材料科学
散热片
微通道
冷却液
核工程
体积流量
热的
鳍
入口
光伏系统
可用能
火用
机械
机械工程
热力学
复合材料
电气工程
纳米技术
工程类
物理
作者
Jiguo Tang,Xiao Li,Rui Hu,Zhengyu Mo,Min Du
标识
DOI:10.1016/j.ijheatmasstransfer.2021.122094
摘要
To meet the requirements of cooling challenges of high concentrator photovoltaic (HCPV), a novel manifold ultrathin micro pin-fin heat sink (MUMPFHS) cooling technique is developed in this study. A comprehensive three-dimensional simulation model is established to investigate the thermal, energy and exergy performance of 10 × 10 mm2 HCPV cells cooling with MUMPFHS, using Star CCM+ with the help of user defined field functions. Compared with the previously proposed designs of the HCPV cooling schemes using jet impingement, hybrid jet impingement/microchannel and stepwise varying width microchannel, the present one shows great advantages of both uniform solar cell temperature and high cooling performance under a high solar concentration of 1000 suns. At inlet flow rate of 3 kg/h and temperature of 25 °C, the solar cell temperature can be reduced to 51 °C, with a small temperature non-uniformity of 3.4 °C. As the inlet flow rate increases, the average cell temperature and its non-uniformity further decrease, resulting in a higher electrical efficiency. However, the inlet coolant temperature has little impact on the cell temperature uniformity, allowing maximizing the inlet temperature to improve the thermal exergy efficiency under the recommended temperature range. In addition, five different designs of inlet/outlet plenums are proposed and integrated on the MUMPFHS, which could achieve a uniform flow distribution in each manifold channel. Thermal and exergy analysis confirms that taking the plenums into consideration increases the friction power which can be compensated by the improvement of electrical power due to the decrease of solar cell temperature. The present simulation results indicate that our designed MUMPFHS could increase the feasibility of using HCPV under higher solar concentration with safe operation.
科研通智能强力驱动
Strongly Powered by AbleSci AI