光伏系统
热致变色
涂层
材料科学
热的
光电子学
复合材料
电气工程
热力学
化学
工程类
物理
有机化学
作者
Jingyu Zhang,Baolu Wang,Gang Li,Huilan Huang
标识
DOI:10.1016/j.applthermaleng.2023.121358
摘要
In this study, a new PV/T system structure is proposed based on the upper surface cooling PV/T system of PV cells. Conventional PV/T system PV unit and solar thermal unit are mutually constrained. The PV/T system proposed in this study solves this problem by separating the collector unit and the photovoltaic unit. A reversible thermochromic coating that can be applied to PV/T system collectors was prepared to further improve the system efficiency. The function of regulating the ratio of PV/T system photothermal and photovoltaic output is achieved by utilizing the property of thermochromic coating to change color when reaching the target temperature. An experimental platform was built for the experimental study and analysis of the PV/T system based on reversible thermochromic coating. The results show that: Adding the right amount of high thermal conductivity powder to the reversible thermochromic coating can improve the thermal efficiency of PV/T systems. The thermal efficiency of the PV/T system reached 46.09% with the addition of 10,000 mesh graphite at a mass fraction of 2‰ in the thermochromic coating, which was 16.57% higher than that of the PV/T system without the coating. When the mass fraction of 36000 mesh graphite added in the thermochromic coating was 3‰ the PV cell output power regulation effect was the best, and the average output power of PV cell was increased by 10.19% after coating color change. The primary energy saving efficiency of PV/T system reached 53.26% when the mass fraction of 10,000 mesh graphite added to the thermochromic coating was 2‰, which was 10.29% higher than the primary energy saving efficiency of PV/T system without coating. The PV/T system in this study is applicable to the application scenario where the thermal energy demand is dominant, broadening the scope of application of the PV/T system.
科研通智能强力驱动
Strongly Powered by AbleSci AI