骆乾亮, 程瑞锋, 张义, 方慧, 李冬, 张晋芳, 宋国祥. 日光温室主动蓄放热系统优化[J]. 农业工程学报, 2020, 36(17): 234-241. DOI: 10.11975/j.issn.1002-6819.2020.17.028
    引用本文: 骆乾亮, 程瑞锋, 张义, 方慧, 李冬, 张晋芳, 宋国祥. 日光温室主动蓄放热系统优化[J]. 农业工程学报, 2020, 36(17): 234-241. DOI: 10.11975/j.issn.1002-6819.2020.17.028
    Luo Qianliang, Cheng Ruifeng, Zhang Yi, Fang Hui, Li Dong, Zhang Jinfang, Song Guoxiang. Optimization of active heat storage and release system in solar greenhouse[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(17): 234-241. DOI: 10.11975/j.issn.1002-6819.2020.17.028
    Citation: Luo Qianliang, Cheng Ruifeng, Zhang Yi, Fang Hui, Li Dong, Zhang Jinfang, Song Guoxiang. Optimization of active heat storage and release system in solar greenhouse[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(17): 234-241. DOI: 10.11975/j.issn.1002-6819.2020.17.028

    日光温室主动蓄放热系统优化

    Optimization of active heat storage and release system in solar greenhouse

    • 摘要: 为了提高日光温室主动蓄放热系统运行的稳定性和可靠性,该研究在第六代主动蓄放热系统的基础上,对主动蓄放热系统的循环管路、供水方式和集放热板进行优化改进,并对系统的加温效果和性能进行探究。研究结果表明,在3种不同的太阳辐射强度天气条件下,试验区的平均气温比对照区分别高2.7、2.2和1.9 ℃;单位面积集热量分别为4.6、3.7和2.6 MJ/m2,单位面积放热量分别为4.1、3.4和3.1 MJ/m2;平均集热功率分别为183.1、146.5和105.0 W/m2,平均放热功率分别为163.2、134.0和121.1 W/m2;平均集热效率分别为56.5%、68.2%和73.8%;平均性能系数分别为3.8、3.1和2.8;与电加热相比,平均节能率分别为73.5%、67.1%和63.0%。在主动蓄放热系统加温期间,在不同太阳辐射强度天气条件下,试验区南北温差较大,植株群体内部南北最大平均气温分别相差2.8、2.6和2.4 ℃。研究结果可为主动蓄放热系统的推广应用提供理论基础和数据支撑。

       

      Abstract: Active Heat Storage-release System (AHS) is a solar thermal utilization system, which collects and stores solar energy through the water circulation in the daytime, and the energy is released at night. To improve the stability and reliability of the operation of AHS, based on the sixth generation of AHS, the circulation pipeline, water supply mode, solar energy collection board were optimized and improved. The field test lasted 87 days was done to investigate the heating effect, heating performance, control strategy of circulation, and the distribution of indoor air temperature during the heating process of improved AHS under different weather conditions. The test period was from November 24th, 2019 to February 29th, 2020. The results showed that, during the experiment time, the improved AHS was in stable operation mode, the energy-saving, and high heating efficiency, the optimization was effective. In three different weather conditions of solar radiation intensity, the average temperature in the experimental area was 2.7, 2.2, and 1.9 ℃ higher than that in the control area, and the heat collection capacity was 4.6, 3.7, and 2.6 MJ/m2 respectively, heat release capacity was 4.1, 3.4, and 3.1 MJ/m2 respectively. The average heat collection power was 183.1, 146.5, and 105 W/m2 respectively, and average heat release power was 163.2, 134, and 121.1 W/m2 respectively. The average heat collection efficiency of improved AHS was 56.5%, 68.2%, and 73.8% respectively and the average coefficient of performance was 3.8, 3.1, and 2.8 respectively. Compared to electric heating, the energy conservation rate of improved AHS was 73.5%, 67.1%, and 63% respectively. Compared with the sixth generation AHS, when total heat energy collected was similar, the daily average power consumption was reduced by 20%, the energy-saving efficiency was increased by 6.7%, and the coefficient of performance was increased by 0.8. The water flow rate was reduced, so the average heat collection efficiency was reduced by 10.3%. If the structure of AHS is improved in the future, the diameter of the aluminum alloy finned pipe is advised to increase to improve the heat collection efficiency. During the heating period at night, the influence of improved AHS on temperature distribution in the experimental area was very obvious, because the board was located in the north wall, and the north side of the greenhouse was closed to the lower temperature roof, the temperature difference between the north and the south in the greenhouse was large. The closer to the north wall at the same height, the temperature is higher. Under different weather conditions, the maximum average temperature difference between north and south parts in the canopy was 2.8, 2.6, and 2.4 ℃ respectively. This temperature difference was getting smaller with height because of the influence of crops on heat shielding and greenhouse shape. Through the analysis of water temperature change during the daytime, it was suggested to adopt the joint control method of temperature and time for control strategy optimization. The application and promotion of AHS could be supported by the basis of theory and experimental results in this study.

       

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