Modeling Of Global Solar Radiation By Using Ambient Air Temperature At Coastal Cities In India

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International Journal of Applied Engineering Research ISSN 0973-4562 Volume 10, Number 7 (2015) pp. 16843-16852 Research India Publications http://www.ripublication.com Modeling Of Global Solar Radiation By Using Ambient Air Temperature At Coastal Cities In India S. Ravichandran 1 and Dr.J. David Rathnaraj 2 1 Assistant professor Department of Mechanical Engineering, Kalaignar Karunanidhi Institute of Technology, Coimbatore-641 402 2 Professor & Head Department of Mechanical Engineering, Sri Ramakrishna Engineering College, Coimbatore-641 022 E-mail: ravichandran_sv@yahoo.co.in & davidrathnaraj@gmail.com Abstract An attempt has been made to Modeling global solar radiation by using ambient air temperature at two cities Chennai and Trivandrum in India. Since the air temperature is the most registered variable, it is convenient to correlate the variable with solar radiation to propose a correlation equation in the two locations separately. Long-term measured monthly mean ambient air temperature and solar radiation has been collected from Indian Meteorological Department, Pune india and analyzed. Obtained results from the study have shown good relation between monthly mean solar radiation and ambient air temperature in the locations under study. Keywords: Air temperature, solar radiation, correlation Introduction Solar radiation is intermittent in nature and availability of solar radiation in a location is necessary for designing solar thermal devices for industrial and domestic applications. Since the solar radiation measuring devices are too expensive, data are measured for limited locations and led to improper designing of solar systems in the locations where data are not readily available. In this scenario, researchers all over the world have made sincere efforts to find relation between the easily measured variables with the solar radiation and found the correlation equations. The developed correlation equations by using measured data of solar radiation and other variables such as humidity, sunshine duration, air temperature etc., are utilized to predict the amount of solar radiation in locations where data are not available. Adjepong and Okujagu (1989) have developed a cross-correlation function of the daily time-series and found the approximate harmonics of the 27-day solar

16844 S. Ravichandran and Dr.J. David Rathnaraj radiation cycle. Regression equation has been derived for the estimation of monthly daily global solar radiation on monthly daily ambient air temperature using Fourier series by Kenisarin and Tkachenkova (1991). It has been concluded that the developed equation can be used to determine the solar radiation for 16 locations of Uzbekistan and Tadjikistan. Ododo et al. (1995) have made an attempt to analyze and develop a new empirical model for solar radiation with available data of solar radiation and maximum air temperature of nine stations in Nigeria. The developed model has shown satisfactory accuracy in predicting solar radiation in Nigerian locations. Reformulation of Bristow-Campbell model for daily solar radiation by using data of 40 stations in contrasting climates has been done by Thornton and Running (1999). It has been inferred that the mean absolute error for the prediction of solar radiation improved by 28% compared to the original model. Further Liu and Scott (2001) have proposed a correlation model for the estimation of daily solar radiation used for similar climatic region with no local recording by utilizing both temperature and rainfall data of 39 sites across Australia. It has been found that the new model was the best and reliable with least error. Paulescu et al. (2006) have found the possibility of using air temperature instead of sunshine duration for the estimation of global solar radiation. It has been inferred that the air temperature can be used for the estimation of global solar radiation with much less error. Papakostas et al. (2007) have proposed a method for estimating the ambient temperature bin data by utilizing monthly average outdoor temperature and solar clearness index at two most populated cities in Greece. It has been suggested that the method can be used for other cities in Greece which have similar climatic conditions. Different models proposed by various researchers all over the world for the estimation of solar radiation by using measured air temperature extremes have been examined for the suitability of the model in 29 stations distributed throughout India by Bandyopadhyay et al. (2008) and ranked in order of descending suitability. Prieto et al. (2009) have correlated air temperature data of Asturias, Spain with monthly average solar radiation and a model has been developed. Results have shown acceptable results compared with other methods and experimental data. Ali Rahimikhoob (2010) has made an attempt to test an artificial neural network (ANN) for estimating global solar radiation as a function of air temperature data in weather station of Ahwez, Iran. Results of the study revealed that the proposed ANN has shown better estimates than Hargreaves and Samani equation. Ji-Long Chen et al. (2011) have used support vector machines (SVMs) method in estimation monthly solar radiation using air temperature at Chongqing, China. It has been confirmed that SVMs may be an alternative to traditional approaches for the prediction of solar radiation where the records of air temperatures are available. New model for the estimation of global solar radiation using temperature has been developed after calibrating seven models for seven stations in Madrid, Spain by Almorox et al. (2011). Results have confirmed the applicability of the model at any site in Madrid, Spain with less error than other models. Nittaya Phakamas et al. (2013) have modified Bristow-Campbell model for the estimation of solar radiation from daily air temperature by using meteorological data from 2008 to 2011 of eight weather stations in Thailand. It has been concluded that, the new coefficients can be

Modeling Of Global Solar Radiation 16845 used for all locations in Thailand and similar environments in southwest Asia for evaluating solar radiation. In the present study, a correlation model has been tried for the estimation of monthly mean average solar radiation by using air temperature in two coastal cities in India Viz., Chennai and Trivandrum Long-term measured solar radiation and air temperature has been collected from Indian Meteorological Derpartment, Pune, India and used for the study. Data used Long term 10 years (2003-2013) data of daily average solar radiation and maximum and minimum ambient air temperature has been collected for Chennai and Trivandrum from Indian Meteorological Department, Pune. Monthly average solar radiation and maximum and minimum ambient air temperature has been found for each month of the year and has been used. The difference in maximum and minimum ambient air temperature has been found for each month and it has been correlated with the monthly average solar radiation for the two locations. Results and Discussion Since the ambient air temperature is measured at larger number of locations, the objective of the study is to correlate the solar radiation with the difference between maximum and minimum ambient air temperature for two Indian locations viz., Chennai,and Trivandrum. Fig. 1 shows the variation of monthly mean maximum ambient air temperature for the two locations for each month of the year. It is observed that, for Chennai the monthly average ambient air temperature gradually increases from the month of January and reaches the maximum of 37.4 C and 33.1 C on May and decreases gradually in the forthcoming months upto December. In Trivandrum, the monthly average ambient temperature reached a maximum of 32.1 C in the month of April slightly lesser than that of the other two coastal areas considered. This is due to the fact that Trivandrum is located along the path of the south-west monsoons and gets its first shower in the early June itself. Similarly Fig. 2 shows the variation of monthly mean minimum ambient air temperature for the three locations. From the graph, it is observed that the variation of minimum air temperature throughout the year for Chennai and Trivandrum, the monthly mean ambient air temperature for all the months is less than that of Chennai By using the monthly mean maximum and minimum ambient air temperature, difference between maximum and minimum ambient air temperature for all the months of the year has been found and graph has been drawn for the difference with respect to the months of the year. Fig. 3 shows the variation of difference between monthly mean maximum and minimum ambient air temperature for the three locations. It has been found that the difference is large for the month of January and December for Trivandrum and n Chennai, in the month of June the difference is large.

16846 S. Ravichandran and Dr.J. David Rathnaraj Fig. 1 Variation of monthly mean maximum ambient air temperature in Chennai and Trivandrum Fig. 2 Variation of monthly mean minimum ambient air temperature in ChennaiandTrivandrum.

Modeling Of Global Solar Radiation 16847 Fig. 3 Variation of difference between monthly mean maximum and minimum ambient air temperature with respect to the months of the year. Monthly average solar radiation for all the months of the year for Chennai and Trivandrum has been found by using long term data collected from Indian Meteorological Department, Pune and has been plotted against the months of the year and depicted in Fig. 4. From the graph it is observed that for all the locations, monthly mean solar radiation is maximum during March to May. This is due to the bright sunshine as the sky is clear during the months. Among the three locations, Chennai received large amount of solar radiation for all the months and Trivandrum received smaller amount of solar radiation compared to the other two locations. Fig. 4 Variation of monthly mean solar radiation for Chennai and Trivandrum

16848 S. Ravichandran and Dr.J. David Rathnaraj Power Correlation For Chennai The monthly mean solar radiation has been plotted against the difference between monthly mean maximum and minimum ambient air temperature and depicted in Fig. 5. In order to develop the power correlation between the parameters, trend line has been drawn and equation has been derived. The derived equation is given by Y = 0.009 X 1.386 Where Y is the monthly mean solar radiation (J/m 2 ) and X is the T max -T min ( C) R 2 value is 0.809 Trivandrum In Trivandrum Monthly mean solar radiation is plotted against the difference in maximum and minimum ambient air temperature and a trend line has been drawn for the derivation of power correlation. R 2 value has also been found for both the locations and presented. Fig. 6 and 7 shows the variation of monthly mean radiation against T max -T min ( C). The derived equations are Trivandrum Y = 0.075 X 0.399 Where Y is the monthly mean solar radiation (J/m 2 ) and X is the T max -T min ( C) R 2 value is 0.218

Modeling Of Global Solar Radiation 16849 Fig. 5 Monthly mean solar radiation against T max -T min Fig. 6 Monthly mean solar radiation against T max -T min In order to signify the closeness of the monthly mean measured and calculated solar radiation, monthly mean solar radiation for all the months for all the locations have been found by using the correlation equation derived. Graphs have been drawn for measured and calculated solar radiation for the three locations with respect to the months of the year and analyzed. Figs 7and8shows the measured and calculated solar radiation for the locations considered.

16850 S. Ravichandran and Dr.J. David Rathnaraj Fig. 7 Variation of measured and calculated monthly mean solar radiation at Chennai Fig. 8 Variation of measured and calculated monthly mean solar radiation at Trivandrum From the graphs, it has been observed that for Chennai, the measured and calculated solar radiation by using the power correlation developed has same trend and the R 2 value of 0.809 has been obtained. Hence the equation holds good for the prediction of monthly mean solar radiation at Chennai with least error. In Trivandrum, Calculated value underestimates for all the months except November and December compared to the measured solar radiation. In November and December, the calculated value of solar radiation overestimates. calculated value overestimate the solar radiation intensity. Since the trends of the measured and calculated monthly mean solar radiation are different, R 2 value of 0.008 has been found and is very small. The power correlation developed for the location correlating the monthly mean solar radiation and difference of maximum and minimum monthly mean ambient air temperature did not suit.

Modeling Of Global Solar Radiation 16851 Table. 1 shows the measured and calculated monthly mean solar radiation for all the months of the year for Chennai and Trivandrum. Table.1 Measured and calculated monthly mean solar radiation at Chennai, and Trivandrum Month Chennai Monthly mean Solar Radiation Trivandrum Monthly mean Solar Radiation Measured Calculated Measured Calculated January 0.1644 0.171907 0.175 0.174491 February 0.1929 0.200908 0.1877 0.173649 March 0.2303 0.206857 0.1998 0.169344 April 0.2124 0.18625 0.1837 0.161151 May 0.2204 0.212854 0.1517 0.154315 June 0.2131 0.21587 0.1604 0.14699 July 0.1743 0.195008 0.1449 0.14699 August 0.1666 0.189157 0.1471 0.14807 September 0.1804 0.180475 0.1631 0.153301 October 0.1602 0.149641 0.1584 0.152276 November 0.1335 0.128263 0.1321 0.156314 December 0.1279 0.138837 0.1288 0.167576 The standard Deviation between measured and calculated monthly mean solar radiation has been found for all the months of the year for Chennai and Trivandrum. Average standard deviation has been calculated and is 0.008574and 0.009756 for Chennai and Trivandrum respectively. It can be seen that, the average standard deviation for Chennai is small when compared to the other two locations and the power correlation predicts the monthly mean solar radiation with least error. The correlation did not suit for the other two locations since it predicts the monthly mean solar radiation with large error. Conclusion Monthly mean solar radiation and maximum and minimum ambient air temperature data are important in designing and implementation of solar thermal and photovoltaic devices. Difference in monthly mean maximum and minimum ambient air temperature and monthly mean solar radiation has been correlated to derive power correlation for the prediction of monthly mean solar radiation for Chennaiand Trivandrum. The developed equation for Chennai has shown good correlation with much less error whereas the equation underestimates and overestimates monthly mean solar radiation at Trivandrum. Hence the power correlation for Chennai can be used for the prediction of monthly mean solar radiation with known values of the difference in maximum and minimum ambient air temperature.

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