8th PVPMC Workshop, May 9-10 2017

1. Temperature Coefficients and Thermal Uniformity
Mapping of PV Modules and Plants
Ashwini Pavgi, Joseph Kuitche, Jaewon Oh and GovindaSamy TamizhMani
8th PV Performance Modeling and Monitoring Workshop
Albuquerque, New Mexico
May 9, 2017

2. PART 1
PART 2
AZ
3
AZ
5
Mapping of thermal
uniformity of PV cells in a
module
Mapping of thermal
uniformity of PV modules in
PV plants
Determination of climate-
specific (Phoenix/AZ)
thermal model coefficients,
specifically for PVsyst
2
This is a two-part presentation:

3. 3
Part 1
Mapping of Thermal Uniformity in a Module

4. How to obtain accurate temperature coefficients outdoor?
Thermocouple locations
T1: Center
T2: Corner
T3: Short edge
T4: Long edge
2. Electrical conditions before taking I-V curves
• Maximum power point tracking condition
1. Test modules
Various PV technologies: c-Si, CdTe, CIGS and a-Si
Approaches to reduce the temperature difference:
• Frame and back sheet insulated
• Frame-insulated
• Black-frame
• Aluminum tape on white backsheet
4
This work attempts to answer the following question:
How to reduce the temperature difference between T1,
T2, T3 and T4?
3. Weather data
Wind speed, irradiance etc.

5. Approaches attempted to reduce the temperature difference in a module
5
Code Insulation Type Technology Code Insulation Type Technology
1 Non-insulated mono-Si 5 Frame and
backsheet insulated
poly-Si
2 Aluminum tape
covered backsheet
mono-Si 6 Non-insulated a-Si
3 Frame insulated Poly-Si 7 Non-insulated CIGS
4 Non-insulated
(frameless)
CdTe 8 Non-insulated
(black frame)
mono-Si

6. 0
1
2
3
4
5
6
7
8
9
10
10:00:00 11:00:00 12:00:00 13:00:00 14:00:00
ΔT(oC)
Temperature monitoring at Pmax at one minute interval from 10am-2pm
cSi CdTe CIGS
ΔTmax between four thermocouples @ MPPT
6

7. -2.8
-5.7
-1.7 -1.4
-5.9 -5.7
-2.6
-4.8
-6.9
-5.4
-3.2
-6.1
4.8 4.5
2.2
1.1
7.4
4.6
2.6
5.4
7.7
4.2
2.9
7.1
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
No insulation Black frame Frame insulation F & BS insulation
Percentchange
Percentage change in temperature coefficients with respect to different temperature
sensors
Iscmin Vocmin Pmaxmin Iscmax Vocmax Pmaxmax
Thermal variation based on various thermal insulation configurations
Variation in c-Si PV module with frame insulation ±3 percent
Variation in c-Si PV module with black frame ±6 percent
LEAST
7

8. Maximum temperature difference (ΔTmax) between the thermocouples
depends on the insulation configuration
8
 c-Si module with
black frame
experienced the
least ΔTmax
 The variability in
ΔTmax is the highest
in no insulated
module
 ΔTmax value for
module backsheet
with aluminum
cover is highest, but
the variability is
lower
Weather condition:
Irradiance= 1007-1015 W/m2
Wind speed = 0.7-0.8 m/s
Ambient temperature = 22-24 oC
c-Si

9. Temperature difference between two identical modules (use of thermocouples):
White backsheet vs. White backsheet with aluminum cover
Backsheet with Al cover: Blocking radiative loss causes higher operating temperature
15
25
35
45
55
65
75
38
39
40
41
42
43
44
10:00AM
11:00AM
12:00PM
1:00PM
2:00PM
3:00PM
4:00PM
5:00PM
Temperature(oC)
Voc(volts)
Temperature and voltage values on a clear sunny
day 10am-5pm
Sensor A Voc: No insulation
Sensor B Voc: Aluminum tape covered BS
No insulation: temperature
Al tape covered BS: temperature
-3
-2.5
-2
-1.5
-1
-0.5
0
0
2
4
6
8
10
12
14
16
18
10:00AM
11:00AM
12:00PM
1:00PM
2:00PM
3:00PM
4:00PM
5:00PM
Voc(volts)
Temperature(oC)
Impact of aluminum covered back sheet on
temperature and voltage on a clear sunny day
∆T ∆V
Average ΔT= 8oC
Highest= 15oC
9

10. Weather conditions:
Irradiance= 1019 W/m2, Wind speed= 1.2 m/s, Ambient temperature= 24.9 oC
61.8-29.4
= 32.4 oC
Blockage of
radiative loss
Since IR imaging captures only the
surface radiation (not the cell
temperature) of the substrate, IR
image shows that the white backsheet
with aluminum cover is about 32oC
cooler but the cell is actually hotter as
can be seen by the attached
thermocouples (see the previous
slide)!
10
With Al cover on
white back sheet
White back sheet
only
With Al cover on
white backsheet
White backsheet
Front Imaging
Back Imaging
Backsheet with Al cover: Blocking radiative loss causes higher operating temperature
Temperature difference between two identical modules (use of IR imaging):
White backsheet vs. White backsheet with aluminum cover
IR Imaging: Misleading

11. 11
Part 1
Mapping of Thermal Uniformity in a Plant

12. Data collected from 04/17/2015 to 09/30/2015
Thermal Mapping of Modules in PV Power Plants
System
Tilt/
orientation
Years
fielded
Year
Commissioned
Model
Type
Number of
modules
Site 4a Horizontal fixed 19 1997 AZ3 1512
Site 4c One-axis tracking 7 2009 AZ5 1280
Location of thermocouples on each of five modules per plant
T1 = Center cell temperature
T2 = Corner cell temperature
T3 = Bottom cell temperature
T4 = Left cell temperature
Location of each HOBO under an array
12
AZ3
AZ5
Temperatures of
five modules (four
corners and
center) of each
plant monitored
Horizontal fixed
1-Axis Tracking
AZ5 plant is about 4 feet lower than AZ3 plant
& 15 foot high wall to south of AZ5 plant

13. AZ3 PLANT LEVEL TEMPERATURE DISTRIBUTION: SOLAR NOON (12-1PM)
Installation type: Fixed horizontal system
Module: Siemens SP75 frameless
PV technology: Monocrystalline silicon
Years of field exposure: 19
NW
SW
NE
SE
Date: July 15, 2015
Weather conditions: Clear sunny day
Average irradiance (GHI,
SolarAnywhere): 971 W/m2
Average wind speed: 3m/s
13

14. NW NE
SW SE
AZ5 PLANT LEVEL TEMPERATURE DISTRIBUTION SOLAR NOON (12-1PM)
Installation type: One-axistracking system
Module: Sanyo HIP190 framed
PV technology: Monocrystalline silicon
heterojunction
Years of field exposure: 7
Date: July 15, 2015
Weather conditions: Clear
sunny day
Average irradiance (GHI,
SolarAnywhere) : 971
W/m2
Average wind speed: 3m/s
14

15. Thermal representation for AZ3 and AZ5
9am-5pm data Daily average data Solar noon data
AZ3 100% 100% 100%
AZ5 109% 107% 103%
30
40
50
60
70
AZ3 and AZ5 : Plant level 9am-5pm temperature
(averaged) data
AZ3 9-5 AZ5 9-5
30
40
50
60
70
AZ3 and AZ5 : Plant level solar noon temperature
(averaged) data
AZ3 solar noon AZ5 solar noon
15

16. 47
48
49
50
51
52
53
Center Corner Bottom Left
AZ3 Center
Module level temperature variation from 9am – 5pm
∆T = 3.036649
47
48
49
50
51
52
53
Center Corner Bottom Left
AZ3 SE
∆T = 0.848
Cell temperature
difference within a
module: 0.8-3.0oC
47
48
49
50
51
52
53
Center Corner Bottom Left
AZ3 SW
∆T = 1.778
47
48
49
50
51
52
53
Center Corner Bottom Left
AZ3 NW
∆T = 2.485
47
48
49
50
51
52
53
Center Corner Bottom Left
AZ3 NE
∆T = 2.373
Fixed horizontal (AZ3) Average temperature: 50.4oC
16

17. Module level temperature variation from 9am – 5pm
49
51
53
55
57
59
Center Corner Bottom Left
AZ5 Center49
51
53
55
57
59
Center Corner Bottom Left
AZ5 NW
49
51
53
55
57
59
Center Corner Bottom Left
AZ5 NE
49
51
53
55
57
59
Center Corner Bottom Left
AZ5 SE
∆T = 2.010
∆T = 4.008
∆T = 0.837∆T = 2.181
∆T = 2.453
Cell temperature
difference within a
module: 0.8-4.0oC
1-axis (AZ5)
Average
temperature:
54.9oC
Higher degradation rate
& Lower lifetime expected
17
49
51
53
55
57
59
Center Corner Bottom Left
AZ5 SW

18. CONCLUSION
• Mapping of thermal uniformity of PV cells in a module
• c-Si module with black frame experienced the least ΔTmax
• Temperature coefficients for c-Si module with frame insulation
experienced least variability
• It is recommended to use average value from four temperature
sensors for uninsulated crystalline silicon PV module
• Backsheet with aluminum cover experiences higher operating
temperature due to blocking of radiative losses.
• Mapping of thermal uniformity of PV modules in a plant
• Position (four corners or center) of the hottest modules
depends on the wind speed, wind direction and height of array.
18

19. 19
Part 2
Climate-specific Thermal Model Coefficients for PVsyst
(for Phoenix, Arizona)

20. 1. For free-standing arrays
Uc = 25 W/m²·K, Uv = 1.2 W/m²·K /m/s
2. For free-standing arrays (when the wind
velocity is not present in the data)
Uc = 29 W/m²·K, Uv = 0 W/m²·K /m/s
3. For fully insulated arrays
Uc = 15 W/m²·K, Uv = 0 W/m²·K /m/s
Default values provided by PVsyst
20
Climate-specific Thermal Model Coefficients for PVsyst
Goal : Develop thermal model coefficients for specific
PV technologies and specific climate

21. 21
System description
• 14 PV modules from 7 different manufacturers and of 6 different technologies
• a-Si technology is from two different manufacturers (glass superstrate and Tefzel/Polymer superstrate)
• South facing, latitude-tilt, open rack system
• Near Pmax operation with power resistors
• Data stored for every 5 minute interval
• Hot desert climate conditions (Phoenix, Arizona)
• Average wind speed= 1.84 m/s
• Average ambient temperature= 23.6 oC
• Average measured POA (annual) during the solar window time period 10am-2pm= 837 W/m2
Climate-specific Thermal Model Coefficients for PVsyst

22. Retrieve monthly data with main parameters together: Irradiance
(W/m2), wind speed (m/s), module temperature (oC) and ambient
temperature (oC) at five-minute interval
Filter the data for solar window time from 10am to 2pm
Calculate the following values: ΔT=Tmod-Tamb and (
𝐈𝐫𝐫𝐚𝐝𝐢𝐚𝐧𝐜𝐞
𝚫𝐓
)
Remove prominent outliers (due to data logging issues)
Plot (
𝑰𝒓𝒓𝒂𝒅𝒊𝒂𝒏𝒄𝒆
𝚫𝑻
) versus wind speed
Intercept of the line = Uc and Slope of the line = Uv
Performed model-adequacy checking of the residuals to statistically
determine the values
Average the values for two modules with same model number, cell
technology and manufacturer
Flow chart to determine Uc and Uv coefficients
22

23. 0
1
2
3
4
5
6
7
8
9
10
0
5
10
15
20
25
30
35
Uv(W/m3Ks)
Uc(W/m2K)
Uc and Uv values for all PV technologies based on one year data at
one hour interval (10am-2pm) for desert climate (Phoenix, Arizona)
Uc Uv
23

24. • Considering all the PV technologies, Uc and Uv value
tend to follow the trend of:
Polymer-Polymer > Glass-Polymer > Glass-Glass
• For c-Si PV technology (when average wind speed=
1.84 m/s):
Uc = 25.46 W/m2K
Uv = 4.31 W/m3K.s
CONCLUSION
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25. THANK YOU
Ashwini Pavgi
ashwini.pavgi@asu.edu
MS Thesis – Free Downloading: repository.asu.edu
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