Greenhouse Energy Management Methods Based On Energy Balance Equation And CFD

The modern greenhouse is the most advanced form of facilities agriculture.It can afford a conducive microclimate environment for crop growth and improve crop quality and yield quantity.However,modern greenhouses are energy-intensive production facilities,and heating in winter and cooling in summer are the main sources of energy consumption in greenhouses.Consequently,high energy consumption has become the main obstacle to the operation and agricultural production of greenhouses.Against this background,there is a need to conduct research on greenhouse energy management methods to find techniques and strategies for energy conservation and consumption reduction in greenhouses.Accordingly,to achieve the aforementioned objective,the work undertaken are:utilization of the energy balance model to forecast the greenhouse energy demand under winter conditions and applying the energy demand in the management of the greenhouse heat pump system to reduce energy consumption and achieve energy-savings;a 3-D transient CFD model was established to simulate the air velocity,temperature and absolute humidity inside a greenhouse under winter conditions and optimize the layout of the greenhouse heating system components to reduce energy consumption and achieve energy conservation;a 3-D CFD model was used to simulate and optimize the sawtooth greenhouse ventilation configuration under natural ventilation to achieve a better cooling effect in summer conditions.The main research contents are as follows:(1)The Invasive Weed Optimization(IWO)algorithm-optimized energy demand model was employed to predict the greenhouse energy demand under winter conditions and the energy demand was applied to manage the operation of the heat pump system to reduce energy consumption and achieve energy-savings.The energy balance equation was applied to construct the energy demand model of the Venlo-Type greenhouse.The energy model constituted numerous parameters and parameters that were difficult to determine,which mainly included transfer coefficients of the greenhouse glass,transfer coefficients of the thermal screen,leaf aerodynamic resistance of the crop,etc.were formulated as unknown model parameters.An optimization algorithm was employed to train the energy model to determine the optimal values of these unknown model parameters.To reduce the number of unknown model parameters in the model and alleviate the computational burden on the algorithm,the extended FAST(e FAST)analysis method was used to undertake sensitivity analysis on the unknown model parameters.The results showed that leaf aerodynamic resistance,density and specific heat of air were non-influential on the energy model output and were assigned a constant value in the model.The Particle Swarm Algorithm(PSO),Genetic Algorithm(GA),Shuffle Frog Leaping Algorithm(SFLA)and Invasive Weed Optimization(IWO)algorithm were used to train the energy model to determine the optimal values for the unknown model parameters.The PSO,GA,SFLA and IWO-optimized energy models were applied to predict energy demand for a 3-day nocturnal period to validate the optimized models.The validation results revealed that the predicted energy demand of the IWO-optimized model displayed a better fit to the actual energy consumption and showed the lowest standard error of 7.08%for the entire calibration period.In comparison,the predicted energy demand of the PSO-optimized model,SFLA-optimized model and GA-optimized model presented standard errors of 9.45%,12.45%and 14.44%,respectively,for the entire calibration period against the actual energy consumption.Therefore,the IWO-optimized model exhibited a higher prediction accuracy as compared to the other optimized energy models and was utilized to predict energy demand for a 7-day nocturnal and 7-day nychthemeron period that was employed to manage the operation of the air-source heat pump system.Estimated daily electrical power savings of142.29 k Wh to 720.05 k Wh was realized which was equivalent to 6.86%to 20.76%of the total estimated daily electrical power consumption of the heat pump system.(2)A 3-D transient CFD model was developed to simulate the air velocity,temperature and absolute humidity inside the greenhouse under winter conditions and optimize the layout design of the greenhouse heating system components according to temperature-relative humidity uniformity principles.A three-dimensional transient CFD model was employed to assess the thermo-environment,and simulate the airflow pattern and the dynamic distribution of temperature and humidity in the greenhouse.Validation of the numerical model against experimental data collected inside the greenhouse described a satisfactory agreement between measured and simulated values of air velocity,temperature and absolute humidity.The hourly mean absolute error(MAE)values ranged from 0.99℃ to 2.87℃ for temperature and from2.01 g/kg to 2.43 g/kg for absolute humidity.The hourly root mean square error(RMSE)values ranged from 1.10℃ to 2.88℃ for temperature and from 2.02 g/kg to 2.44 g/kg for absolute humidity.Statistical analysis results showed no significant difference in the measured and simulated datasets,pointing to the capability of the developed numerical model to accurately predict the microclimate inside the greenhouse.The simulation of the dynamic environment inside the greenhouse demonstrated that the airflow pattern shaped the distribution of temperature and absolute humidity inside the greenhouse and the periodicity in the air velocity profile was replicated in the temperature and absolute humidity profile.The periodicity in the air velocity profile was due to the orientation and installation locations of fan coil units(FCUs).Three alternative FCU layouts,Case A,Case B and Case C presenting potential power savings of 39.77%,48.33%and 45.80%,respectively,were investigated.In the diurnal scenario,analysis of the average temperature and relative humidity at the eastern,central and western sections of the greenhouse showed that all alternative FCU layouts were able to attain the desired temperature of 21℃ and relative humidity values above the recommended value of65%.Case B and Case C showed marginally higher temperature-relative humidity uniformity indices and lower temperature-relative humidity standard deviations as compared to Case A.It was also observed that Case B and Case C layouts showed satisfactory thermal and hygrometric distribution.Therefore,Case B and Case C alternative FCU layouts could be used for greenhouse heating under adequate solar radiation conditions and potential power savings of48.33%and 45.80%,respectively,could be attained thereby reducing energy consumption and achieving energy conservation.(3)Four different ventilation configuration schemes of the existing sawtooth greenhouse were designed and 3-D CFD simulations were undertaken to simulate the air velocity,temperature,relative humidity and ventilation in the different ventilation configuration schemes to maximize ventilation efficiency,improve cooling performance and conserve greenhouse cooling energy.A three-dimensional CFD model was employed to simulate the air velocity,temperature and relative humidity in the existing sawtooth greenhouse.The simulation results were satisfactorily validated against experimental data collected inside the greenhouse,computing temperature,relative humidity and air velocity MAE values of0.23℃,2.23%and 0.07 m/s,RMSE values of 0.26℃,2.63%and 0.09 m/s and Mean Absolute Percentage Error(MAPE)values of between 0.21%～1.21%,0.08%～6.15%and 8.48%,respectively.Four different ventilation configuration schemes of the sawtooth greenhouse were designed;SV=2.0m RV=1.5m,SV=2.0m RV=1.0m,SV=3.0m RV=1.5m,SV=3.0m RV=1.0m(SV:side ventilation RV:roof ventilation)and a greenhouse performance comparative analysis of the four different ventilation configurations and the tunnel greenhouse were undertaken.The results of the parametric analysis of the four different ventilation configurations under different ambient conditions revealed that the SV=3.0m RV=1.5m and SV=3.0m RV=1.0m vent schemes improved the air exchange capacity and enhanced microclimate homogeneity.However,velocity vector airflow fields for the different ambient conditions showed that the SV=3.0m RV=1.5m vent scheme allowed for the evacuation of more hot less dense air through the larger roof ventilation area.Thus,the SV=3.0m RV=1.5m vent scheme was selected as the sawtooth vent optimized design.In the comparative analysis of the vent optimized design and the tunnel greenhouse under different wind speeds,wind directions and ambient conditions,under 26.27℃ greenhouse exterior temperature,wind direction of 90oand the exterior wind speed increased from 0.43 m/s to 2.0 m/s,the ventilation rate in the vent optimized design increased by 0.16 m~3/s/m~2,while the ventilation rate in the tunnel design increased by only0.03 m~3/s/m~2.The difference in average greenhouse interior and exterior temperature per total ventilation area increased by 1.11℃/m~2in the vent optimized design,while this criterion in the tunnel design increased by 6.69℃/m~2.Further,under 34.73℃ greenhouse exterior temperature,wind direction of 90oand the exterior wind speed increased from 0.90 m/s to 2.1 m/s,the ventilation rate in the vent optimized design increased by 0.13 m~3/s/m~2,while the ventilation rate in the tunnel design increased by 0.03 m~3/s/m~2.The difference in average greenhouse interior and exterior temperature per total ventilation area in the vent optimized design increased by 0.59℃/m~2,while this criterion in the tunnel design increased by 11.5℃/m~2.Under26.27℃ and 34.73℃ outside temperature conditions,the difference between average interior and exterior temperature of the vent optimized design was small and less sensitive to the increase of exterior wind speed.Under 26.27℃ greenhouse external temperature,outside wind speed of 1.1 m/s and wind directions of 45°,90°and 180°,the ventilation rate was 0.062m~3/s/m~2,0.094 m~3/s/m~2 and 0.004 m~3/s/m~2,respectively,higher in the vent optimized design as compared to the tunnel design.The difference in average greenhouse interior and exterior temperature per total ventilation area was 14.17℃/m~2,7.82℃/m~2 and 22.31℃/m~2,respectively,lower in the vent optimized design in comparison to the tunnel design.Additionally,under 34.73℃ greenhouse exterior temperature,outside wind speed of 2.1 m/s and wind directions of 45°,90°and 225°,the ventilation rate was 0.11m~3/s/m~2,0.18m~3/s/m~2and 0.10 m~3/s/m~2,respectively,higher in the vent optimized design in comparison to the tunnel design.The difference in average greenhouse interior and exterior temperature per total ventilation area was 10.05℃/m~2,8.51℃/m~2 and 10.69℃/m~2,respectively,lower in the vent optimized design as compared to the tunnel design.The vent optimized sawtooth greenhouse design with its larger total ventilation index presented higher ventilation rates,superior cooling effect and better microclimate homogeneity.Therefore,ventilation configuration optimization of the sawtooth greenhouse under natural ventilation can be adopted to maximize the cooling effect under summer conditions in the Yangtze River Delta Region.