Empirical models for estimating the global solar radiation based on air temperature and sunshine duration

Benamrou, Badr; Ouardouz, Mustapha; Allaouzi, Imane; Ahmed, Mohamed Ben

doi:10.1145/3286606.3286856

Cited by 4 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Quansah et al (2014) evaluated the performance of various models for estimating global solar radiation in Ghana and other tropical regions, and found that models using S and Ta parameters had the smallest values of MBE, MPE, and RMSE. Benamrou et al (2018) evaluated 10 prediction models of global solar radiation for sunshine duration and temperature, as well as a newly proposed functional model of Fourier series. The results show that the proposed model is more accurate with smaller errors and the best coefficient of determination.…”

Section: Introductionmentioning

confidence: 99%

“…,Akinnawo et al (2016),Okundamiya and Emagbetere (2016),Sarkar and Sifat (2016),Mohammadi et al (2016),Coulibaly and Ouedraogo. (2016),Liu et al (2016),Gong et al (2016),Yang et al (2016),Olomiyesan and Oyedum (2016), Namrata et al (2016), Ayodele and Ogynjuyigbe (2017), Soulouknga et al (2017a), Achour et al (2017), Soulouknga et al (2017b), Bakirci (2017), Kalogirou et al (2017), Cao et al (2017), Yaniktepe et al (2017),Aoun and Bouchouicha (2017),Benamrou et al (2018),Yıldırım et al (2018),Kaplan (2018), Siva Krishna Rao et al (2018,Gouda et al (2018),Chala (2018),Uckan and Khudhur (2018),Kada et al (2018),Pereira and Schiebelbein (2018),Zhang et al (2018),Mbiaké et al (2018),Akpootu et al (2019),Ishola et al (2019),Khan and Ahmad (2019),Makade et al (2019), Manju…”

mentioning

confidence: 99%

See 1 more Smart Citation

The applicability of sunshine-based global solar radiation models modified with meteorological factors for different climate zones of China

et al. 2023

View full text Add to dashboard Cite

With the development of renewable energy, the exploitation and utilization of solar energy resources also need continuous progress, but solar radiation data shortage has become a serious concern. A method for estimating global solar radiation has been developed to address this issue. The sunshine-based model is currently the most widely used model due to its high calculation accuracy and few input parameters. This paper will first review 13 subcategories (8 categories in total) of the global solar radiation prediction model based on sunshine. Subsequently, the astronomical factors were introduced to modify empirical coefficients, and 8 new categories of models based on sunshine rate were introduced. The radiation data from 83 meteorological stations in China was used to train and validate the model, and the performance of the model was evaluated by using evaluation indicators, such as coefficient of determination (R2), root mean square error (RMSE), mean absolute bias error (MABE), mean bias error (MBE), and global performance index (GPI). The results show that the R2 value of the unmodified empirical model is in a range of 0.82–0.99, and the RMSE value is in a range of 0.018–3.09. In contrast, with the introduction of the astronomical factor, the model accuracy improves significantly, and the modified power function model (N3) gains its best performance. The R2 of model N3 is in a range of 0.86–0.99, and the RMSE value is in a range of 0.018–2.62. The R2 increases by 0.49%, while the RMSE value 6.44%. Above all, it does not require the input of other meteorological parameters for predicting the value of global solar radiation.

show abstract

Section: Introductionmentioning

confidence: 99%