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Equations for estimating global solar radiation in data sparse regions

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  • Chineke, Theo Chidiezie

Abstract

The knowledge of the amount of solar radiation in an area/region is very essential in the field of Solar Energy Physics. In this work two equations are put forward for estimating global solar radiation from common climate variables in data sparse regions. The first is the Hargreaves equation, Rs=0.16RaTd0.5 where Ra is the extraterrestrial solar radiation and Td is the temperature difference (maximum minus minimum), while the second is the Angstrom equation, Rs=Ra(0.28+0.39n/N) where n and N are the measured sunshine hours and the maximum daylight duration respectively. The global solar radiation estimated by the two equations for three sites, Owerri (5°28′N, 7°2′E), Umudike (5°29′N, 7°33′E) and Ilorin (8°32′N, 4°46′E), located in different climate zones of in Nigeria, West Africa, are in agreement with those of earlier workers and that from Photovoltaic Geographic Information System (PVGIS) project. The implication of this in solar photovoltaic applications has been stressed.

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  • Chineke, Theo Chidiezie, 2008. "Equations for estimating global solar radiation in data sparse regions," Renewable Energy, Elsevier, vol. 33(4), pages 827-831.
    • Handle: RePEc:eee:renene:v:33:y:2008:i:4:p:827-831
    DOI: 10.1016/j.renene.2007.01.018
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    1. Udo, S.o. & Aro, T.o., 1999. "Technical note Measurement of global solar global photosynthetically-active and downward infrared radiations at Ilorin, Nigeria," Renewable Energy, Elsevier, vol. 17(1), pages 113-122.
    2. Adeoti, O. & Oyewole, B.A. & Adegboyega, T.D., 2001. "Solar photovoltaic-based home electrification system for rural development in Nigeria: domestic load assessment," Renewable Energy, Elsevier, vol. 24(1), pages 155-161.
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    1. Gao, Yuan & Miyata, Shohei & Akashi, Yasunori, 2022. "Multi-step solar irradiation prediction based on weather forecast and generative deep learning model," Renewable Energy, Elsevier, vol. 188(C), pages 637-650.
    2. Dos Santos, Cícero Manoel & De Souza, José Leonaldo & Ferreira Junior, Ricardo Araujo & Tiba, Chigueru & de Melo, Rinaldo Oliveira & Lyra, Gustavo Bastos & Teodoro, Iêdo & Lyra, Guilherme Bastos & Lem, 2014. "On modeling global solar irradiation using air temperature for Alagoas State, Northeastern Brazil," Energy, Elsevier, vol. 71(C), pages 388-398.
    3. Chineke, Theo Chidiezie & Okoro, Ugochukwu Kingsley, 2010. "Application of Sayigh “Universal Formula” for global solar radiation estimation in the Niger Delta region of Nigeria," Renewable Energy, Elsevier, vol. 35(3), pages 734-739.
    4. Pang, Zhihong & Niu, Fuxin & O’Neill, Zheng, 2020. "Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons," Renewable Energy, Elsevier, vol. 156(C), pages 279-289.
    5. Adaramola, Muyiwa S., 2012. "Estimating global solar radiation using common meteorological data in Akure, Nigeria," Renewable Energy, Elsevier, vol. 47(C), pages 38-44.
    6. Khatib, Tamer & Mohamed, Azah & Sopian, K., 2012. "A review of solar energy modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2864-2869.
    7. Khalil, Samy A. & Shaffie, A.M., 2013. "A comparative study of total, direct and diffuse solar irradiance by using different models on horizontal and inclined surfaces for Cairo, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 853-863.
    8. Giwa, Adewale & Alabi, Adetunji & Yusuf, Ahmed & Olukan, Tuza, 2017. "A comprehensive review on biomass and solar energy for sustainable energy generation in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 620-641.
    9. Li, Huashan & Lian, Yongwang & Wang, Xianlong & Ma, Weibin & Zhao, Liang, 2011. "Solar constant values for estimating solar radiation," Energy, Elsevier, vol. 36(3), pages 1785-1789.
    10. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
    11. Ozoegwu, C.G. & Mgbemene, C.A. & Ozor, P.A., 2017. "The status of solar energy integration and policy in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 457-471.
    12. Dike, V.N. & Chineke, T.C. & Nwofor, O.K. & Okoro, U.K., 2012. "Optimal angles for harvesting solar electricity in some African cities," Renewable Energy, Elsevier, vol. 39(1), pages 433-439.
    13. Jose Manuel Barrera & Alejandro Reina & Alejandro Maté & Juan Carlos Trujillo, 2020. "Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    14. Amrouche, Badia & Le Pivert, Xavier, 2014. "Artificial neural network based daily local forecasting for global solar radiation," Applied Energy, Elsevier, vol. 130(C), pages 333-341.

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