大跨度保温型温室的热环境模拟

大跨度保温型温室为拱型钢骨架结构，南北走向，相邻温室间距仅2m，相比于传统日光温室土地利用率提高到91%，且仍具有日光温室节能的特点。为分析和评价该温室的蓄热保温性能，基于温室热传导、对流换热、太阳辐射、天空辐射、作物蒸腾、自然通风等热物理过程，构建了温室内热环境变化模型，并利用Matlab软件对其进行求解，模拟在冬季连续4个典型工作日无加温条件下，每10min的室内空气温度和作物根区温度，并将模拟值与实测值进行对比分析。结果表明，模型对大跨度温室内空气温度模拟的平均绝对误差在±1.3℃之内，模拟值与实测值间直线方程的决定系数（R2）为0.99（n=576），回归估计标准误差（RMSE）和相对误差（RE）分别为1.6℃和16.4%；作物根区温度实测值与模拟值的绝对误差在±0.6℃之内，直线方程的R2为0.91（n=576），RMSE和RE分别为0.76℃和6.7%。模型模拟值与实测值较为一致，可为温室环境精准调控和结构优化设计提供理论依据。

Modelling of Thermal Climate in a Large-scale Insulation Solar Greenhouse

Large-scale insulation solar greenhouse, with wide span, steel frame and built in south-north orientation, was a tunnel type greenhouse. The distance between greenhouses was only 2m and the land utilization efficiency can be increased up to 91%, but it still has the characteristics of energy saving compared with traditional solar greenhouse. A greenhouse climate model was developed in order to predict the inside air temperature and root zone temperature to assess the greenhouse insulation and heat storage ability based on the physical processes of heat conduction, heat convection, solar radiation distribution, sky radiation, crop transpiration and air exchanged by natural ventilation. The model was established with Matlab software to calculate the temperature of the different parts. The variables, include inside air temperature and plant root zone temperature, were also measured during four successive days with time span of 10min. The results showed that the absolute error of the air temperature inside large-scale insulation solar greenhouse was ±1.3℃, the simulated air temperature agreed well with the measured data. The determination coefficient of linear equation (R2) (n=576), root mean squared error (RMSE) and relative prediction error (RE) between simulated and measured air temperature was 0.99, 1.6℃ and 16.4%, respectively. The absolute error of the root zone temperature was ±0.6℃. The determination coefficient of linear equation (R2) (n=576), RMSE and RE between simulated and measured root zone temperature was 0.91, 0.76℃ and 6.7%, respectively. It was concluded that the model was robust and could be used for the optimization of the large-scale insulation solar greenhouse as well as the climate control.