Suitability analysis of assembled solar greenhouses in northwest China based on CFD

Authors

  • Xiao Wu College of Horticulture, Xinjiang Agricultural University, Urumqi 830052, China
  • Kai Jia College of Horticulture, Xinjiang Agricultural University, Urumqi 830052, China
  • Hongjun Xu College of Horticulture, Xinjiang Agricultural University, Urumqi 830052, China
  • Hong Li College of Horticulture, Xinjiang Agricultural University, Urumqi 830052, China
  • Weihua Zhang Xinjiang Donglu water control agricultural development Co., LTD, Kashi 844000, Xinjiang, China

DOI:

https://doi.org/10.25165/ijabe.v18i4.9289

Keywords:

assembled solar greenhouses, suitability analysis, northwest China, CFD

Abstract

Solar greenhouses in China have various structural forms. Compared with traditional solar greenhouses, the assembled solar greenhouse is not only simple in construction, convenient and fast in installation, but also improves the utilization efficiency of land and reduces the damage to the soil layer, cleverly achieving the transformation between plastic greenhouses and solar greenhouses. To determine the regions suitable for promoting modular solar greenhouses, this study adopts a combination of actual measurement and simulation methods. Based on Autodesk CFD software, a dynamic thermal model of modular solar greenhouse is established. Predictions and adaptive analysis of indoor temperature field changes at different regions are conducted in the consideration of boundary conditions such as outdoor air temperature, solar radiation on walls, and ground in various regions. The experimental results show that the change trends of measured and simulated values are basically consistent, indicating a high degree of model agreement. The maximum average deviation between the predicted and measured values of indoor air temperature is 1.53°C, the maximum average absolute deviation is 2.52°C, and the maximum root mean square is 3.74°C. The absolute coefficient ranges from 0.84 to 0.92, which indicates that the model can accurately reflect the temperature field distribution and heat exchange situation of the modular solar greenhouse at different times. This study provides a theoretical basis for the application and promotion of modular solar greenhouses and also offers a new research method for suitability simulation analysis of other types of solar greenhouses. Keywords: assembled solar greenhouses, suitability analysis, northwest China, CFD DOI: 10.25165/j.ijabe.20251804.9289 Citation: Wu X, Jia K, Xu H J, Li H, Zhang W H. Suitability analysis of assembled solar greenhouses in northwest China based on CFD. Int J Agric & Biol Eng, 2025; 18(4): 78–88.

References

Sydorovych O, Wossink A. The meaning of agricultural sustainability: Evidence from a conjoint choice survey. Agricultural Systems, 2008; 98(1): 10–20.

Li T L, Qi M F, Meng S D. Sixty years of facility horticulture development in China: Achievements and prospects. Acta Horticulturae Sinica, 2022; 49(10): 2119–2130. (in Chinese)

Ge J, Feng D P, Liu H R, Li W C, Zhu Y N. Characteristics and determining factors of spring-summer consecutive drought variations in Northwest China. Atmospheric Research, 2024; 304: 107361.

Zhou C J. Active heating technology and equipment for Chinese solar greenhouse. China Vegetables, 2023; 7: 7–19. (in Chinese)

Xu S X, Wang Y Y, Niu J H, Ma G Y. ‘Coal-to-electricity’project is ongoing in north China. Energy, 2020; 191: 116525.

Tafuni A, Giannotta A, Mersch M, Pantaleo A M, Amirante R, Markides C N, et al. Thermo-economic analysis of a low-cost greenhouse thermal solar plant with seasonal energy storage. Energy Conversion and Management, 2023; 288: 117123.

Liu K, Xu H J, Li H, Wu X, Sang S Y, Gao J. Analysis of Solar radiation changes in Chinese solar greenhouses with different roof structures based on a solar radiation model. Int J Agric & Biol Eng, 2022; 15(2): 221–229.

Bo Y, Zhang Y, Zheng K P, Zhang J X, Wang X C, Sun J, et al. Light environment simulation for a three-span plastic greenhouse based on greenhouse light environment simulation software. Energy, 2023; 271: 126966.

Sethi V P. On the selection of shape and orientation of a greenhouse: Thermal modeling and experimental validation. Solar Energy, 2009; 83(1): 21–38.

Soriano T, Montero J I, Sánchez-Guerrero M C, Medrano E. , Antón A, Hernández J, et al. A study of direct solar radiation transmission in asymmetrical multi-span greenhouses using scale models and simulation models. Biosystems Engineering, 2004; 88(2): 243–253.

Han F T, Chen C, Hu Q L, He Y P, Wei S, Li C Y. Modeling method of an active–passive ventilation wall with latent heat storage for evaluating its thermal properties in the solar greenhouse. Energy and Buildings, 2021; 238: 110840.

Xia T Y, He M, Li Y M, Sun D P, Sun Z P, Liu X A, et al. New design concept and thermal performance of a composite wall applied in solar greenhouse. Energy, 2024; 300: 131554.

Wu X, Li H, Sang S Y, He A H, Re Y M, Xu H J. Performance analysis and selection of chinese solar greenhouses in Xinjiang desert area. Agriculture, 2023; 13(2): 306.

Lian M. Influence of solar greenhouse structure parameters on indoor warm and light environment. Master dissertation, Shanxi: Shanxi Agricultural University, 2022; 71p. (in Chinese)

Zhang Y, Xu L H, Zhu X H, He B, Chen Y. Thermal environment model construction of Chinese solar greenhouse based on temperature–wave interaction theory. Energy and Buildings, 2023; 279: 112648.

Taki M, Ajabshirchi Y, Ranjbar S F, Rohani A, Matloobi M. Heat transfer and MLP neural network models to predict inside environment variables and energy lost in a semi-solar greenhouse. Energy and Buildings, 2016; 110: 314–329.

Ferreira P M, Faria E A, Ruano A E. Neural network models in greenhouse air temperature prediction. Neurocomputing, 2002; 43(1-4): 51–75.

Guerra R R, Vizziello A, Savazzi P, Goldoni E, Gamba P. Forecasting LoRaWAN RSSI using weather parameters: A comparative study of ARIMA, artificial intelligence and hybrid approaches. Computer Networks, 2024; 243: 110258.

Zou W D, Yao F X, Zhang B H, He C X, Guan Z X. Verification and predicting temperature and humidity in a solar greenhouse based on convex bidirectional extreme learning machine algorithm. Neurocomputing, 2017; 249: 72–85.

Li X J, Zhang X N, Wang Y W, Zhang K F, Chen Y F. Temperature prediction model for solar greenhouse based on improved BP neural network. Journal of Physics: Conference Series, 2020; 1639: 012036.

Yang Y X, Gao P, Sun Z T, Wang H Y, Lu M, Liu Y Y, et al. Multistep ahead prediction of temperature and humidity in solar greenhouse based on FAM-LSTM model. Computers and Electronics in Agriculture, 2023; 213: 108261.

Mao X J, Ren N, Dai P Y, Jin J, Wang B J, Kang R, et al. A variable weight combination prediction model for climate in a greenhouse based on BiGRU-Attention and LightGBM. Computers and Electronics in Agriculture, 2024; 219: 108818.

Huang L, Deng L H, Li A G, Gao R, Zhang L H, Lei W J. A novel approach for solar greenhouse air temperature and heating load prediction based on Laplace transform. Journal of Building Engineering, 2021; 44: 102682.

Mohammadi B, Ranjbar S F, Ajabshirchi Y. Application of dynamic model to predict some inside environment variables in a semi-solar greenhouse. Information processing in agriculture. 2018; 5(2): 279–288. doi: 10.1016/j.inpa.2018.01.001.

Mashonjowa E, Ronsse F, Milford J R, Pieters J G. Modelling the thermal performance of a naturally ventilated greenhouse in Zimbabwe using a dynamic greenhouse climate model. Solar Energy, 2013; 91: 381–393.

Zhao L, Lu L C, Liu H L, Li Y M, Sun Z P, Liu X A, et al. A onedimensional transient temperature prediction model for Chinese assembled solar greenhouses. Computers and Electronics in Agriculture, 2023; 215: 108450.

Zhang G X, Fu Z T, Yang M S, Liu X X, Dong Y H, Li X X. Nonlinear simulation for coupling modeling of air humidity and vent opening in Chinese solar greenhouse based on CFD. Computers and Electronics in Agriculture, 2019; 162: 337–347.

Mao C, Su Y P. CFD based heat transfer parameter identification of greenhouse and greenhouse climate prediction method. Thermal Science and Engineering Progress, 2024; 49: 102462.

Zhang X, Wang H L, Zou Z R, Wang S J. CFD and weighted entropy based simulation and optimisation of Chinese Solar Greenhouse temperature distribution. Biosystems Engineering, 2016; 142: 12–26.

He X L, Wang J, Guo S R, Zhang J, Wei B, Sun J, et al. Ventilation optimization of solar greenhouse with removable back walls based on CFD. Computers and Electronics in Agriculture, 2018; 149: 16–25.

Yu M H, Gao G L, Ding G D, Zhao Y Y, Sai K. A review on body temperature of plants. Chinese Journal of Ecology, 2015; 34(12): 3533–3541. (in Chinese)

Zhang M J, Zhao Y X. The Climate Suitability Zoning Method of the Solar Greenhouse in the Northern of China. Journal of Applied Meteorological Science, 2013; 24(3): 278–286. (in Chinese)

Downloads

Published

2025-08-21

How to Cite

Wu, X., Jia, K., Xu, H., Li, H., & Zhang, W. (2025). Suitability analysis of assembled solar greenhouses in northwest China based on CFD. International Journal of Agricultural and Biological Engineering, 18(4), 78–88. https://doi.org/10.25165/ijabe.v18i4.9289

Issue

Section

Animal, Plant and Facility Systems