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Energy efficient operation and modeling for greenhouses: A literature review

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  • Iddio, E.
  • Wang, L.
  • Thomas, Y.
  • McMorrow, G.
  • Denzer, A.

Abstract

With growing food demand worldwide, controlled environment agriculture is an important strategy for crop production year-round. One of the important types of controlled environment agriculture is greenhouses. Key indoor environmental parameters such as carbon dioxide, moisture, lighting, and temperature are required to be maintained for favorable crop growth in greenhouses. Due to lightweight construction and inefficient operation, greenhouses consume more fossil fuel energy in the operation of mechanical systems than other similar sized buildings and have larger carbon footprints. In fact, greenhouses are one of the most energy-intensive sectors of the agricultural industry. Energy consumption in greenhouses is influenced by mechanical systems, indoor environment, crop growth, and evapotranspiration. Therefore, energy simulations help analyze the complex thermal processes in greenhouse operation, and contribute to energy efficient greenhouse operation. This paper reviews existing strategies on energy efficient control operation and state-of-the-art energy simulation for greenhouses. It first discusses strategies for improving energy efficiency in greenhouse control operation by summarizing the studies on energy efficient operation strategies, the control of key greenhouse parameters, sensing network and monitoring systems, along with various control algorithms. Second, the review covers energy modeling of greenhouses by summarizing existing and developed approaches. Finally, this review identifies areas in which future research has the potential to reduce greenhouse energy consumption and carbon footprint.

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  • 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).
    • Handle: RePEc:eee:rensus:v:117:y:2020:i:c:s1364032119306884
    DOI: 10.1016/j.rser.2019.109480
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    References listed on IDEAS

    as
    1. Mahmoud, Tawfek & Dong, Z.Y. & Ma, Jin, 2018. "An advanced approach for optimal wind power generation prediction intervals by using self-adaptive evolutionary extreme learning machine," Renewable Energy, Elsevier, vol. 126(C), pages 254-269.
    2. Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
    3. Chen, Jiaoliao & Xu, Fang & Tan, Dapeng & Shen, Zheng & Zhang, Libin & Ai, Qinglin, 2015. "A control method for agricultural greenhouses heating based on computational fluid dynamics and energy prediction model," Applied Energy, Elsevier, vol. 141(C), pages 106-118.
    4. Egilmez, Gokhan & Tatari, Omer, 2012. "A dynamic modeling approach to highway sustainability: Strategies to reduce overall impact," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1086-1096.
    5. Si, Binghui & Tian, Zhichao & Jin, Xing & Zhou, Xin & Shi, Xing, 2019. "Ineffectiveness of optimization algorithms in building energy optimization and possible causes," Renewable Energy, Elsevier, vol. 134(C), pages 1295-1306.
    6. Farinaz Behrooz & Norman Mariun & Mohammad Hamiruce Marhaban & Mohd Amran Mohd Radzi & Abdul Rahman Ramli, 2018. "Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps," Energies, MDPI, vol. 11(3), pages 1-41, February.
    7. Xu, J. & Li, Y. & Wang, R.Z. & Liu, W. & Zhou, P., 2015. "Experimental performance of evaporative cooling pad systems in greenhouses in humid subtropical climates," Applied Energy, Elsevier, vol. 138(C), pages 291-301.
    8. Graamans, Luuk & Baeza, Esteban & van den Dobbelsteen, Andy & Tsafaras, Ilias & Stanghellini, Cecilia, 2018. "Plant factories versus greenhouses: Comparison of resource use efficiency," Agricultural Systems, Elsevier, vol. 160(C), pages 31-43.
    9. Montero, J.I. & Baeza, E. & Heuvelink, E. & Rieradevall, J. & Muñoz, P. & Ercilla, M. & Stanghellini, C., 2017. "Productivity of a building-integrated roof top greenhouse in a Mediterranean climate," Agricultural Systems, Elsevier, vol. 158(C), pages 14-22.
    10. Walters, Jeffrey P. & Archer, David W. & Sassenrath, Gretchen F. & Hendrickson, John R. & Hanson, Jon D. & Halloran, John M. & Vadas, Peter & Alarcon, Vladimir J., 2016. "Exploring agricultural production systems and their fundamental components with system dynamics modelling," Ecological Modelling, Elsevier, vol. 333(C), pages 51-65.
    11. Van Beveren, P.J.M. & Bontsema, J. & Van Straten, G. & Van Henten, E.J., 2015. "Minimal heating and cooling in a modern rose greenhouse," Applied Energy, Elsevier, vol. 137(C), pages 97-109.
    12. Golzar, Farzin & Heeren, Niko & Hellweg, Stefanie & Roshandel, Ramin, 2018. "A novel integrated framework to evaluate greenhouse energy demand and crop yield production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 487-501.
    13. Jeon, Chanwoong & Shin, Juneseuk, 2014. "Long-term renewable energy technology valuation using system dynamics and Monte Carlo simulation: Photovoltaic technology case," Energy, Elsevier, vol. 66(C), pages 447-457.
    14. Wang, Xiaozhong & Liu, Bin & Wu, Gang & Sun, Yixiang & Guo, Xisheng & Jin, Zhenghui & Xu, Weining & Zhao, Yongzhi & Zhang, Fusuo & Zou, Chunqin & Chen, Xinping, 2018. "Environmental costs and mitigation potential in plastic-greenhouse pepper production system in China: A life cycle assessment," Agricultural Systems, Elsevier, vol. 167(C), pages 186-194.
    15. Vadiee, Amir & Martin, Viktoria, 2014. "Energy management strategies for commercial greenhouses," Applied Energy, Elsevier, vol. 114(C), pages 880-888.
    16. Aslani, Alireza & Helo, Petri & Naaranoja, Marja, 2014. "Role of renewable energy policies in energy dependency in Finland: System dynamics approach," Applied Energy, Elsevier, vol. 113(C), pages 758-765.
    17. Ben G. Li & Yibei Liu, 2018. "The Production Life Cycle," Scandinavian Journal of Economics, Wiley Blackwell, vol. 120(4), pages 1139-1170, October.
    18. Katsoulas, N. & Sapounas, A. & De Zwart, F. & Dieleman, J.A. & Stanghellini, C., 2015. "Reducing ventilation requirements in semi-closed greenhouses increases water use efficiency," Agricultural Water Management, Elsevier, vol. 156(C), pages 90-99.
    19. Dounis, A.I. & Caraiscos, C., 2009. "Advanced control systems engineering for energy and comfort management in a building environment--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1246-1261, August.
    20. Edgar Hertwich, 2014. "Understanding the Climate Mitigation Benefits of Product Systems: Comment on “Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation…”," Journal of Industrial Ecology, Yale University, vol. 18(3), pages 464-465, May.
    21. Afroz, Zakia & Shafiullah, GM & Urmee, Tania & Higgins, Gary, 2018. "Modeling techniques used in building HVAC control systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 64-84.
    22. Giuseppina Nicolosi & Roberto Volpe & Antonio Messineo, 2017. "An Innovative Adaptive Control System to Regulate Microclimatic Conditions in a Greenhouse," Energies, MDPI, vol. 10(5), pages 1-17, May.
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    8. 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).
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    14. Luo, X.J. & Oyedele, Lukumon O. & Ajayi, Anuoluwapo O. & Akinade, Olugbenga O. & Owolabi, Hakeem A. & Ahmed, Ashraf, 2020. "Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
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    17. Hu, Guoqing & You, Fengqi, 2022. "Renewable energy-powered semi-closed greenhouse for sustainable crop production using model predictive control and machine learning for energy management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

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