IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v159y2015icp509-519.html
   My bibliography  Save this article

Optimal control of greenhouse climate using minimal energy and grower defined bounds

Author

Listed:
  • van Beveren, P.J.M.
  • Bontsema, J.
  • van Straten, G.
  • van Henten, E.J.

Abstract

Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO2 concentration, and the maximum amount of CO2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO2 were used as control variables.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:159:y:2015:i:c:p:509-519
    DOI: 10.1016/j.apenergy.2015.09.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191501082X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2015.09.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
    3. Ouammi, Ahmed, 2021. "Model predictive control for optimal energy management of connected cluster of microgrids with net zero energy multi-greenhouses," Energy, Elsevier, vol. 234(C).
    4. Nadal, Ana & Llorach-Massana, Pere & Cuerva, Eva & López-Capel, Elisa & Montero, Juan Ignacio & Josa, Alejandro & Rieradevall, Joan & Royapoor, Mohammad, 2017. "Building-integrated rooftop greenhouses: An energy and environmental assessment in the mediterranean context," Applied Energy, Elsevier, vol. 187(C), pages 338-351.
    5. Sun, Weituo & Wei, Xiaoming & Zhou, Baochang & Lu, Chungui & Guo, Wenzhong, 2022. "Greenhouse heating by energy transfer between greenhouses: System design and implementation," Applied Energy, Elsevier, vol. 325(C).
    6. Muñoz-Liesa, Joan & Royapoor, Mohammad & López-Capel, Elisa & Cuerva, Eva & Rufí-Salís, Martí & Gassó-Domingo, Santiago & Josa, Alejandro, 2020. "Quantifying energy symbiosis of building-integrated agriculture in a mediterranean rooftop greenhouse," Renewable Energy, Elsevier, vol. 156(C), pages 696-709.
    7. Zhang, Guanshan & Ding, Xiaoming & Li, Tianhua & Pu, Wenyang & Lou, Wei & Hou, Jialin, 2020. "Dynamic energy balance model of a glass greenhouse: An experimental validation and solar energy analysis," Energy, Elsevier, vol. 198(C).
    8. Blaud, Pierre Clement & Haurant, Pierrick & Chevrel, Philippe & Claveau, Fabien & Mouraud, Anthony, 2023. "Multi-flow optimization of a greenhouse system: A hierarchical control approach," Applied Energy, Elsevier, vol. 351(C).
    9. Germán Díaz-Flórez & Jorge Mendiola-Santibañez & Luis Solís-Sánchez & Domingo Gómez-Meléndez & Ivan Terol-Villalobos & Hector Gutiérrez-Bañuelos & Ma. Araiza-Esquivel & Gustavo Espinoza-García & Juan , 2019. "Modeling and Simulation of Temperature and Relative Humidity Inside a Growth Chamber," Energies, MDPI, vol. 12(21), pages 1-22, October.
    10. 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.
    11. Tahery, Danial & Roshandel, Ramin & Avami, Akram, 2021. "An integrated dynamic model for evaluating the influence of ground to air heat transfer system on heating, cooling and CO2 supply in Greenhouses: Considering crop transpiration," Renewable Energy, Elsevier, vol. 173(C), pages 42-56.
    12. 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).
    13. Theodora Karanisa & Yasmine Achour & Ahmed Ouammi & Sami Sayadi, 2022. "Smart greenhouses as the path towards precision agriculture in the food-energy and water nexus: case study of Qatar," Environment Systems and Decisions, Springer, vol. 42(4), pages 521-546, December.
    14. Dafni Despoina Avgoustaki & George Xydis, 2020. "Plant factories in the water-food-energy Nexus era: a systematic bibliographical review," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(2), pages 253-268, April.
    15. Katzin, David & van Henten, Eldert J. & van Mourik, Simon, 2022. "Process-based greenhouse climate models: Genealogy, current status, and future directions," Agricultural Systems, Elsevier, vol. 198(C).
    16. Katzin, David & Marcelis, Leo F.M. & van Mourik, Simon, 2021. "Energy savings in greenhouses by transition from high-pressure sodium to LED lighting," Applied Energy, Elsevier, vol. 281(C).
    17. 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).
    18. Wenfei Guan & Wenzhong Guo & Fan Chen & Xiaobei Han & Haiguang Wang & Weituo Sun & Qian Zhao & Dongdong Jia & Xiaoming Wei & Qingzhen Zhu, 2024. "Multi-Span Greenhouse Energy Saving by External Insulation: System Design and Implementation," Agriculture, MDPI, vol. 14(2), pages 1-15, February.
    19. Drottberger, Annie & Zhang, Yizhi & Yong, Jean Wan Hong & Dubois, Marie-Claude, 2023. "Urban farming with rooftop greenhouses: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    20. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barkat Rabbi & Zhong-Hua Chen & Subbu Sethuvenkatraman, 2019. "Protected Cropping in Warm Climates: A Review of Humidity Control and Cooling Methods," Energies, MDPI, vol. 12(14), pages 1-24, July.
    2. Elham Bolandnazar & Hassan Sadrnia & Abbas Rohani & Francesco Marinello & Morteza Taki, 2023. "Application of Artificial Intelligence for Modeling the Internal Environment Condition of Polyethylene Greenhouses," Agriculture, MDPI, vol. 13(8), pages 1-16, August.
    3. Zhang, Guanshan & Ding, Xiaoming & Li, Tianhua & Pu, Wenyang & Lou, Wei & Hou, Jialin, 2020. "Dynamic energy balance model of a glass greenhouse: An experimental validation and solar energy analysis," Energy, Elsevier, vol. 198(C).
    4. Katzin, David & van Henten, Eldert J. & van Mourik, Simon, 2022. "Process-based greenhouse climate models: Genealogy, current status, and future directions," Agricultural Systems, Elsevier, vol. 198(C).
    5. Achour, Yasmine & Ouammi, Ahmed & Zejli, Driss, 2021. "Technological progresses in modern sustainable greenhouses cultivation as the path towards precision agriculture," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    6. Xue-Bo Jin & Wei-Zhen Zheng & Jian-Lei Kong & Xiao-Yi Wang & Min Zuo & Qing-Chuan Zhang & Seng Lin, 2021. "Deep-Learning Temporal Predictor via Bidirectional Self-Attentive Encoder–Decoder Framework for IOT-Based Environmental Sensing in Intelligent Greenhouse," Agriculture, MDPI, vol. 11(8), pages 1-25, August.
    7. 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.
    8. 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.
    9. Tahery, Danial & Roshandel, Ramin & Avami, Akram, 2021. "An integrated dynamic model for evaluating the influence of ground to air heat transfer system on heating, cooling and CO2 supply in Greenhouses: Considering crop transpiration," Renewable Energy, Elsevier, vol. 173(C), pages 42-56.
    10. 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).
    11. Lihan Chen & Lihong Xu & Ruihua Wei, 2023. "Energy-Saving Control Algorithm of Venlo Greenhouse Skylight and Wet Curtain Fan Based on Reinforcement Learning with Soft Action Mask," Agriculture, MDPI, vol. 13(1), pages 1-16, January.
    12. Blaud, Pierre Clement & Haurant, Pierrick & Chevrel, Philippe & Claveau, Fabien & Mouraud, Anthony, 2023. "Multi-flow optimization of a greenhouse system: A hierarchical control approach," Applied Energy, Elsevier, vol. 351(C).
    13. Hassanien, Reda Hassanien Emam & Li, Ming & Dong Lin, Wei, 2016. "Advanced applications of solar energy in agricultural greenhouses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 989-1001.
    14. 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).
    15. Katzin, David & Marcelis, Leo F.M. & van Mourik, Simon, 2021. "Energy savings in greenhouses by transition from high-pressure sodium to LED lighting," Applied Energy, Elsevier, vol. 281(C).
    16. 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).
    17. Engler, Nicholas & Krarti, Moncef, 2021. "Review of energy efficiency in controlled environment agriculture," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    18. Sun, Weituo & Wei, Xiaoming & Zhou, Baochang & Lu, Chungui & Guo, Wenzhong, 2022. "Greenhouse heating by energy transfer between greenhouses: System design and implementation," Applied Energy, Elsevier, vol. 325(C).
    19. Mahmood, Farhat & Govindan, Rajesh & Bermak, Amine & Yang, David & Al-Ansari, Tareq, 2023. "Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment," Applied Energy, Elsevier, vol. 343(C).
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:159:y:2015:i:c:p:509-519. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.