An Experimental Study of Influencing Factors on the Snow Removing Time for Self-Heating Snow Removed Photovoltaic Panels

被引:1
|
作者
Zhao Li [1 ]
Chen Jianbo [1 ]
Wang Shunchao [1 ]
Qu Minglu [1 ]
Feng Min [1 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Environm & Architecture, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Photovoltaic panel; self-heating; snow-removing time; influencing factors; experimental study; regression model; 3-CIRCUIT OUTDOOR COIL; PUMP UNIT; DEFROSTING PERFORMANCE; THERMAL PERFORMANCE; ENERGY; PARAMETERS; EFFICIENCY; SYSTEMS;
D O I
10.1080/15435075.2021.1974449
中图分类号
O414.1 [热力学];
学科分类号
摘要
Because of the applicability and sustainability, photovoltaic (PV) panels are widely used around the world and attracting lots of academic research interests as one promising application of renewable energy. However, snow issues would decrease the power generating efficiency of PV panels during the winter in cold and snowy regions so that studies of snow-removing methods for PV panels attracted lots of interests. To some extent, current snow-removing methods, either manually or mechanically, have their own deficiencies. Therefore, a novel self-heating snow-removing method for PV panels was proposed in this study, applying a PV panel as an electrical load by supplying it with electric power. To validate this novel method, experiments were carried out and reported in detail in this paper and four influencing factors, snow thickness (4-8 cm), ambient air temperature (-3 to -9 degrees C), input power (170 to 290 W/m(2)) and the panel tilt (14 to 18o), on the snow-removing time were quantitatively analyzed. Generally, the experimental results showed that increasing the snow thickness, the ambient air temperature, the input electric power and the panel tilt would somehow benefit to the snow-removing process and within the range of the varying parameters the snow-removing time reduction could reach as high as 83.4%. Furthermore, the correlation between the four factors and the snow-removing time was generalized through multiple variables linear regression using obtained experimental data. The comparison between the predicted and tested value showed good agreement, suggesting that the correlation regressed can provide satisfying accuracy when applied to estimating the snow-removing duration in engineering application using the novel snow-removing method proposed in this paper.
引用
收藏
页码:904 / 917
页数:14
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