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356 tadhg
1. 3D Thermal Numerical Analysis of a
Densely Packed Concentrating Receiver
Marios Theristis, Michail E. Arnaoutakis, Nabin Sarmah, Tapas K. Mallick
and Tadhg S O’Donovan
4th ICAER
10-12th December 2013
IIT Bomday, Mumbai, India
3. Approach
•
NREL SMARTS model (AM1.5D) multiplied by a CR of 500x assuming uniform
concentration per nm
•
EQE data for (Ga0.35In0.65P/Ga0.63In0.17As/Ge) III-V cells (from literature)
•
Simulation of IV characteristics of each sub-cell and total electrical power output
estimation
2D and 3D Finite Element Analysis (FEA) of the thermal behaviour in COMSOL
Multiphysics
Thermal power as calculated from the electrical model is used as an input
Prediction of the cell’s surface temperature using a parametric study to vary the
ambient temperature and the convective heat transfer coefficient
8. Boundary Conditions of 2D single cell
model
No
1
2
3
4
Region
Back side of cell
Air gap
Cell’s surface
Sides of cell
5
6
Back plate
Air gap
InGaP
InGaAs
Ge
Adhesive
Material
Copper
Alumina
Copper
Boundary condition
Inflow heat flux as found from electrical model
Open boundary conditions with no shear stress
Surface to ambient radiation and natural convection
Perfect thermal insulation was assumed on the sides of the cell
and a no slip boundary condition was considered on the wall
Surface to ambient radiation and convection
Ambient temperature of 20-45oC
Air
13. Geometry & Boundary Conditions of 3D
Densely Packed Receiver
No
Region
Boundary condition
1
On top of cells
Inflow heat flux as found from numerical model
2
Ambient
Ambient temperature of 20-45oC
3
Cell’s surface
Surface to ambient radiation and natural convection
4
Sides of cell
5
Heat Sink
PV receiver components
1: Frame
2: Cover glass
3: Al2O3 ceramic
4: Solar cells
5: Copper plate
6: Aluminium heat sink
Heat is conducted through the layers
Surface to ambient radiation and convection
2
3
1
2
1
4
4
5
3
5
6
14. Results of 3D Model
(with an extensive surface – aluminium heat sink)
Tcell(hnat.conv)
5<=hconv<=25W/m2K
C=500x
Tcell(Tamb)
15<=Tamb<=45oC
C=500x
Tcell(C)
50<=C<=500 suns
hnat.conv=15W/m2K
C=500x
Tamb =15oC
hnat.conv=15W/m2K
15. Results of 3D Model
(without an extensive surface)
C=500x
Tamb =25oC
hf.conv=3.5kW/m2K
Tcell(hnat.conv)
0.5<=hf.conv<=7.5kW/m2K
C=500x
16. Results of 3D Single Cell Model
C=500x
Tamb =25oC
hconv=700kW/m2K
nopt(λ)=1 (will be added later on)
Unrealistic Scenario – NO current mismatch
Realistic Scenario - Current mismatch
17. Spectral irradiance within
various solar spectra*
*B. S. Richards, "Enhancing the performance of silicon solar cells via the
application of passive luminescence conversion layers," Solar Energy Materials
and Solar Cells, vol. 90, pp. 2329-2337, Sep 22 2006.
18. Discussion & Conclusions
A detailed integrated solar spectrum dependent thermal-electrical model was
described for a HCPV cell. This model can lead to the accurate quantification
of the thermal power which is needed to be dissipated, including the excess
thermal output due to current mismatch.
Passive cooling cannot dissipate enough heat from the densely packed
configuration since a minimum convective heat transfer coefficient of
2.5kW/m2K is needed from the candidate cooling system.
Passive cooling with (Rth<1.2K/W) is feasible for single cell geometries
however, the atmospheric conditions of the location (wind speed, ambient
temperature, etc) must be taken into careful consideration when designing a
receiver.
This study validates the results of our previous work, where real
meteorological data were used to predict the temperature distribution across
a solar cell and was suggested that a hconv of around 6kW/m2K should be
required from the cooling system in order for the cell to withstand the harsh
ambient conditions.
Here is just to describe the methodology - aim. The integrated modelling is like a circle where the ‘thermal parameters’ are affected from the ‘electrical’ and vice versa. So starting from the EQE, higher temperature will shift the response towards the longer wavelengths, therefore the current production on each subcell will change, hence the overall performance will be increased or decreased. Our aim is to keep some values constant and vary each parameter at a time in order to build a model to accurately quantify the CPV performance, including spectral variations and current mismatch.You can mention that III-V cells are used which are basicly 3 different cells on the top of each other, gallium indium phosphide, gallium indium Arsenide and Germanium at the bottom. Due to the series connections the total voltage output is equal to the sum of the three subcells while the total current output is restricted to the minimum.
I used the NREL SMARTS model to get the AM1.5D as an input to the model. This was multiuplied by 500x.External Quantum Efficiency (EQE) data were obtained from literature and the cell manufacturer (Azurspace).Then the numerical model simulated the IV characteristics for each sub-cell and also the total electrical power output. From that I could calculate the heat power which is left, and I imported it into a 2D FEA model in Comsol.Later on, I did a parametric study varying the ambient temperature and the convective heat transfer coefficient on the backplate.
EQE responses from each subcell. Top (red) medium (green) bottom (purple). And the AM1.5D spectrum under 500x concentration with blue colour.
This is the theoritical model – you dont need to discuss about the equivalent if you want. I think you know that better than me.
Results obtained from the electrical model. This is the current density production as a function of the spectrums wavelength. Germanium generates higher current density and that can be seen in the next slide.
Here again, Germanium generates almost 10A, however the total current output is limited to the lowest value of the Top and middle cells, which are current matched. Voltage is summed.The maximum electrical output power from the cell was found to be 18.55W while the minimum heat power which needs to be dissipated is 26.45W.
Now, having explained the electrical model, we will use those results as an input for the thermal model in comsol. These are the boundary conditions of the thermal model. Air gap is varied from 20-45oC in order to predict the convective heat transfer coefficient of the back plate (5).
Results of the Parametric study; The dotted line divides the hconv which can maintain the cell below 80oC. It can be seen that above 2.5kW/m2K, a cells temperature below 80C can be maintained. However since CPV applications are always installed in countries with high DNI, thus ambient temperature can be above 40oC, then the heat transfer coefficient should be above 6kW/m2K for safe operation under any circumstances.
Real data are used from Athens where the max ambient temp is 40+ and a hconv of 6kW/m2K is predicted.
Now, having explained the electrical model, we will use those results as an input for the thermal model in comsol. These are the boundary conditions of the thermal model. Air gap is varied from 20-45oC in order to predict the convective heat transfer coefficient of the back plate (5).
This slide shows the difference of the cell temperature when current mismatch is taken into consideration and when is not.
Future work; more profiles will be added in the model to predict the thermalbeahaviour.