A new optimisation methodology used to study the effect of cover properties on night-time greenhouse climate

This study presents an optimisation method for improving greenhouse design. The approach was based on the surrogate-based method and combines the use of energy balance simulation (ES) and computational fluid dynamics (CFD). The optimisation was applied to study the effects of cover properties on the night-time greenhouse climate. The ES model was verified by comparing its predictions with experimental data. The root mean square error (RMSE) values for internal temperature and humidity showed there was good agreement between the ES and experimental values. The optimisation process highlighted the importance of using a low emissivity and low transmissivity cover material. Under a clear sky the predicted temperature gain by using a high reflectance material compared to a regular one on an unheated greenhouse was approximately 4 °C. The relative humidity in the same scenario was reduced by almost 10%. Two ES parametric studies were carried out, the first showed the effects of different combinations of thermal radiation properties in term of temperature and humidity; the second showed the effects of the high reflectance material under different external conditions (equivalent sky temperature and soil heat flux (SHF)). This paper suggests that ES and CFD can be used together to provide a complete approach to greenhouse modelling.