Indirect evaporative cooling(IEC)is a kind of high efficiency,energy-saving and environmental protection cooling technology,which has been widely used in data centers and other fields in recent years.In this paper,the...Indirect evaporative cooling(IEC)is a kind of high efficiency,energy-saving and environmental protection cooling technology,which has been widely used in data centers and other fields in recent years.In this paper,the optimized two-dimensional non-condensation state model of indirect evaporative cooling was proposed.Meanwhile the computer program was updated to solve the developed mathematical model under variable fresh air conditions.The optimized model was verified by the experimental data,and the maximum deviation was only 4.6%.Based on the modified model and the annual hourly meteorological parameters in Tianjin,China,it was analyzed the optimal heat transfer area of IEC used as fresh air pre-cooling unit under various air volumes to provide references for system design and equipment selection.Finally,taking an IEC-primary return air conditioning system of a gymnasium as an example,the hourly energy-saving effect of whole year was simulated by the developed IEC model.The simulation results showed that IEC could control the fresh air temperature below 27℃ and the moisture content below 18 g/kg throughout the year,and undertook 102.6% of the total fresh air cooling load.The findings are useful in future system optimization and design of IEC equipment.展开更多
Cooling tower is crucial equipment in the cool-end system of power plant and the natural draft counter-flow wet cooling tower(NDWCT)gets wide application.The artificial neural network(ANN)technique is becoming an effe...Cooling tower is crucial equipment in the cool-end system of power plant and the natural draft counter-flow wet cooling tower(NDWCT)gets wide application.The artificial neural network(ANN)technique is becoming an effective method for the thermal performance investigation of cooling towers.However,the neural network research on the energy efficiency performance of NDWCTs is not sufficient.In this paper,a novel approach was proposed to predict energy efficiency of various NDWCTs by using Back Propagation(BP)neural network:Firstly,based on 638 sets of field test data within 36 diverse NDWCTs in power plant,a three-layer BP neural network model with structure of 8-14-2 was developed.Then the cooling number and evaporation loss of water of different NDWCTs were predicted adopting the BP model.The results show that the established BP neural network has preferable prediction accuracy for the heat and mass transfer performance of NDWCT with various scales.The predicted cooling number and evaporative loss proportion of the testing cooling towers are in good agreement with experimental values with the mean relative error in the range of 2.11%–4.45%and 1.04%–4.52%,respectively.Furthermore,the energy efficiency of different NDWCTs can also be predicted by the proposed BP model with consideration of evaporation loss of water in cooling tower.At last,a novel method for energy efficiency prediction of various NDWCTs using the developed ANN model was proposed.The energy efficiency index(EEI)of different NDWCTs can be achieved readily without measuring the temperature as well as velocity of the outlet air.展开更多
High temperature and humidity can be controlled in greenhouses by using mechanical refrigeration cooling system such as air conditioner(AC)in warm and humid regions.This study aims to evaluate the techno-financial asp...High temperature and humidity can be controlled in greenhouses by using mechanical refrigeration cooling system such as air conditioner(AC)in warm and humid regions.This study aims to evaluate the techno-financial aspects of the AC-cooled greenhouse as compared to the evaporative cooled(EV-cooled)greenhouse in winter and summer seasons.Two quonset single-span prototype greenhouses were built in the Agriculture Experiment Station of Sultan Qaboos University,Oman,with dimensions of 6.0 m long and 3.0 m wide.The AC-cooled greenhouse was covered by a rockwool insulated polyethylene plastic sheet and light emitting diodes(LED)lights were used as a source of light,while the EV-cooled greenhouse was covered by a transparent polyethylene sheet and sunlight was used as light source.Three cultivars of high-value lettuce were grown for experimentation.To evaluate the technical efficiency of greenhouse performance,we conducted measures on land use efficiency(LUE),water use efficiency(WUE),gross water use efficiency(GWUE)and energy use efficiency(EUE).Financial analysis was conducted to compare the profitability of both greenhouses.The results showed that the LUE in winter were 10.10 and 14.50 kg/m^(2) for the AC-and EV-cooled greenhouses,respectively.However,the values reduced near to 6.80 kg/m^(2) in both greenhouses in summer.The WUE of the AC-cooled greenhouse was higher than that of the EV-cooled greenhouse by 3.8%in winter and 26.8%in summer.The GWUE was used to measure the total yield to the total greenhouse water consumption including irrigation and cooling water;it was higher in the AC-cooled greenhouse than in the EV-cooled greenhouse in both summer and winter seasons by almost 98.0%–99.4%.The EUE in the EV-cooled greenhouse was higher in both seasons.Financial analysis showed that in winter,gross return,net return and benefit-to-cost ratio were better in the EVcooled greenhouse,while in summer,those were higher in the AC-cooled greenhouse.The values of internal rate of return in the AC-and EV-cooled greenhouses were 63.4%and 129.3%,respectively.In both greenhouses,lettuce investment was highly sensitive to changes in price,yield and energy cost.The financial performance of the AC-cooled greenhouse in summer was better than that of the EV-cooled greenhouse and the pattern was opposite in winter.Finally,more studies on the optimum LED light intensity for any particular crop have to be conducted over different growing seasons in order to enhance the yield quantity and quality of crop.展开更多
基金This research is financially supported by the National Natural Science Foundation of China(No.51678385).
文摘Indirect evaporative cooling(IEC)is a kind of high efficiency,energy-saving and environmental protection cooling technology,which has been widely used in data centers and other fields in recent years.In this paper,the optimized two-dimensional non-condensation state model of indirect evaporative cooling was proposed.Meanwhile the computer program was updated to solve the developed mathematical model under variable fresh air conditions.The optimized model was verified by the experimental data,and the maximum deviation was only 4.6%.Based on the modified model and the annual hourly meteorological parameters in Tianjin,China,it was analyzed the optimal heat transfer area of IEC used as fresh air pre-cooling unit under various air volumes to provide references for system design and equipment selection.Finally,taking an IEC-primary return air conditioning system of a gymnasium as an example,the hourly energy-saving effect of whole year was simulated by the developed IEC model.The simulation results showed that IEC could control the fresh air temperature below 27℃ and the moisture content below 18 g/kg throughout the year,and undertook 102.6% of the total fresh air cooling load.The findings are useful in future system optimization and design of IEC equipment.
基金supported by the National Key R&D Program of China(Grant No.2017YFF0209803)。
文摘Cooling tower is crucial equipment in the cool-end system of power plant and the natural draft counter-flow wet cooling tower(NDWCT)gets wide application.The artificial neural network(ANN)technique is becoming an effective method for the thermal performance investigation of cooling towers.However,the neural network research on the energy efficiency performance of NDWCTs is not sufficient.In this paper,a novel approach was proposed to predict energy efficiency of various NDWCTs by using Back Propagation(BP)neural network:Firstly,based on 638 sets of field test data within 36 diverse NDWCTs in power plant,a three-layer BP neural network model with structure of 8-14-2 was developed.Then the cooling number and evaporation loss of water of different NDWCTs were predicted adopting the BP model.The results show that the established BP neural network has preferable prediction accuracy for the heat and mass transfer performance of NDWCT with various scales.The predicted cooling number and evaporative loss proportion of the testing cooling towers are in good agreement with experimental values with the mean relative error in the range of 2.11%–4.45%and 1.04%–4.52%,respectively.Furthermore,the energy efficiency of different NDWCTs can also be predicted by the proposed BP model with consideration of evaporation loss of water in cooling tower.At last,a novel method for energy efficiency prediction of various NDWCTs using the developed ANN model was proposed.The energy efficiency index(EEI)of different NDWCTs can be achieved readily without measuring the temperature as well as velocity of the outlet air.
文摘High temperature and humidity can be controlled in greenhouses by using mechanical refrigeration cooling system such as air conditioner(AC)in warm and humid regions.This study aims to evaluate the techno-financial aspects of the AC-cooled greenhouse as compared to the evaporative cooled(EV-cooled)greenhouse in winter and summer seasons.Two quonset single-span prototype greenhouses were built in the Agriculture Experiment Station of Sultan Qaboos University,Oman,with dimensions of 6.0 m long and 3.0 m wide.The AC-cooled greenhouse was covered by a rockwool insulated polyethylene plastic sheet and light emitting diodes(LED)lights were used as a source of light,while the EV-cooled greenhouse was covered by a transparent polyethylene sheet and sunlight was used as light source.Three cultivars of high-value lettuce were grown for experimentation.To evaluate the technical efficiency of greenhouse performance,we conducted measures on land use efficiency(LUE),water use efficiency(WUE),gross water use efficiency(GWUE)and energy use efficiency(EUE).Financial analysis was conducted to compare the profitability of both greenhouses.The results showed that the LUE in winter were 10.10 and 14.50 kg/m^(2) for the AC-and EV-cooled greenhouses,respectively.However,the values reduced near to 6.80 kg/m^(2) in both greenhouses in summer.The WUE of the AC-cooled greenhouse was higher than that of the EV-cooled greenhouse by 3.8%in winter and 26.8%in summer.The GWUE was used to measure the total yield to the total greenhouse water consumption including irrigation and cooling water;it was higher in the AC-cooled greenhouse than in the EV-cooled greenhouse in both summer and winter seasons by almost 98.0%–99.4%.The EUE in the EV-cooled greenhouse was higher in both seasons.Financial analysis showed that in winter,gross return,net return and benefit-to-cost ratio were better in the EVcooled greenhouse,while in summer,those were higher in the AC-cooled greenhouse.The values of internal rate of return in the AC-and EV-cooled greenhouses were 63.4%and 129.3%,respectively.In both greenhouses,lettuce investment was highly sensitive to changes in price,yield and energy cost.The financial performance of the AC-cooled greenhouse in summer was better than that of the EV-cooled greenhouse and the pattern was opposite in winter.Finally,more studies on the optimum LED light intensity for any particular crop have to be conducted over different growing seasons in order to enhance the yield quantity and quality of crop.
