IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v271y2023ics0360544223003602.html
   My bibliography  Save this article

Light environment simulation for a three-span plastic greenhouse based on greenhouse light environment simulation software

Author

Listed:
  • Bo, Yu
  • Zhang, Yu
  • Zheng, Kunpeng
  • Zhang, Jingxu
  • Wang, Xiaochan
  • Sun, Jin
  • Wang, Jian
  • Shu, Sheng
  • Wang, Yu
  • Guo, Shirong

Abstract

Light environment research in greenhouses is mainly focused on solar greenhouses with simple structures; the universality of illumination models is low to date. To study the light environments in various of greenhouses, Greenhouse Light Environment Simulation software has been developed based on the ray tracing and Monte Carlo methods. The function of the software is to analyse the light path of the sampling point. The software has been verified and applied in a three-span plastic greenhouse. The results show that the mean relative errors of each month and typical weather conditions are less than 10%. The mean relative error of the simulated mean at any point in the greenhouse is less than 4%. The solar radiation intensity in the greenhouse is mainly affected by the solar incidence angle, and the solar radiation uniformity is mainly affected by the roof shape; the average solar radiation intensity in the greenhouse is the highest in August (over 250 W/m2), and the lowest in December, (below 60 W/m2). When the greenhouse is oriented at 10° east by south, the total solar radiation is 2% higher and the uniformity of daily solar radiation is 0.8% higher than when the greenhouse is oriented to the south.

Suggested Citation

  • Bo, Yu & Zhang, Yu & Zheng, Kunpeng & Zhang, Jingxu & Wang, Xiaochan & Sun, Jin & Wang, Jian & Shu, Sheng & Wang, Yu & Guo, Shirong, 2023. "Light environment simulation for a three-span plastic greenhouse based on greenhouse light environment simulation software," Energy, Elsevier, vol. 271(C).
  • Handle: RePEc:eee:energy:v:271:y:2023:i:c:s0360544223003602
    DOI: 10.1016/j.energy.2023.126966
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223003602
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.126966?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. Petržala, J. & Kómar, L. & Kocifaj, M., 2017. "An advanced clear-sky model for more accurate irradiance and illuminance predictions for arbitrarily oriented inclined surfaces," Renewable Energy, Elsevier, vol. 106(C), pages 212-221.
    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. Cao, Fei & Li, Huashan & Yang, Tian & Li, Yan & Zhu, Tianyu & Zhao, Liang, 2017. "Evaluation of diffuse solar radiation models in Northern China: New model establishment and radiation sources comparison," Renewable Energy, Elsevier, vol. 103(C), pages 708-720.
    4. Singh, Gurpreet & Singh, Parm Pal & Lubana, Prit Pal Singh & Singh, K.G., 2006. "Formulation and validation of a mathematical model of the microclimate of a greenhouse," Renewable Energy, Elsevier, vol. 31(10), pages 1541-1560.
    5. Xiaodan Zhang & Jian Lv & Jianming Xie & Jihua Yu & Jing Zhang & Chaonan Tang & Jing Li & Zhixue He & Cheng Wang, 2020. "Solar Radiation Allocation and Spatial Distribution in Chinese Solar Greenhouses: Model Development and Application," Energies, MDPI, vol. 13(5), pages 1-27, March.
    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. Shuyao Dong & Md Shamim Ahamed & Chengwei Ma & Huiqing Guo, 2021. "A Time-Dependent Model for Predicting Thermal Environment of Mono-Slope Solar Greenhouses in Cold Regions," Energies, MDPI, vol. 14(18), pages 1-19, September.
    2. 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).
    3. Xiaodan Zhang & Jian Lv & Jianming Xie & Jihua Yu & Jing Zhang & Chaonan Tang & Jing Li & Zhixue He & Cheng Wang, 2020. "Solar Radiation Allocation and Spatial Distribution in Chinese Solar Greenhouses: Model Development and Application," Energies, MDPI, vol. 13(5), pages 1-27, March.
    4. Manzoni, Stefano & Katul, Gabriel & Fay, Philip A. & Polley, H. Wayne & Porporato, Amilcare, 2011. "Modeling the vegetation–atmosphere carbon dioxide and water vapor interactions along a controlled CO2 gradient," Ecological Modelling, Elsevier, vol. 222(3), pages 653-665.
    5. Xing, Jiangkuan & Wang, Haiou & Luo, Kun & Wang, Shuai & Bai, Yun & Fan, Jianren, 2019. "Predictive single-step kinetic model of biomass devolatilization for CFD applications: A comparison study of empirical correlations (EC), artificial neural networks (ANN) and random forest (RF)," Renewable Energy, Elsevier, vol. 136(C), pages 104-114.
    6. Akarslan, Emre & Hocaoglu, Fatih Onur & Edizkan, Rifat, 2018. "Novel short term solar irradiance forecasting models," Renewable Energy, Elsevier, vol. 123(C), pages 58-66.
    7. 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).
    8. Fan, Junliang & Wu, Lifeng & Zhang, Fucang & Cai, Huanjie & Ma, Xin & Bai, Hua, 2019. "Evaluation and development of empirical models for estimating daily and monthly mean daily diffuse horizontal solar radiation for different climatic regions of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 168-186.
    9. Rabiu, Anis & Adesanya, Misbaudeen Aderemi & Na, Wook-Ho & Ogunlowo, Qazeem O. & Akpenpuun, Timothy D. & Kim, Hyeon Tae & Lee, Hyun-Woo, 2023. "Thermal performance and energy cost of Korean multispan greenhouse energy-saving screens," Energy, Elsevier, vol. 285(C).
    10. Kolosz, B.W. & Athanasiadis, I.N. & Cadisch, G. & Dawson, T.P. & Giupponi, C. & Honzák, M. & Martinez-Lopez, J. & Marvuglia, A. & Mojtahed, V. & Ogutu, K.B.Z. & Van Delden, H. & Villa, F. & Balbi, S., 2018. "Conceptual advancement of socio-ecological modelling of ecosystem services for re-evaluating Brownfield land," Ecosystem Services, Elsevier, vol. 33(PA), pages 29-39.
    11. Nima Asgari & Matthew T. McDonald & Joshua M. Pearce, 2023. "Energy Modeling and Techno-Economic Feasibility Analysis of Greenhouses for Tomato Cultivation Utilizing the Waste Heat of Cryptocurrency Miners," Energies, MDPI, vol. 16(3), pages 1-42, January.
    12. Grillone, Benedetto & Danov, Stoyan & Sumper, Andreas & Cipriano, Jordi & Mor, Gerard, 2020. "A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    13. Sławomir Francik & Adrian Knapczyk & Artur Knapczyk & Renata Francik, 2020. "Decision Support System for the Production of Miscanthus and Willow Briquettes," Energies, MDPI, vol. 13(6), pages 1-24, March.
    14. Omar, M.N. & Taha, A.T. & Samak, A.A. & Keshek, M.H. & Gomaa, E.M. & Elsisi, S.F., 2021. "Simulation and validation model of cooling greenhouse by solar energy (P V) integrated with painting its cover and its effect on the cucumber production," Renewable Energy, Elsevier, vol. 172(C), pages 1154-1173.
    15. Sławomir Francik & Bogusława Łapczyńska-Kordon & Norbert Pedryc & Wojciech Szewczyk & Renata Francik & Zbigniew Ślipek, 2022. "The Use of Artificial Neural Networks for Determining Values of Selected Strength Parameters of Miscanthus × Giganteus," Sustainability, MDPI, vol. 14(5), pages 1-26, March.
    16. Mobtaker, Hassan Ghasemi & Ajabshirchi, Yahya & Ranjbar, Seyed Faramarz & Matloobi, Mansour, 2019. "Simulation of thermal performance of solar greenhouse in north-west of Iran: An experimental validation," Renewable Energy, Elsevier, vol. 135(C), pages 88-97.
    17. Liu, Peirong & Tong, Xiaojuan & Zhang, Jinsong & Meng, Ping & Li, Jun & Zhang, Jingru, 2020. "Estimation of half-hourly diffuse solar radiation over a mixed plantation in north China," Renewable Energy, Elsevier, vol. 149(C), pages 1360-1369.
    18. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparative analysis of diffuse solar radiation models based on sky-clearness index and sunshine period for humid-subtropical climatic region of India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 329-355.
    19. Aurora González-Vidal & José Mendoza-Bernal & Alfonso P. Ramallo & Miguel Ángel Zamora & Vicente Martínez & Antonio F. Skarmeta, 2022. "Smart Operation of Climatic Systems in a Greenhouse," Agriculture, MDPI, vol. 12(10), pages 1-18, October.
    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:energy:v:271:y:2023:i:c:s0360544223003602. 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/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.