Venturi effect-based simulation of air-based PVT optimization

ABSTRACT

Air-based photovoltaic thermal(PVT) solar collectors can convert solar energy into both electrical and thermal energy. However, the output efficiency was often low due to the limitation of the heat transfer capacity for air. Therefore, in this paper, an air-based PVT with the application of a novel rib was modeled and numerically simulated. The innovation of this paper was proposing a novel rib, which was based on the Venturi effect. First, the effects of the new rib control parameters on the performance of the PVT system were analyzed using orthogonal design tests. The result showed that the thermal efficiency of the best factors combination test was 51.16% when the solar radiation was $500W/m^2$and the air inlet rate was $0.09m/s$. Second, analyzing the fluid flow characteristics and the enhanced heat transfer mechanism, this study found that the increased air velocity under the novel rib and the low-velocity vortex formed between the rib both negatively affected heat transfer. Consequently, this paper proposed a novel fin design coupled with curved fins to address the issues with the novel rib design, which achieved 55.12% thermal efficiency with the combination structure. Finally, we applied the combined structure to the PVT system, studied its thermal efficiency under real-world conditions, and compared it with the empty channel collector. The results showed significant improvement, with a 16.38% increase in thermal efficiency and the model exhibited excellent, stable performance.

KEYWORDS:

• PVT collector
• heat transfer enhancement
• the Venturi effect
• numerical simulation
• orthogonal design tests

Nomenclature

A	=	area, [m2]
Cp	=	Air specific heat, [J/(kg$\cdot$K)]
dferror	=	Degree of freedom for error, [-]
dffactor	=	Factorial freedom, [-]
dfT	=	Total degree of freedom, [-]
eb	=	Blackbody radiation force, [W/m2]
E	=	Rate of energy transfer, [W]
Gsun	=	Solar radiation, [W/m2]
hglass – amb	=	Convective heat transfer coefficient from glass to environment, [(Wm−2K−1]
H	=	Model height, [mm]
I	=	Moment of inertia, [kgm2]
J	=	Effective radiation of gray surface, [Wm−2]
k	=	Turbulent kinetic energy, [Wm−3]
L	=	Model length, [mm]
M	=	Air quality flow, [kgs−1]
n	=	Number of inserted ribs, [-]
N	=	Number of longitudinal ribs, [-]
P	=	Pressure, [Pa]
pk	=	Turbulent kinetic pressure, [Pa]
q	=	Heat flux vector, [-]
Q	=	Heat source (Wm−3)
SST	=	Square sum of total departure,[-]
SSerror	=	The sum of square of factor deviation,[-]
Rate of energy transfer, [W]	=
S	=	Model width, [mm]
Vair	=	velocity of air, [m/s]
$u_x,v_y,w_z$	=	velocity component, [m/s]
x, y, z	=	Cartesian coordinates, [mm]
n	=	Surface normal, [-]
F	=	Volume force, [N]
Greek symbols	=
αpv	=	Photovoltaic cell absorption rate, [-]
γ	=	Diffuse reflectance, [-]
$\epsilon$	=	Turbulence dissipation rate, [m2/s3]
$\eta th$	=	efficiency, [-]
$\lambda$	=	Thermal conductivity of material, [W/(m∙K)]
µ	=	Dynamic viscosity of the fluid, [m2/s]
µT	=	Eddy viscosity coefficient, [-]
$\xi$	=	Viscous stress tensor, [Pa]
$\rho$	=	density, [kg/m3]
$\sigma$	=	Stefan-Boltzmann value, [W/(m2∙K4)]
$\zeta glas$	=	Glass transmittance, [-]
$\mathrm{\nabla }$	=	Vector differential operator,[-]
${\epsilon }_{glas}$	=	Glass-surface emissivity,[-

Acknowledgements

The authors acknowledge the support of the Jilin Province Science and Technology Development Plan Project (20220203160SF).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work was supported by the Jilin Province Science and Technology Development Plan Project.

Notes on contributors

Jianrui Bai

Jianrui Bai received his B.S. degree in Energy and Power Engineering from the College of Modern Science and Technology, Taiyuan University of Technology in 2017. He is pursuing a master’s degree in the Department of Energy and Power Engineering at Changchun College of Engineering, China. His research interests include thermal, gas, ventilation, and air conditioning engineering. Gas, Ventilation, and Air Conditioning Engineering.

Liang Pan

Liang Pan received his Bachelor’s degree in Heating, Ventilation, and Air Conditioning Engineering from Jilin Architectural and Engineering College in 2000 and his Master’s degree in Thermal Engineering from Jilin University in 2007. He is currently working at Changchun Engineering Institute, in China. His main research interests are efficient energy utilization and heat transfer control.

Dali Ding

Dali Ding graduated from Jilin University and earned his Bachelor’s in Theoretical and Applied Mechanics in 2005. He received his M.S. in fluid mechanics from Lanzhou University of Science and Technology, Lanzhou, China 2009. He received his Ph.D. in Engineering Mathematics from Jilin University in 2019. He is currently working in Changchun Engineering Institute.

Rundong Zhang

Rundong Zhang received B.S. degree in Built Environment and Energy Application Engineering from Xi’an University of Science and Technology, Xi’an, China, in 2019 and the M.S. degree in Master of Civil and Hydraulic Engineering from Changchun Institute Of Technology, Changchun, China, in 2023. He is currently working toward the Ph.D. degree in Civil Engineering with the Shandong University of Science and Technology, Qingdao, China. His research interests include solar, hydrate and air conditioners.

Weijian Zhang

Weimin Zhang graduated from the Jinling Institute of Science and Technology in 2021, majoring in Mechanical Design, Manufacturing, and Automation. He is now pursuing a master’s degree in civil engineering from Changchun Engineering College.

Qi Du

Qi Du received his Bachelor’s Degree in Building Environment and Energy Application Engineering from Henan Engineering Institute in 2022. He is currently pursuing his master’s degree in the Department of Energy and Power Engineering, at Changchun Engineering Institute, China. His main research interests are heating, gas, ventilation, and air conditioning engineering.