Microsoft Word - CST - 265 - REVISED - ACCEPTED - FINAL © Applied Science Innovations Pvt. Ltd., India Carbon – Sci. Tech. 10/1(2018)1-6 1 RESEARCH ARTICLE Received: 15/3/2018, Accepted: 24/4/2018 ------------------------------------------------------------------------------------------------------------------------- Estimation of the monthly average global and diffuse solar radiation for the city Bareilly, Uttar Pradesh, India Akanksha Varshney, K. Namrata, and Bhushan Mahajan Department of Electrical Engineering, National Institute of Technology, Jamshedpur, India. Abstract: This paper presents a process to develop the monthly global and diffused solar radiation data for the city Bareilly, Uttar Pradesh in order to exploit the solar energy available at the location throughout the year. It is located in the northern zone of Uttar Pradesh at 28.367°N latitude and 79.4304°E longitude at an elevation of 268 meters. The values of monthly average global solar radiation are calculated using the regression constants in the model provided by Gopinathan. Kreith and Gupta model has been used for estimating the values of monthly average diffuse solar radiation. The calculated data has been analyzed and the result has been simulated through matlab. Keywords: Solar constant, solar day length, Bareilly, Uttar Pradesh ------------------------------------------------------------------------------------------------------------------------------------- 1. Introduction: Solar energy is a very large, inexhaustible and environmentally clean source of energy. It is sufficient to meet all the present and future energy demands of the world [1]. A number of technologies have been developed to harness its potential. Solar radiation data provides information of how much the sun's energy strikes the surface at a place on earth during a particular period [2]. Such data is available for most of the developed countries of the world. India, being a tropical country receives adequate amount of sunshine for most of the time of the year but the parameters are measured only in a few meteorological stations. Hence to recognize its true potential, data should be available for each and every corner of the country. For places where it is not directly measured, solar radiation data can be estimated by using models and empirical correlation [3]. Presently, global solar radiation in India is measured at four work stations namely Delhi, Kolkata, Mumbai and Chennai [4-5].Bareilly is the eighth largest metropolis in Uttar Pradesh and the 50thlargest city in India. It occupies an area of 4120 sq km and receives good amount of sunshine throughout the year [6-7]. Solar radiation estimation can unlock the potential of solar energy making it a viable option for developing energy for this place. 2. Methodology: The Angstrom correlation has served as a basic approach to estimate global radiation for a long time. He was the first to relate the amount of sunshine received at a place, by a linear relation given as [8-9] – = 𝑎 + 𝑏 ̅ ̅ (1) where 𝐻 is the monthly average daily global solar radiation received on a horizontal surface (MJm-2day-1), 𝐻 is the monthly average daily extraterrestrial radiation on a horizontal surface (MJm-2day-1), a and b are regression constants, S is the monthly average daily number of hours of bright sunshine, 𝑆̅ is the monthly average daily maximum number of hours of possible sunshine. The value of 𝐻 is calculated as: 𝐻 = 𝐼 (1 + 0.033𝑐𝑜𝑠 )(⍵ 𝑠𝑖𝑛𝜑 𝑠𝑖𝑛𝛿 + 𝑐𝑜𝑠𝜑 𝑐𝑜𝑠𝛿 𝑠𝑖𝑛𝜔 ) (2) ASI Carbon – Science and Technology ISSN 0974 – 0546 http://www.applied-science-innovations.com © Applied Science Innovations Pvt. Ltd., India Carbon – Sci. Tech. 10/1(2018)1-6 2 where Isc is the solar constant having value of 1367 W/m2, n is the average number of days in a month, φ is the latitude of the location, δ is the declination angle calculatedas: 𝛿 = 23.45 sin ( ) (3) and ωs is the sunset hour angle given as: 𝜔 = cos (−𝑡𝑎𝑛𝛿 𝑡𝑎𝑛𝜑) (4) Considering the value of ωs in degree, the value of 𝑆 is calculated as 𝑆̅ = (5) Gopinathan considered the effects of latitude, elevation and established the following equation to calculate regression coefficients a and b of the Angstrom type correlation for global radiation [10] 𝑎 = −0.309 + 0.539 cos 𝜑 − 0.0693 ℎ + 0.29 ̅ ̅ (6) 𝑏 = 1.527 − 1.027 cos 𝜑 + 0.0926ℎ − 0.359 ( ̅ ̅ ) (7) where h is the elevation of the place. Usually (a+b) has values in the range of 0.6 for a moist and turbid atmosphere and 0.85 for a dry and dust free atmosphere [11-12]. The diffuse radiation 𝐻 can be estimated by an empirical formula illustrated in equation (8) which correlates the diffuse solar radiation component 𝐻 to the global solar radiation 𝐻 . This linear expression was obtained when the available Indian data was analyzed [13]. = 1.411 − 1.696 [ ] (8) The ratio 𝐻 𝐻⁄ is denoted by 𝐾 and is called the monthly average clearness index [14]. This parameter indicates the degree of clearness of the atmosphere. 3. Results and discussion: The monthly average global solar radiation for the city Bareilly has been calculated by the above provided Gopinathan Model while Kreith and Gupta model has been used for estimation of diffuse radiation. Table 1 shows the calculated values of input parameters for estimation of both global and diffuse radiation. Table (1): Calculated values of Input Parameters for the city Bareilly. Month n (starting from 1st anuary) δ (in degrees) ωs (in radians) January 16 -21.0963 1.3609 February 45 -13.6198 1.4396 March 75 -2.4177 1.5480 April 105 9.4149 1.6604 May 136 19.0306 1.7581 June 166 23.3144 1.8057 July 197 21.3537 1.7835 August 228 13.4550 1.7003 September 258 2.2169 1.5917 October 289 -9.9663 1.4758 November 319 -19.1478 1.3822 December 350 -23.3717 1.3353 © Applied Science Innovations Pvt. Ltd., India Carbon – Sci. Tech. 10/1(2018)1-6 3 Table (2) depicts the values of monthly average daily number of hours of bright sunshine (𝑆̅), monthly average daily maximum number of hours of possible sunshine (𝑆̅ .) and monthly average daily extraterrestrial radiation (𝐻 ). The regression constant values vary all over the year due to the variation in possible sunshine hour ratio. The approximate values ofa andb for Bareilly can be obtained as 0.3371 and 0.4124 respectively. Table (2): Values of regression coefficient and clearness index for Bareilly, Uttar Pradesh. Month (in hour) (in hour) (MJ/m2-day) January 7.4000 10.3969 22.1175 February 8.1000 10.9977 26.4281 March 8.4000 11.8258 32.1668 April 9.5000 12.6849 37.0668 May 9.1000 13.4312 40.0242 June 7.3000 13.7942 40.9703 July 5.4000 13.6249 40.3815 August 5.8000 12.9896 38.0589 September 7.1000 12.1597 33.8469 October 8.9000 11.2741 28.1112 November 8.6000 10.5592 23.1223 December 7.5000 10.2008 20.7070 In Table (3), the values calculated for monthly global solar radiation ( ), diffuse solar radiation ( ) and clearness index ( ) have been shown. Table (3): Complete Solar Radiation Data for Bareilly, Uttar Pradesh, India Month (MJ/m2-day) (MJ/m2-day) January 13.9906 4.7313 0.6326 February 16.9911 5.4475 0.6429 March 20.3276 6.8956 0.6319 April 24.0171 7.4956 0.6479 May 24.7159 8.9887 0.6175 June 22.2319 10.9090 0.5426 July 18.6614 11.7050 0.4621 August 18.8018 10.7762 0.4940 September 19.3633 8.5343 0.5721 October 18.6537 5.5273 0.6636 November 15.5529 4.2025 0.6726 December 13.3020 4.2766 0.6424 In Figure (1, 2 and 3), the values calculated for , and , have been plotted respectively, after simulation through matlab. © Applied Science Innovations Pvt. Ltd., India Carbon – Sci. Tech. 10/1(2018)1-6 4 Figure (1): Monthly variation of global solar radiation for Bareilly. Figure (2): Monthly variation of diffuse solar radiation for Bareilly. © Applied Science Innovations Pvt. Ltd., India Carbon – Sci. Tech. 10/1(2018)1-6 5 Figure (3): Monthly variation of clearness index for Bareilly. 4. Conclusions: Results have shown that the maximum and minimum values of global solar radiation are obtained in the month of May and December respectively. The maximum and minimum values of diffuse solar radiation are obtained in the month of July and November respectively. The sky over Bareilly is clear for most of the months except for July and August, when the clearness index is less than 50%. Hence, May is the most appropriate month for using solar energy in Bareilly city as it receives the maximum amount of solar radiation in this month. The data that has been calculated through this work may play vital role in solving the energy crisis problem in Bareilly by the solar energy conversion process. References: 1. S. P. Sukhatme, Energy Principles of Thermal Collection and Storage, 2nd edition, 1997, Tata McGraw-Hill, New Delhi, India. 2. B. Y. H. Liu&R. C. Jordan, ‘The interrelationship and characteristic distribution of direct diffuse and total solar radiation’, Solar energy 4/3 (1960) 1-19. 3. K. Namrata, S. P. Sharma,S. B. Saksena, ‘Comparison of different models for estimation of global solar radiation in Jharkhand (India) region’, Smart grid and renewable energy4(2013) 348-352. 4. A. K. Rajput, R. K. Tiwari,A. Sharma, ‘Utility based estimated solar radiation at destination Pune in Maharashtra (India)’, Int. J. Pure Appl. Sci. Technol. 13(2012) 19-26. 5. A. K. Rajput, D. V. Avasthi,D. Kumar, ‘Variation of estimated insolation from east to west in Uttar Pradesh (India)’, CIPEH(2014) 390-394. 6. http://www.censusindia.gov.in/2011census/dchb/0919_PART_B_DCHB_BAREILLY 7. https://www.weather2visit.com/asia/india/bareilly-december.htm 8. A. Angstrom,‘Solar and terrestrial radiation’, Quarter Jourtnal of Royal Meteorological Society 50(1924) 121-125. 9. J. A. Duffieand W. A. Beckman, Solar Engineering of Thermal Processes, 2nd edition, 1991, New York: John Wiley & Sons Inc. © Applied Science Innovations Pvt. Ltd., India Carbon – Sci. Tech. 10/1(2018)1-6 6 10. K. K. Gopinathan, ‘A new model for estimating total solar radiation’, Solar and Wind Technology 5 (1988) 107-109. 11. A. Mani and S. Rangarajan, Solar radiation over India, 1982, Allied Publishers, New Delhi, India. 12. S. S.Chandel, R. K. Aggarwal, andA. N. Pandey, ‘New correlation to estimate global solar radiation on horizontal surfaces using sunshine hour and temperature data for Indian sites’, ASME 127(2005) 417 - 420. 13. V. ModiandS. P. Sukhatme,‘Estimation of daily, total and diffuse insolation in India from weather data’, Solar Energy22 (1979) 407. 14. F. Kreith and J. F. Kreider, Principles of Solar Engineering, 1978, McGraw-Hill, New York. Author’s biography: Akanksha Varshney has graduated in Electrical Engineering from Rajkiya Engineering College, Banda in Uttar Pradesh in the year 2017. Currently she is pursuing her Master's degree in Power System Engineering from National Institute of Technology, Jamshedpur in Jharkhand. Her research interests are in the field of Power System and Renewable Energy Systems. K. Namrata holds a degree in Renewable Energy Technologies in which her research topic was based on Solar Radiation and its effect Solar Power Generation Technology. Currently she is an Assistant Professor in the department of Electrical and Electronics Engineering at N.I.T. Jamshedpur, India. Bhushan Mahajan received B. Tech (Electrical Engineering) degree from Dr. Babasaheb Ambedkar Technological University, Maharashtra, India in 2016. Currently, he is pursuing his M. Tech (Power Electronics and Drives) from NIT Jamshedpur, India. His main research interests are power electronics, renewable energy systems and smart grids. *****