This document summarizes a study analyzing the effects of ambient temperature on the performance of mono-crystalline solar photovoltaic modules in Tripura, India. Key findings include: - A statistical analysis found a 92% correlation between ambient temperature and module efficiency, with efficiency decreasing as temperature increased. - The regression equation derived from the 12-month study was that module efficiency (y) equals 8.66% + 0.1355% for each degree Celsius of ambient temperature (x). - The study concludes ambient temperature can be used to accurately predict photovoltaic performance for the region, as manufacturer specifications do not account for local environmental conditions.

1. Effects of Ambient Temperature on
Performance Analysis of Mono-crystalline
Solar Photovoltaic Module in Composite
Climate
Tanima Bhattacharya
Electrical Engineering Department, NIT, Agartala, India
Ajoy Kumar Chakraborty
Department of Electrical Engineering, NIT Agartala, India,
Kaushik Pal
Department of Mechanical and Industrial Engineering,
IIT Roorkee, India.
IVth International Conference on Advances in Energy
Research, Indian Institute of Technology, Bombay
December 10-12, 2013
1

2. RENEWABLE ENERGY SECTOR IN TRIPURA
 Remote
Village Electrification : 1860 KW
 Solar
Lantern Programme : 200 KW
 Solar
Power Plant : 300 KW
 Solar
Street Lighting System : 200KW
 Solar
Water Heating system : 54KW
 Total
power Installed : 2.6 MW
2

3. 3

4. GEOGRAPHICAL LOCATION AND METEOROLOGICAL DATA
The Analysis has been done at Agartala, Tripura

Lattitude: 23° 50' N

Longitude: 91° 25' E

Height from Sea Level: 43.786 m above sea level

Average Maximum temperature : 33.4 0C

Average Minimum temperature : 15.9 0C

Average Solar Irradiation received : 4-5 Kwh/m2
4

5. AVERAGE WEATHER OF TRIPURA FOR LAST FIVE YEARS
Month Jan Feb
Mar
Apr May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Year
Average
high 25.6 28.3
32.5
33.7
32.8
31.8
31.4
31.7
31.7
31.1
29.2
26.4 30.52
18.7
22.2
23.5
24.6
24.8
24.7
24.3
22
16.6
11.3 19.66
(°C )
Average
10
low
13.2
(°C )
5

6. VARIATION OF EFFICIENCY WITH RELATIVE HUMIDITY
6

7. VARIATION OF EFFICIENCY WITH WIND SPEED
7

8. VARIATION OF EFFICIENCY WITH SOLAR RADIATION
8

9. AMBIENT TEMPERATURE TABLE FOR
EXPERIMENTATION
Month
May 2012
June 2012
July 2012
August 2012
September 2012
October 2012
Novecymber 2012
December 2012
January 2013
February 2013
March 2013
April 2013
Ambient Temperature
(oC)
33.9
32.5
32.4
32.4
32.4
31.2
28.6
24.1
21.2
22.4
35.0
35.8
9

10. VARIATION OF AMBIENT TEMPERATURE FOR DIFFERENT
PERIOD THROUGHOUT THE YEAR
10

11. The maximum values of ambient
temperature is almost same for the
three months July to September of the
area of study due to rainy cloud cover
and high humidity.

Simultaneously the intensity of solar
radiation also reduces. After that, the
maximum temperature
slightly
increases for the month
of
October. After that from October 2012
to
April 2013 the temperature
increases linearly.

11

12. MATERIAL USED
Solar photovoltaic module
12

13. SPECIFICATION OF SOLAR MODULE
Peak power : 38 Wp
Short circuit current, Isc: 2.5 amp
Open-circuit voltage,Voc: 21.0 V
Voltage at maximum power, Vmax : 16.4 V
Current at maximum power, Imax : 2.26 amp
13

14. OPERATING PARAMETERS



Open circuit voltage
Short circuit current
Ambient Temperature
MEASURED PARAMETERS


Solar Photovoltaic Module Power
Module Efficiency
14

15. In the recent study a statistical analysis has
been done to show the ambient
temperature and the efficiency of the
solar module are correlated with each
other.
15

16. STATISTICAL ANALYSIS
Independent variable :
Ambient Temperature
Dependent Variable :
Module Efficiency
16

17. VARIATION OF EFFICIENCY THROUGHOUT THE YEAR
Month
Module Efficiency
(%)
May 2012
13.32
June 2012
13.01
July 2012
12.98
August 2012
12.98
September 2012
12.98
October 2012
12.72
November 2012
12.14
December 2012
12.23
January 2013
11.50
February 2013
11.77
March 2013
13.56
April 2013
13.74
17

18. VARIATION OF MODULE EFFICIENCY FOR DIFFERENT
PERIOD THROUGHOUT THE YEAR
18

19. VARIATION OF EFFICIENCY WITH THE VARIATION OF
AMBIENT TEMPERATURE
Month
Ambient Temperature
(oC)
Module Efficiency
(%)
May 2012
33.9
13.32
June 2012
32.5
13.01
July 2012
32.4
12.98
August 2012
32.4
12.98
September 2012
32.4
12.98
October 2012
31.2
12.72
November 2012
28.6
12.14
December 2012
24.1
12.23
January 2013
21.2
11.50
February 2013
22.4
11.77
March 2013
35.5
13.56
April 2013
35.8
13.74
19

20. REGRESSION ANALYSIS
Effect
Sums of squares
Mean squares
Regression
4.969844
4.969844
Residual
0.375779
0.037578
Total
5.345623
20

21. REGRESSION SUMMARY FOR DEPENDENT VARIABLE
R = 0.96421126, R2 = 0.92970335
Adjusted R2 = 0.92267369
N= 12
Beta
Std. Error of
Beta
B
Std. error of
B
Intercept
--------
---------
8.662075
0.359844
Ambient
Temperatur
e
0.964211
0.083843
0.135549
0.11787
21

22. SUMMARY STATISTICS EFFICIENCY
Statistics
Value
Multiple R
0.9642
Multiple R2
0.9297
Adjusted R2
0.9227
Standard error of Estimate
0.1939
22

23. REGRESSION DESCRIPTIVE STATISTICS
Variable
Ambient
Temperature
Efficiency
Ambient
Temperature
1.000000
0.964211
Efficiency
0.964221
1.000000
23

24. VARIATION OF MODULE EFFICIENCY WITH AMBIENT TEMPERATURE
WITH 95 % CONFIDENCE LEVEL
24

25. VARIATION OF MODULE EFFICIENCY WITH AMBIENT
TEMPERATURE
25

26. The value of correlation coefficient (r2) which is
about 92% obtained from the statistical analysis
indicates the very good correlation of the two
variables.
The regression equation obtained from the analysis
is:
y = 8.6621+0.1355 * x ,
26

27. RESULTS
1.Correlation coefficient (r2) is 92% which
indicates a very good correlation.
2. Direct proportionality between ambient
temperature and solar photovoltaic
module
efficiency.
3. Positive correlation exists between the two
variables.
27

28. CONCLUSIONS
1.
SPV modules performance varies with actual
location and prevailing environmental condition
to which they are subjected.
2.
The specification given by the manufacturer does not
actually give the accurate result while analyzing the
performance of the PV system for a particular area.
3.
Ambient Temperature can be used as parameter for
predicting
the performance of photovoltaic module for the area
of recent
28
study.

29. 29