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Energy performance and climate control in mechanically ventilated greenhouses: A dynamic modelling-based assessment and investigation

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  • Costantino, Andrea
  • Comba, Lorenzo
  • Sicardi, Giacomo
  • Bariani, Mauro
  • Fabrizio, Enrico

Abstract

Controlled environment agriculture in greenhouse is a promising solution for meeting the increasing food demand of world population. The accurate control of the indoor environmental conditions proper of greenhouses enhances high crop productivity but, contemporarily, it entails considerable energy consumption due to the adoption of mechanical systems. This work presents a new modelling approach for estimating the energy consumption for climate control of mechanically ventilated greenhouses. The novelty of the proposed energy model lies in its integrated approach in simulating the greenhouse dynamics, considering the dynamic thermal and hygric behaviour of the building and the dynamic response of the cultivated crops to the variation of the solar radiation. The presented model simulates the operation of the systems and the energy performance, considering also the variable angular speed fans that are a new promising energy-efficient technology for this productive sector. The main outputs of the model are the hourly thermal and electrical energy use for climate control and the main indoor environmental conditions. The presented modelling approach was validated against a dataset acquired in a case study of a new fully mechanically controlled greenhouse during a long-term monitoring campaign. The present work contributes to increase the knowledge about the dynamics and the energy consumption of greenhouses, and it can be a valuable decision support tool for industry, farmers, and researchers to properly address an energy efficiency optimisation in mechanically ventilated greenhouses to reach the overall objective of decreasing the rising energy consumption of the agricultural sector.

Suggested Citation

  • Costantino, Andrea & Comba, Lorenzo & Sicardi, Giacomo & Bariani, Mauro & Fabrizio, Enrico, 2021. "Energy performance and climate control in mechanically ventilated greenhouses: A dynamic modelling-based assessment and investigation," Applied Energy, Elsevier, vol. 288(C).
    • Handle: RePEc:eee:appene:v:288:y:2021:i:c:s0306261921001288
    DOI: 10.1016/j.apenergy.2021.116583
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    References listed on IDEAS

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    2. Zhang, Menghang & Yan, Tingxiang & Wang, Wei & Jia, Xuexiu & Wang, Jin & Klemeš, Jiří Jaromír, 2022. "Energy-saving design and control strategy towards modern sustainable greenhouse: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    3. Chul-sung Lee & Hyungjin Shin & Changi Park & Mi-Lan Park & Young Choi, 2023. "Economic Feasibility Analysis of Greenhouse–Fuel Cell Convergence Systems," Sustainability, MDPI, vol. 16(1), pages 1-14, December.
    4. Jin, Yang & Jiang, Wei & Han, Yang & Nan, Songyu & Liu, Gongliang & Guo, Wei & Zhang, Kuan & Li, Qing & Li, Dong, 2024. "Comprehensive optimization of shading and electrical performance of roof-mounted photovoltaic system of Venlo-type greenhouse in the severe cold region," Energy, Elsevier, vol. 296(C).
    5. Lin, Dong & Zhang, Lijun & Xia, Xiaohua, 2021. "Model predictive control of a Venlo-type greenhouse system considering electrical energy, water and carbon dioxide consumption," Applied Energy, Elsevier, vol. 298(C).
    6. Hu, Guoqing & You, Fengqi, 2023. "An AI framework integrating physics-informed neural network with predictive control for energy-efficient food production in the built environment," Applied Energy, Elsevier, vol. 348(C).
    7. Shekaina Justin & Wafaa Saleh & Maha M. A. Lashin & Hind Mohammed Albalawi, 2023. "Modeling of Artificial Intelligence-Based Automated Climate Control with Energy Consumption Using Optimal Ensemble Learning on a Pixel Non-Uniformity Metro System," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    8. Leandra Vanbaelinghem & Andrea Costantino & Florian Grassauer & Nathan Pelletier, 2024. "Alternative Heating, Ventilation, and Air Conditioning (HVAC) System Considerations for Reducing Energy Use and Emissions in Egg Industries in Temperate and Continental Climates: A Systematic Review o," Sustainability, MDPI, vol. 16(12), pages 1-35, June.
    9. Piotr Michalak, 2022. "Thermal Network Model for an Assessment of Summer Indoor Comfort in a Naturally Ventilated Residential Building," Energies, MDPI, vol. 15(10), pages 1-19, May.
    10. Chen, Wei-Han & Mattson, Neil S. & You, Fengqi, 2022. "Intelligent control and energy optimization in controlled environment agriculture via nonlinear model predictive control of semi-closed greenhouse," Applied Energy, Elsevier, vol. 320(C).
    11. Piotr Michalak, 2023. "Simulation and Experimental Study on the Use of Ventilation Air for Space Heating of a Room in a Low-Energy Building," Energies, MDPI, vol. 16(8), pages 1-17, April.
    12. Costantino, Andrea & Comba, Lorenzo & Cornale, Paolo & Fabrizio, Enrico, 2022. "Energy impact of climate control in pig farming: Dynamic simulation and experimental validation," Applied Energy, Elsevier, vol. 309(C).
    13. Abdelouhab Labihi & Paul Byrne & Amina Meslem & Florence Collet & Sylvie Prétot, 2023. "Heat Recovery Potential in a Semi-Closed Greenhouse for Tomato Cultivation," Clean Technol., MDPI, vol. 5(4), pages 1-27, September.
    14. Piotr Michalak, 2022. "Thermal—Airflow Coupling in Hourly Energy Simulation of a Building with Natural Stack Ventilation," Energies, MDPI, vol. 15(11), pages 1-18, June.
    15. Piotr Michalak, 2022. "Impact of Air Density Variation on a Simulated Earth-to-Air Heat Exchanger’s Performance," Energies, MDPI, vol. 15(9), pages 1-24, April.

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