Estimating Daily Solar Radiation Using Hargreaves Model in Eastern Malaysia

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This paper presents the forecasting of solar radiation in Kelantan, Eastern Malaysia for the year of 2011 using Hargreaves model. This estimation is based on latitude and daily minimum and maximum temperature in Kelantan. The measured and estimated solar radiation data were compared for the year 2011 and analyzed using coefficient of residual mass (CRM), root mean squared error (RMSE), coefficient of determination (R2) and percentage error (e). The results showed that the value of CRM is 0.09, it indicates the tendency of the estimation model to under-estimate the measure solar radiation. Meanwhile, the value of RMSE is 8.21% and the value of R2 is 0.8661, closed to 1 indicates that about 86.61% of the total variation is explained in the data. For the e, the value is 7.98%, it indicates that the model estimation is good.

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November 2014

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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[1] L. E. Akpabio, S. O. UDO, S. E, Etuk, 2004. Empirical correlations of global solar radiation with meteorological data for Onne, Nigeria. Turk. J. Physics. 28 (2004) 205 – 212.

Google Scholar

[2] O. A. Bamiro, Empirical relations for the determination of solar radiation in Ibadan, Nigeria, Sol. Energy. 31(1983) 85 – 94.

DOI: 10.1016/0038-092x(83)90038-5

Google Scholar

[3] B. Golderg, WH. Klein, RD. McCartney, A comparison of some simple models used to predict solar irradiance on a horizontal surface, Solar Energy. 23 (1979) 81-83.

DOI: 10.1016/0038-092x(79)90047-1

Google Scholar

[4] L. A. Hunt, L. Kuchar, C. J. Swanton, Estimation of solar radiation for use in crop modelling. Agric Forest Meteorol. 91(1998) 293-300.

DOI: 10.1016/s0168-1923(98)00055-0

Google Scholar

[5] G. H. Hargreaves, Z. A. Samani, Estimating potential evaporation. J. Irrig. Drain. Eng. 108 (1982) 225 –230.

Google Scholar

[6] H. Meinke, P.S. Carberry, M. R. McCaskill, M. A. Hills, I. McLeod, Evaluation of radiation and temperature data generators in the Australian tropics and sub-tropics using crop simulation models. Agric Forest Meteorol. 72 (1995) 295- 316.

DOI: 10.1016/0168-1923(94)02159-h

Google Scholar

[7] F. Meza, E. Varas, Estimation of mean monthly solar global radiation as a function of temperature. Agric Forest Meteorol. 100 (2000) 231-241.

DOI: 10.1016/s0168-1923(99)00090-8

Google Scholar

[8] X. Yin, Evaluation of solar irradiance models with a special reference to globally-parameterized and land cover sensitive Solar 123, Theor Appl Climatol. 64 (1999a) 249-261.

DOI: 10.1007/s007040050127

Google Scholar

[9] X. Yin, Sunshine duration in relation to precipitation, air temperature and geographic location. Theor Appl Climatol. 64 (1999b) 61-68.

Google Scholar

[10] J. Almorox, C. Hontoria, Global solar radiation estimation using sunshine duration in Spain. Energy Conversion & Management. 45 (2003) 1529–1535.

DOI: 10.1016/j.enconman.2003.08.022

Google Scholar

[11] A. Bandyopadhyay, A. Bhadra, N. S. Raghuwanshi, R. Singh, Estimation of monthly solar radiation from measured air temperature extreme. Agricultural and Forest Meteorology. 148 (2008) 1707–1718.

DOI: 10.1016/j.agrformet.2008.06.002

Google Scholar

[12] R. Chen, K. Ersi, J. Yang, S. Lu, W. Zhao, Validation of five global radiation models with measured daily data in China, Energy Conversion & Management. 45 (2003) 1759–1769.

DOI: 10.1016/j.enconman.2003.09.019

Google Scholar

[13] R. Chen, E. Kang, L. Lu, New methods to estimate global radiation based on meteorological data in China, Energy Conversion & Management. 47 (2006) 2991–2998.

DOI: 10.1016/j.enconman.2006.03.025

Google Scholar

[14] T.C. Chineke, Equation for estimating global solar radiation in data sparese regions. Renewable Energy 33 (2007) 827–831.

DOI: 10.1016/j.renene.2007.01.018

Google Scholar

[15] I. Daut, M. Sembiring, M. Irwanto, N. Syafawati, S. Hardi, Solar radiation potential for photovoltaic power generation based on meteorological data in Perlis, International Conference: Electrical Energy and Industrial Electronic Systems EEIES, (2009).

Google Scholar

[16] A. Itagaki, H. Okamura, M. Yamada, Preparation of meteorological data set throughout Japan for suitable design of PV Systems, 3rd World Conference on Photovoltaic Energy Conversion. (2003) 2074–(2077).

Google Scholar

[17] T. Markvart, Solar Electricity. John Wiley & Sons, LTD, New York, 1994, p.5–19.

Google Scholar

[18] A. Mellit, S.A. Kalogirou, S. Shaari, H. Salhi, A.H. Arab, Methodology for predicting sequences of mean monthly learness index and daily solar radiation data in remote areas application for sizing a stand-alone PV system. Renewable Energy. 33 (2007).

DOI: 10.1016/j.renene.2007.08.006

Google Scholar

[19] H.O. Menges, C. Ertekin, M.H. Sonmete, Evaluation of global solar radiation models for Konya, Turkey. Energy Conversion & Management. 47 (2006) 3149–3173.

DOI: 10.1016/j.enconman.2006.02.015

Google Scholar

[20] P. Gavalian, I.J. Lorite, S. Tornero, J. Berengena, Regional calibration of Hargreaves equation for estimating reference ET in a semiarid environment. Agricultural Water Management. 81 (2005) 257–281.

DOI: 10.1016/j.agwat.2005.05.001

Google Scholar

[21] I. Supit, R.V. Kappel, A simple method to estimate global radiation. Solar Energy. 63 (1998) 147–159.

DOI: 10.1016/s0038-092x(98)00068-1

Google Scholar

[22] Malaysian Timber Council, Malaysia: Sustainable Forest Management (2007).

Google Scholar

[23] J.A. Engel-Cox, N.L. Nair, and J.L. Ford. Evaluation of Solar and Meteorological Data Relevant to Solar Energy Technology Performance in Malaysia. Journal of Sustainable Energy & Environment. 3 (2012) 115-124.

Google Scholar