Published January 22, 2021 | Version v1
Journal article Open

Prediction of daily global solar radiation using different empirical models at eastern subtropical region, Nepal

Creators

  • 1. Department of Mechanical Engineering, IOE Pulchowk Campus, TU, Nepal
  • 2. Department of Physics, Patan Multiple Campus, TU, Nepal
  • 3. Department of Applied Sciences and Chemical Engineering, IOE Pulchowk Campus, TU, Nepal

Description

The current study estimates the daily global solar radiation (GSR) at subtropical region of eastern Nepal at Biratnagar Airport (lat. 26°28′53″N, long. 87°15′50″E and Alt. 72m) for 2016 using measured GSR values and meteorological parameters from 2015. The maximum of measured GSR of magnitude 15.9 MJ/m2/day was found in April while the minimum of magnitude 8.7 MJ/m2/day was found in January. Meteorological parameters such as the temperature and their relation with the GSR were utilized for this comparative study. Temperature-based multi-variable linear empirical models were used to perform regression analysis and determine the regression coefficients. The calculated regression coefficients from these models were utilized to predict the GSR values for subsequent year. The variation in the GSR estimated from these models were compared. Variation between measured GSR and estimated GSR for 2015 was also studied for each of these models. Performance comparison of these models was carried out by employing mean bias error (MBE), relative root mean square error (RRMSE) and adjusted coefficient of determination (R2). Such study is relevant in situations where reliable data for sunshine duration is not adequately available. The Falayi model has the highest adjusted R2 value of 0.61 but the largest MBE of 14.1%. The Garcia model has least adjusted R2 value of 0.55 but least MBE of 6.6%. Both the Garcia and Chen and Li model predict similar GSR value of 12.8 and 12.5 MJ/m2/day.

Files

IRJEvS_Prediction of daily global solar radiation using different empirical models at eastern sub tropical region, Nepal.pdf

Files (466.0 kB)

Additional details

References

  • Karanth, V. (2007). Modernization and global warming. Current Science, 93, 7–8.
  • WECS (2010). Energy Sector Synopsis Report 2010, Water and Energy Commission Secretariat, Kathmandu, Nepal, pp 1-98.
  • Fadare, D. A. (2009). Modelling of solar energy potential in Nigeria using an artificial neural network model. Applied Energy, 86(9), 1410–1422. https://doi.org/ 10.1016/ j.apenergy.2008.12.005
  • Amrouche, B.,& le Pivert, X. (2014). Artificial neural network based daily local forecasting for global solar radiation. Applied Energy, 130, 333–341. https://doi.org/10.1016/j.apenergy.2014.05.055
  • Besharat, F., Dehghan, A. A., & Faghih, A. R. (2013). Empirical models for estimating global solar radiation: A review and case study. Renewable and Sustainable Energy Reviews, 21, 798–821. https://doi.org/10.1016/ j.rser.2012.12.043
  • Chen, J. L., He, L., Yang, H., Ma, M., Chen, Q., Wu, S. J., & Xiao, Z.L. (2019). Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China. Renewable and Sustainable Energy Reviews, 108, 91–111. https://doi.org/10.1016/j.rser.2019.03.033
  • Voyant, C., Darras, C., Muselli, M., Paoli, C., Nivet, M. L., & Poggi, P. (2014). Bayesian rules and stochastic models for high accuracy prediction of solar radiation. Applied Energy, 114, 218–226. https://doi.org/10.1016/ j.apenergy.2013.09.051
  • Pinker, R. T., Frouin, R., & Li, Z. (1995). A review of satellite methods to derive surface shortwave irradiance. Remote Sensing of Environment, 51(1),108–124.
  • Feng, Y., Gong, D., Jiang, S., Zhao, L., & Cui, N. (2020). National-scale development and calibration of empirical models for predicting daily global solar radiation in China. Energy Conversion and Management, 203, 112236. https://doi.org/10.1016/j.enconman.2019.112236
  • Bajracharya, S.R., Shrestha, M.S., & Shrestha, A.B. (2017). Assessment of high-resolution satellite rainfall estimation products in a streamflow model for flood prediction in the Bagmati basin, Nepal. Journal of Flood Risk Management, 10(1), 5–16. https://doi.org/10.1111/jfr3.12133
  • Martinez-lozano, J., Tena, F., Onrubia, J., & la Rubia, J. de. (1984). The historical evolution of the Angstrom formula and its modifications: Review and bibliography. Agriculture and Forest Meteorology, 33(2–3), 109–128.https://doi.org/10.1016/0168-1923(84)90064-9
  • Poudyal, K.N. (2015). Estimation of global solar radiation using Modified Angstrom empirical formula on the basis of meteorological parameters in Himalaya Region Pokhara, Nepal. Journal of the Institute of Engineering, 11(1), 158–164.
  • Awasthi, J., & Poudyal, K.N. (2018). Estimation of global solar radiation using empirical model on meteorological parameters at Simara Airport, Bara, Nepal. Journal of the Institute of Engineering, 14(1), 143–150.
  • Makade, R.G., Chakrabarti, S., & Jamil, B. (2019). Prediction of global solar radiation using a single empirical model for diversified locations across India. Urban Climate, 29, 100492. https://doi.org/10.1016/ j.uclim.2019.100492
  • Srivastava, R.C., & Pandey, H. (2013). Estimating Angstrom-Prescott coefficients for India and developing a correlation between sunshine hours and global solar radiation for India. ISRN Renewable Energy, 1–7. https://doi.org/10.1155/2013/403742
  • Despotovic, M., Nedic, V., Despotovic, D., &Cvetanovic, S. (2015). Review and statistical analysis of different global solar radiation sunshine models. Renewable and Sustainable Energy Reviews,52,1869–1880. https://doi.org/10.1016/j.rser.2015.08.035
  • Trnka, M., Žalud, Z., Eitzinger, J., &Du rovský, M. ( ). Global solar radiation in Central European lowlands estimated by various empirical formulae. Agricultural and Forest Meteorology, 131(1–2), 54–76. https://doi.org/ 10.1016/j.agrformet.2005.05.002
  • Mecibah, M.S., Boukelia, T.E., Tahtah, R., &Gairaa, K. (2014). Introducing the best model for estimation the monthly mean daily global solar radiation on a horizontal surface (Case study: Algeria). Renewable and Sustainable Energy Reviews, 36,194–202. https://doi.org/ 10.1016/ j.rser.2014.04.054
  • Podestá, G.P., Núñez, L., Villanueva, C.A., &Skansi, M.A. (2004). Estimating daily solar radiation in the Argentine Pampas. Agricultural and Forest Meteorology, 123(1–2), 41–53. https://doi.org/10.1016/j.agrformet.2003.11.002
  • Hargreaves, G.H., &Samani, Z.A. (1982). Estimating potential evapotranspiration. Journal of Irrigation and Drainage Division, 108(3), 225–230.
  • Hassan, G.E., Youssef, M.E., Mohamed, Z.E., Ali, M.A., & Hanafy, A.A. (2016). New temperature-based models for predicting global solar radiation. Applied Energy, 179, 437–450. https://doi.org/10.1016/j.apenergy.2016.07.006
  • Li, M.F., Tang, X.P., Wu, W., & Liu, H.B. (2013). General models for estimating daily global solar radiation for different solar radiation zones in mainland China. Energy Conversion and Management,70,139–148. https://doi.org/ 10.1016/j.enconman.2013.03.004
  • Goodin, D.G., Hutchinson, J.M.S., Vanderlip, R.L., & Knapp, M.C. (1999). Estimating solar irradiance for crop modeling using daily air temperature data. Agronomy Journal,91(5),845–851. American Society of Agronomy. https://doi.org/10.2134/agronj1999.915845x
  • Fan, J., Chen, B., Wu, L., Zhang, F., Lu, X., & Xiang, Y. (2018). Evaluation and development of temperature-based empirical models for estimating daily global solar radiation in humid regions. Energy, 144, 903–914. https://doi.org/ 10.1016/j.energy.2017.12.091
  • Falayi, E., Adepitan, J., &Rabiu, A. (2008). Empirical models for the correlation of global solar radiation with meteorological data for Iseyin, Nigeria. International Journal of Physical Sciences, 3(9), 210–216.
  • Garcia, J.V. (1994). PrincipiosFisicos de la Climatologia, Ediciones. UNALM (Universidad Nacional Agraria La Molina: Lima, Peru.
  • Chen, J.L., & Li, G.S. (2013). Estimation of monthly average daily solar radiation from measured meteorological data in Yangtze River Basin in China. International Journal of Climatology, 33,487–498. https://doi.org/ 10.1002/joc.3442
  • John A. Duffie and William A. Beckman (2013). Solar engineering of thermal processes, John Wiley & Sons, Hoboken, New Jersey, pp 3-41. ISBN: 978-1-118-43348-5
  • Cooper, P.I. (1969). The absorption of radiation in solar stills. Solar Energy, 12(3), 333–346.https://doi.org/ 10.1016/0038-092X(69)90047-4