120 tanima bhattacharya

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120 tanima bhattacharya

  1. 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. 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. 3
  4. 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. 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. 6. VARIATION OF EFFICIENCY WITH RELATIVE HUMIDITY 6
  7. 7. VARIATION OF EFFICIENCY WITH WIND SPEED 7
  8. 8. VARIATION OF EFFICIENCY WITH SOLAR RADIATION 8
  9. 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. 10. VARIATION OF AMBIENT TEMPERATURE FOR DIFFERENT PERIOD THROUGHOUT THE YEAR 10
  11. 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. 12. MATERIAL USED Solar photovoltaic module 12
  13. 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. 14. OPERATING PARAMETERS    Open circuit voltage Short circuit current Ambient Temperature MEASURED PARAMETERS   Solar Photovoltaic Module Power Module Efficiency 14
  15. 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. 16. STATISTICAL ANALYSIS Independent variable : Ambient Temperature Dependent Variable : Module Efficiency 16
  17. 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. 18. VARIATION OF MODULE EFFICIENCY FOR DIFFERENT PERIOD THROUGHOUT THE YEAR 18
  19. 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. 20. REGRESSION ANALYSIS Effect Sums of squares Mean squares Regression 4.969844 4.969844 Residual 0.375779 0.037578 Total 5.345623 20
  21. 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. 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. 23. REGRESSION DESCRIPTIVE STATISTICS Variable Ambient Temperature Efficiency Ambient Temperature 1.000000 0.964211 Efficiency 0.964221 1.000000 23
  24. 24. VARIATION OF MODULE EFFICIENCY WITH AMBIENT TEMPERATURE WITH 95 % CONFIDENCE LEVEL 24
  25. 25. VARIATION OF MODULE EFFICIENCY WITH AMBIENT TEMPERATURE 25
  26. 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. 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. 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.
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