| 考虑动态吸收率的玻璃温室覆盖层温度预测模型 |
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| 引用本文： | 张观山,李天华,侯加林.考虑动态吸收率的玻璃温室覆盖层温度预测模型[J].农业工程学报,2020,36(5):201-211. |
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| 作者姓名： | 张观山 李天华 侯加林 |
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| 作者单位： | 山东农业大学机械与电子工程学院,泰安 271018;山东农业大学机械与电子工程学院,泰安 271018;山东农业大学机械与电子工程学院,泰安 271018 |
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| 基金项目： | 十三五国家重点研发计划项目智能农机装备专项"温室智能化精细生产技术与装备研发"（2017YFD0701500）;山东省现代农业产业技术体系蔬菜产业创新团队项目（SDAIT-05-11） |
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| 摘 要： | 覆盖层温度是影响温室热环境的重要因素之一。为了实现温室覆盖层温度预测,该研究以玻璃温室覆盖层为研究对象,综合考虑太阳辐射吸收、对流换热等能量传递形式,建立温室覆盖层温度预测模型。为提高模型精度,该研究进一步提出温室覆盖层动态吸收率计算方法,并使用该方法将覆盖层太阳辐射吸收率分为直射辐射吸收率、散射辐射吸收率与地表反射辐射吸收率分别计算,进而精确计算覆盖层吸收太阳辐射。为验证模型正确性及其精度,在山东省泰安市选择3个时段开展相关验证试验并得出如下结论,温室覆盖层温度预测值与测量值变化趋势较为一致,模型计算值与覆盖层温度测量值的决定系数R^2最小为0.92,均方根误差RMSE最大为2.05℃,通过与相关模型对比得出该研究提出的模型能够精确预测覆盖层温度。
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| 关 键 词： | 温度 模型 温室 覆盖层 动态吸收率 太阳辐射 能量传递 |
| 收稿时间： | 2019/12/2 0:00:00 |
| 修稿时间： | 2020/2/14 0:00:00 |
Model for predicting the temperature of glass greenhouse cover considering dynamic absorptivity |
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| Zhang Guanshan,Li Tianhua and Hou Jialin.Model for predicting the temperature of glass greenhouse cover considering dynamic absorptivity[J].Transactions of the Chinese Society of Agricultural Engineering,2020,36(5):201-211. |
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| Authors: | Zhang Guanshan Li Tianhua and Hou Jialin |
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| Institution: | 1. College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian 271018, China; 2. Shandong Provincial Engineering Laboratory of Agricultural Equipment Intelligence, Taian 271018, China,1. College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian 271018, China; 2. Shandong Provincial Engineering Laboratory of Agricultural Equipment Intelligence, Taian 271018, China and 1. College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian 271018, China; 2. Shandong Provincial Engineering Laboratory of Agricultural Equipment Intelligence, Taian 271018, China |
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| Abstract: | The cover temperature has an important effect on the thermal behavior of the greenhouse. This research developed and validated a prediction model of the cover temperature considering dynamic cover absorptivity. The absorptivity of the cover changes with the time of day and depending on many parameters such as the refractive coefficient, extinction coefficient, and thickness of the cover. The dynamic absorptivity of the cover was used to improve the model’s accuracy. The absorptivity of the cover was divided into the absorptivity of beam radiation, diffuse radiation, and ground-reflected radiation. This mathematical model also considered the thermodynamic exchanges between the cover and other components of the greenhouse including the convection, shortwave and longwave radiation. A computer program adopting the MATLAB standard solver ode45 was written to find a solution to the energy equations employing a fourth-order Runge–Kutta method. The input parameters of the model were the measurement of the meteorological environment and thermo-physical characteristics of the greenhouse components including those of the soil and inside air. The thermophysical characteristics of the greenhouse were determined by the material properties of the glass greenhouse and the construction scheme, which were not affected by the geographic location of the glass greenhouse. Initial input values for these equations were the measured temperatures of cover, soil, and air at t=0. Employing the computer program model built-in MATLAB, trends of temperature in the greenhouse were acquired by solving the unsteady-state energy balance equation for the structural components of the greenhouse and estimating heat absorbed by various surfaces. The model was validated utilizing measured data of three non-continuous periods of 10 days in three seasons in the north of China in Shandong province(36°08’N, 116°95’E). To predict the model accuracy, varying statistical indicators, including the root-mean-square error(RMSE), and the square of the correlation coefficient(R^2) was determined from data series. The model’s accuracy was verified by comparing the calculated temperatures with experimental measurements for the glass greenhouse. The best results were obtained with RMSE=1.26 ℃ and R2=0.98 for the cover temperature. The worst results were obtained with RMSE=2.05 ℃ and R2=0.92 for the cover temperature. Statistical analysis confirmed that the developed model was effective in forecasting the microclimate of the greenhouse. Finally, we compared the accuracy of this model with related research abroad. With the comparison, we concluded that the accuracy of the model was higher than that of the related research abroad. Because this research considered the dynamic absorptivity of the greenhouse cover creatively. Besides, this study had an energy analysis of solar radiation flux absorbed by the cover with the experimental greenhouse as a study case. The results indicated that the south wall absorbed less solar radiation in the summer period, while other walls and roofs absorbed more solar radiation in the summer period. The solar radiation absorbed by the east wall and the west wall was almost equal. The north wall absorbed the least solar radiation compared with other walls and roofs. It is clear that the quantification of solar radiation as demonstrated here is of great interest to the growers and is essential for the model’s accuracy and greenhouse management. |
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| Keywords: | temperature models greenhouse cover dynamic absorptivity solar radiation energy transfer |
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