IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v228y2024ics0960148124006505.html
   My bibliography  Save this article

Optimized model predictive control for solar assisted earth air heat exchanger system in greenhouse

Author

Listed:
  • Qi, Di
  • Zhang, Kunlun
  • Zhao, Chuangyao
  • Li, Ang
  • Song, Bingye
  • Li, Angui

Abstract

Agricultural greenhouses play a crucial role in addressing the threat of climate change to agricultural systems. The greenhouse systems control exhibits nonlinear characteristics and large lag, both affecting the regulation of the greenhouse thermal environment. In this paper, a control strategy was designed to set the dynamic reference value of the control objective of the greenhouse model, considering factors such as solar radiation and the heating capacity of water body. A complete greenhouse model was developed using TRNSYS, and then the model predictive control building and optimization were implemented through MATLAB. The control effects of traditional proportional-integral-differentiation control, initial model predictive control, and optimized model predictive control were compared. The results showed that the regulation of greenhouse temperature was improved by 10.6 % in the coldest mouth compared to the conventional proportional-integral-differentiation control by the optimized model predictive control. During a typical cold month, the violation of constraints was reduced by 29.7 % by dynamically setting the target of the greenhouse with the optimized model predictive control. The performance of greenhouse climate control is enhanced by the proposed optimized model predictive control method, ensuring a stable regulation of the crop growth environment.

Suggested Citation

  • Qi, Di & Zhang, Kunlun & Zhao, Chuangyao & Li, Ang & Song, Bingye & Li, Angui, 2024. "Optimized model predictive control for solar assisted earth air heat exchanger system in greenhouse," Renewable Energy, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:renene:v:228:y:2024:i:c:s0960148124006505
    DOI: 10.1016/j.renene.2024.120582
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124006505
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.120582?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. Ceusters, Glenn & Rodríguez, Román Cantú & García, Alberte Bouso & Franke, Rüdiger & Deconinck, Geert & Helsen, Lieve & Nowé, Ann & Messagie, Maarten & Camargo, Luis Ramirez, 2021. "Model-predictive control and reinforcement learning in multi-energy system case studies," Applied Energy, Elsevier, vol. 303(C).
    2. 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).
    3. Yunsong Jia & Xiang Li, 2021. "Complex Event Processing Methods for Greenhouse Control," Agriculture, MDPI, vol. 11(9), pages 1-24, August.
    4. Fiorentini, Massimo & Wall, Josh & Ma, Zhenjun & Braslavsky, Julio H. & Cooper, Paul, 2017. "Hybrid model predictive control of a residential HVAC system with on-site thermal energy generation and storage," Applied Energy, Elsevier, vol. 187(C), pages 465-479.
    5. James Allen & Ari Halberstadt & John Powers & Nael H. El-Farra, 2020. "An Optimization-Based Supervisory Control and Coordination Approach for Solar-Load Balancing in Building Energy Management," Mathematics, MDPI, vol. 8(8), pages 1-28, July.
    6. Anifantis, Alexandros Sotirios & Colantoni, Andrea & Pascuzzi, Simone, 2017. "Thermal energy assessment of a small scale photovoltaic, hydrogen and geothermal stand-alone system for greenhouse heating," Renewable Energy, Elsevier, vol. 103(C), pages 115-127.
    7. Sigounis, Anna-Maria & Vallianos, Charalampos & Athienitis, Andreas, 2023. "Model predictive control of air-based building integrated PV/T systems for optimal HVAC integration," Renewable Energy, Elsevier, vol. 212(C), pages 655-668.
    8. Saberian, Ayad & Sajadiye, Seyed Majid, 2019. "The effect of dynamic solar heat load on the greenhouse microclimate using CFD simulation," Renewable Energy, Elsevier, vol. 138(C), pages 722-737.
    9. 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).
    10. 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).
    11. Liu, Zhengxuan & Sun, Pengchen & Xie, Mingjing & Zhou, Yuekuan & He, Yingdong & Zhang, Guoqiang & Chen, Dachuan & Li, Shuisheng & Yan, Zhongjun & Qin, Di, 2021. "Multivariant optimization and sensitivity analysis of an experimental vertical earth-to-air heat exchanger system integrating phase change material with Taguchi method," Renewable Energy, Elsevier, vol. 173(C), pages 401-414.
    12. Zhang, Liang & Xu, Peng & Mao, Jiachen & Tang, Xu & Li, Zhengwei & Shi, Jianguo, 2015. "A low cost seasonal solar soil heat storage system for greenhouse heating: Design and pilot study," Applied Energy, Elsevier, vol. 156(C), pages 213-222.
    13. Zou, Bin & Peng, Jinqing & Yin, Rongxin & Li, Houpei & Li, Sihui & Yan, Jinyue & Yang, Hongxing, 2022. "Capacity configuration of distributed photovoltaic and battery system for office buildings considering uncertainties," Applied Energy, Elsevier, vol. 319(C).
    Full references (including those not matched with items on IDEAS)

    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. Xu, Demin & Fei, Shuaipeng & Wang, Zhi & Zhu, Jinyu & Ma, Yuntao, 2024. "Optimum design of Chinese solar greenhouses for maximum energy availability," Energy, Elsevier, vol. 304(C).
    2. 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).
    3. Hu, Zehuan & Gao, Yuan & Sun, Luning & Mae, Masayuki & Imaizumi, Taiji, 2024. "Improved robust model predictive control for residential building air conditioning and photovoltaic power generation with battery energy storage system under weather forecast uncertainty," Applied Energy, Elsevier, vol. 371(C).
    4. Wu, Xiaoyang & Li, Yiming & Jiang, Lingling & Wang, Yang & Liu, Xingan & Li, Tianlai, 2023. "A systematic analysis of multiple structural parameters of Chinese solar greenhouse based on the thermal performance," Energy, Elsevier, vol. 273(C).
    5. 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.
    6. Villa-Arrieta, Manuel & Sumper, Andreas, 2018. "A model for an economic evaluation of energy systems using TRNSYS," Applied Energy, Elsevier, vol. 215(C), pages 765-777.
    7. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    8. Song, Xueyi & Yuan, Junjie & Yang, Chen & Deng, Gaofeng & Wang, Zhichao & Gao, Jubao, 2023. "Carbon dioxide separation performance evaluation of amine-based versus choline-based deep eutectic solvents," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    9. Yang, Shiyu & Wan, Man Pun & Ng, Bing Feng & Dubey, Swapnil & Henze, Gregor P. & Chen, Wanyu & Baskaran, Krishnamoorthy, 2020. "Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system," Applied Energy, Elsevier, vol. 257(C).
    10. Lork, Clement & Li, Wen-Tai & Qin, Yan & Zhou, Yuren & Yuen, Chau & Tushar, Wayes & Saha, Tapan K., 2020. "An uncertainty-aware deep reinforcement learning framework for residential air conditioning energy management," Applied Energy, Elsevier, vol. 276(C).
    11. Cui, Can & Zhang, Xin & Cai, Wenjian, 2020. "An energy-saving oriented air balancing method for demand controlled ventilation systems with branch and black-box model," Applied Energy, Elsevier, vol. 264(C).
    12. Gokhale, Gargya & Claessens, Bert & Develder, Chris, 2022. "Physics informed neural networks for control oriented thermal modeling of buildings," Applied Energy, Elsevier, vol. 314(C).
    13. 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).
    14. Artur Kraszkiewicz & Artur Przywara & Alexandros Sotirios Anifantis, 2020. "Impact of Ignition Technique on Pollutants Emission during the Combustion of Selected Solid Biofuels," Energies, MDPI, vol. 13(10), pages 1-13, May.
    15. Hu, Guoqing & You, Fengqi, 2024. "AI-enabled cyber-physical-biological systems for smart energy management and sustainable food production in a plant factory," Applied Energy, Elsevier, vol. 356(C).
    16. Omar Al-Ani & Sanjoy Das, 2022. "Reinforcement Learning: Theory and Applications in HEMS," Energies, MDPI, vol. 15(17), pages 1-37, September.
    17. Ilaria Zambon & Artemi Cerdà & Sirio Cividino & Luca Salvati, 2019. "The (Evolving) Vineyard’s Age Structure in the Valencian Community, Spain: A New Demographic Approach for Rural Development and Landscape Analysis," Agriculture, MDPI, vol. 9(3), pages 1-13, March.
    18. 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.
    19. Yang, Shiyu & Oliver Gao, H. & You, Fengqi, 2022. "Model predictive control for Demand- and Market-Responsive building energy management by leveraging active latent heat storage," Applied Energy, Elsevier, vol. 327(C).
    20. La Notte, Luca & Giordano, Lorena & Calabrò, Emanuele & Bedini, Roberto & Colla, Giuseppe & Puglisi, Giovanni & Reale, Andrea, 2020. "Hybrid and organic photovoltaics for greenhouse applications," Applied Energy, Elsevier, vol. 278(C).

    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:renene:v:228:y:2024:i:c:s0960148124006505. 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.journals.elsevier.com/renewable-energy .

    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.