期刊
ENERGY EXPLORATION & EXPLOITATION
卷 35, 期 6, 页码 748-766出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/0144598717716285
关键词
Solar radiation; heat transfer; building wall; coating material; cooling load
资金
- National Key Research and Development Program of China [2016YFC0700406]
- National Natural Science Foundation of China [51478280]
- China Scholarship Council [201706245001]
Heat transfer through building envelopes constitutes the dominant part of indoor cooling load in summer. Coating building external walls with high reflectivity materials proves to be an effective way to reduce heat gains from solar radiation and save cooling energy consumption accordingly. In this paper, the transient heat transfer model of building external envelopes is established and validated through experiment, to investigate the thermal performance of building walls coated with retro-reflective materials. Moreover, taking an office building in Chengdu as an illustrative example, the cooling energy saving potential of such retro-reflective material coated building is evaluated in summer. The experiment results show that for the building box with retro-reflective coating materials (r = 0.59), the average indoor air temperature is about 2.4 degrees C lower than the reference box without coating materials, resulted from decreasing heat absorption of solar radiation for external walls. Furthermore, the illustrative example in Chengdu shows the cooling load can be reduced by about 9.1 W/m(2), with such retro-reflective coating materials for building external walls, saving 15.2% electricity consumption in a whole summer. The incremental investment for coating can be paid back by 9.1 years for the studied case. Moreover, economic analysis and comparison indicate that such coating material is more applicable to southern cities in China, since the payback period is shorter due to more cooling energy saving for those with hot summer. This work can provide guidance for practical building envelope thermal design.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据