Adnan Rasheed & Wook Ho Na & Jong Won Lee & Hyeon Tae Kim & Hyun Woo Lee, 2019. "Optimization of Greenhouse Thermal Screens for Maximized Energy Conservation," Energies, MDPI, vol. 12(19), pages 1-20, September.
    5. Cuce, Erdem & Harjunowibowo, Dewanto & Cuce, Pinar Mert, 2016. "Renewable and sustainable energy saving strategies for greenhouse systems: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 34-59.
    6. António M. Raimundo & Nuno Baía Saraiva & Luisa Dias Pereira & Ana Cristina Rebelo, 2021. "Market-Oriented Cost-Effectiveness and Energy Analysis of Windows in Portugal," Energies, MDPI, vol. 14(13), pages 1-19, June.
    7. Baneshi, Mehdi & Gonome, Hiroki & Maruyama, Shigenao, 2020. "Wide-range spectral measurement of radiative properties of commercial greenhouse covering plastics and their impacts into the energy management in a greenhouse," Energy, Elsevier, vol. 210(C).
    8. Misbaudeen Aderemi Adesanya & Wook-Ho Na & Anis Rabiu & Qazeem Opeyemi Ogunlowo & Timothy Denen Akpenpuun & Adnan Rasheed & Yong-Cheol Yoon & Hyun-Woo Lee, 2022. "TRNSYS Simulation and Experimental Validation of Internal Temperature and Heating Demand in a Glass Greenhouse," Sustainability, MDPI, vol. 14(14), pages 1-30, July.
    9. Lin, Terry & Goldsworthy, Mark & Chavan, Sachin & Liang, Weiguang & Maier, Chelsea & Ghannoum, Oula & Cazzonelli, Christopher I. & Tissue, David T. & Lan, Yi-Chen & Sethuvenkatraman, Subbu & Lin, Han , 2022. "A novel cover material improves cooling energy and fertigation efficiency for glasshouse eggplant production," Energy, Elsevier, vol. 251(C).
    10. Yano, Akira & Cossu, Marco, 2019. "Energy sustainable greenhouse crop cultivation using photovoltaic technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 116-137.
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