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Optimizing the 3D Distributed Climate inside Greenhouses Using Multi-Objective Optimization Algorithms and Computer Fluid Dynamics

Author

Listed:
  • Kangji Li

    (School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Wenping Xue

    (School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Hanping Mao

    (Institute of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Xu Chen

    (School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Hui Jiang

    (School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Gang Tan

    (Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY 82071, USA)

Abstract

As one of the major production facilities in agriculture, a greenhouse has many spatial distributed factors influencing crop growth and energy consumption, such as temperature field, air flow pattern, CO 2 concentration distribution, etc. By introducing a hybrid computational fluid dynamics–evolutionary algorithm (CFD-EA) method, this paper constructs a micro-climate model of greenhouse with main environmental parameters optimized. Considering environmental factors’ spatial influences together with energy usage simultaneously, the optimal solutions of control variables for crop growth are calculated. A commercial greenhouse located in east China is chosen for the method validation. Field experiments using temperature/velocity sensor matrix are carried out for CFD accuracy investigation. On this basis, the proposed optimization method is employed to search for the optimal control variables and parameters corresponding to the environmental Pareto frontier. By the proposed multi-objective scheme, we believe the method can provide set point basis for the design and regulation of large/medium-sized greenhouse production with high spatial resolution.

Suggested Citation

  • Kangji Li & Wenping Xue & Hanping Mao & Xu Chen & Hui Jiang & Gang Tan, 2019. "Optimizing the 3D Distributed Climate inside Greenhouses Using Multi-Objective Optimization Algorithms and Computer Fluid Dynamics," Energies, MDPI, vol. 12(15), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2873-:d:251825
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    References listed on IDEAS

    as
    1. van Beveren, P.J.M. & Bontsema, J. & van Straten, G. & van Henten, E.J., 2015. "Optimal control of greenhouse climate using minimal energy and grower defined bounds," Applied Energy, Elsevier, vol. 159(C), pages 509-519.
    2. Kangji Li & Wenping Xue & Guohai Liu, 2017. "Exploring the Environment/Energy Pareto Optimal Front of an Office Room Using Computational Fluid Dynamics-Based Interactive Optimization Method," Energies, MDPI, vol. 10(2), pages 1-15, February.
    3. Kangji Li & Lei Pan & Wenping Xue & Hui Jiang & Hanping Mao, 2017. "Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study," Energies, MDPI, vol. 10(2), pages 1-23, February.
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    Citations

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    Cited by:

    1. Kangji Li & Yanhui Mi & Wen Zheng, 2023. "An Optimal Control Method for Greenhouse Climate Management Considering Crop Growth’s Spatial Distribution and Energy Consumption," Energies, MDPI, vol. 16(9), pages 1-19, May.
    2. Morice R. O. Odhiambo & Adnan Abbas & Xiaochan Wang & Ehsan Elahi, 2020. "Thermo-Environmental Assessment of a Heated Venlo-Type Greenhouse in the Yangtze River Delta Region," Sustainability, MDPI, vol. 12(24), pages 1-34, December.
    3. Edwin Villagran & Rommel Leon & Andrea Rodriguez & Jorge Jaramillo, 2020. "3D Numerical Analysis of the Natural Ventilation Behavior in a Colombian Greenhouse Established in Warm Climate Conditions," Sustainability, MDPI, vol. 12(19), pages 1-27, October.
    4. Andrea Colantoni & Rodolfo Picchio & Alvaro Marucci & Elena Di Mattia & Valerio Cristofori & Fabio Recanatesi & Mauro Villarini & Danilo Monarca & Massimo Cecchini, 2020. "WP3—Innovation in Agriculture and Forestry Sector for Energetic Sustainability," Energies, MDPI, vol. 13(22), pages 1-7, November.
    5. Gloria Alexandra Ortiz Rocha & Maria Angelica Pichimata & Edwin Villagran, 2021. "Research on the Microclimate of Protected Agriculture Structures Using Numerical Simulation Tools: A Technical and Bibliometric Analysis as a Contribution to the Sustainability of Under-Cover Cropping," Sustainability, MDPI, vol. 13(18), pages 1-40, September.
    6. Subin Mattara Chalill & Snehaunshu Chowdhury & Ramanujam Karthikeyan, 2021. "Prediction of Key Crop Growth Parameters in a Commercial Greenhouse Using CFD Simulation and Experimental Verification in a Pilot Study," Agriculture, MDPI, vol. 11(7), pages 1-23, July.
    7. Di Qi & Chuangyao Zhao & Shixiong Li & Ran Chen & Angui Li, 2021. "Numerical Assessment of Earth to Air Heat Exchanger with Variable Humidity Conditions in Greenhouses," Energies, MDPI, vol. 14(5), pages 1-18, March.

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