Estimation of mean monthly global solar radiation using sunshine hours for Nairobi City, Kenya

Onyango, Augustine Omondi; Ongoma, Victor

doi:10.1063/1.4930530

Cited by 22 publications

(12 citation statements)

References 37 publications

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“…Garg [46 Rietveld [29] Continue on the next page Afungchui and Neba [114] Continue on the next page Ayodele and Ogunjuyigbe [124] H/H 0 = 0.292+ 0.284 (S/S 0 ) +0.211 (S/S 0 ) 2 Katiyar et al [15] H/H 0 = -0.197+ 0.177 (S/S 0 ) -0.912 (S/S 0 ) 2 Katiyar et al [15] H/H 0 = 0.129+ 0.933 (S/S 0 ) -0.503 (S/S 0 ) 2 Katiyar et al [15] H/H 0 = 0.234+ 0.465 (S/S 0 ) -0.043 (S/S 0 ) 2 Katiyar et al [15] H/H 0 = 0.184+ 0.845 (S/S 0 ) -0.280 (S/S 0 ) 2 Almorox et al [16] H/H 0 = 0.181+ 0.895 (S/S 0 ) -0.361 (S/S 0 ) 2 Akinoglu et al [125] H/H 0 = 0.222+ 0.705 (S/S 0 ) -0.217 (S/S 0 ) 2 Ogelman [30] H/H 0 = 1.111-1.828 (S/S 0 ) +1.660 (S/S 0 ) 2 Ogelman [30] H/H 0 = 0.168+ 0.835 (S/S 0 ) +0.320 (S/S 0 ) 2 Ogolo [90] H/H 0 = 0.154+ 0.933 (S/S 0 ) +0.370 (S/S 0 ) 2 Ogolo [90] H/H 0 = 0.719-1.067 (S/S 0 ) +1.145 (S/S 0 ) 2 Ogolo [90] H/H 0 = 0.339+ 0.287 (S/S 0 ) +0.119 (S/S 0 ) 2 Singh et al [5] H/H 0 = 0.154+ 1.172 (S/S 0 ) -0.705 (S/S 0 ) 2 Aras et al [94] H/H 0 = 0.100+ 0.874 (S/S 0 ) -0.255 (S/S 0 ) 2 Togrul et al [126] H/H 0 = 0.180+ 1.160 (S/S 0 ) -0.910 (S/S 0 ) 2 Said et al [80] H/H 0 = 0.348+ 0.320 (S/S 0 ) +0.070 (S/S 0 ) 2 Maduekwe et al [59] H/H 0 = 0.222+ 0.538 (S/S 0 ) +0.152 (S/S 0 ) 2 Ahmad et al [7] H/H 0 = 0.069+1.326 (S/S 0 ) -0.667 (S/S 0 ) 2 Onyango et al [24] H/H 0 = -2.767+ 9.207 (S/S 0 ) -6.350 (S/S 0 ) 2 Safari et al [67]…”

Section: Statistical Indicatorsmentioning

confidence: 99%

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Performance Evaluation and Statistical Analysis of Solar Energy Modeling: A Review and Case Study

Khalil¹

2022

J. Nig. Soc. Phys. Sci.

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The main target of this research is a quantitative review of literature on global solar radiation (GSR) models available for different stations around the world. The statistical analysis of 400 existing sunshine-based GSR models on a horizontal surface is compared using 40-year meteorological data in the selected locations in Egypt. The measured data is divided into two sets. The first sub-data set from 1980 to 2019 was used to develop empirical correlation models between the monthly average daily global solar radiation fraction (H/H0) and the monthly average of desired meteorological parameters. The second sub-data set from 2015–2019 was used to validate and evaluate the derived models and correlations. The developed models were compared with each other and with the experimental data of the second subset based on the statistical error indicators such as RMSE, MBE, MABE, MPE, and correlation coefficient (R). The statistical test of the correlation, coefficient (R), for all models gives very good results (above 0.92). The smallest values of t-Test occur around the models (M 272, M 261, M 251, and M 238). The accuracy of each model is tested using ten different statistical indicator tests. The Global Performance Indicator (GPI) is used to rank the selected GSR models. According to the results, the Rietveld model (Model 272) has shown the best capability to predict the GSR on horizontal surfaces, followed by the Katiyar et al. model (Model 251) and the Aras et al. model (Model 261).

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Section: Statistical Indicatorsmentioning

confidence: 99%

“…A comparative review was finished by [22] for 86 different areas across China and proposed the higher request relapse model regarding scope, longitude and elevation. As of late, Gadiwala et al [23], Onyango, and Ongoma [24] have proposed the relapse model for Pakistan and Kenya separately.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation and Statistical Analysis of Solar Energy Modeling: A Review and Case Study

Khalil¹

2022

J. Nig. Soc. Phys. Sci.

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“…The sunshine was uttered as the regular number of hours of sunshine per month or year, and tabulating the real hours of sunshine, as a percentage possible duration of sunshine for the particular location indicates the relative sun shines of climate (Russell 1934) radiation during the summer months could be attributed to the maximum daily sunshine hours due to a high clearness index. In the presence of cloud and rainfall, suspension of water particles attenuates the incoming solar radiation to the earth's surface (Sansui, et al, 2015;Omondi Onyango et al 2015) and hence the reduction in the amount of global solar radiation.…”

Section: Monthly Variation Of Solar Radiationmentioning

confidence: 99%

Estimation of Monthly Mean Global Solar Radiation Over Semi-arid Region, Kadapa Using Meteorological Parameters

Sankarayogi

Annareddy²,

Awasthi³

et al. 2022

Preprint

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To accomplish the best operation of available solar energy, it is important to estimate the incident solar radiation over the specific region. The present study focuses on the estimation of solar radiation by using mathematical modelling. For that purpose, monthly average daily global solar radiations are estimated based on different parameters like minimum and maximum temperature, sunshine hour, and relative humidity. The location selected for this study is Kadapa ((14.47ºN, 78.87º E, and 138m asl) Southern part of India. The study period is from April 2016 to October 2018. The study focuses particularly on models based on the relative sunshine (S/S0) and clearness index (kt). The clearness index and relative sunshine were high in December (1.058±0.002 and 0.968±0.005) and low in July (0.952±0.05 and 0.734±0.072). The estimated clearness index based on sunshine models is best correlated with the calculated clearness index values. In temperature and relative humidity-based models the hybrid parameter-based models are better correlated with the single parameter based-models.

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“…Table 2 Sunshine based model regression equation classifications [10]- [16]. In comparison to other models, the Angstrom-Prescott (A-P) model is most widely used to estimate GSR at a location.…”

Section: Temperature-based 16mentioning

confidence: 99%

Sunshine-based Global Solar Radiation Modelling: Case Study of Putrajaya, Malaysia

Tsung

2020

JEST

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Electricity demands are on the rise and with it, carbon dioxide emissions from many conventional power plants are increasing. In the efforts to mitigate such phenomena, the Malaysian government seeks to implement Building Integrated Photovoltaic (BIPV) projects. Early stage studies on Global Solar Radiation (GSR) have been carried out in several states in Malaysia including Penang, Kuala Lumpur and Kota Bharu. Afterward, data from the Malaysia Meteorological Department and the Malaysia National University have been used to estimate the monthly average daily global radiation in various locations in Malaysia. Putrajaya, a location which is implementing Malaysian Building Integrated Photovoltaic (MBIPV) is among the locations where a GSR study is currently absent. Conventional methods exist for GSR estimation with the aid of pyranometer. However, this method of GSR estimation is time consuming and not cost-effective practice. The main objective of this study is to estimate the GSR in Putrajaya. This is achieved in this study by utilizing sunshine-based data with calculated monthly average daily extraterrestrial radiation on a horizontal surface and monthly average maximum possible daily sunshine to plot a linearly fitted graph. Coefficients in the Angstrom-Prescott (A-P) model was generated from the plotted graph and was used for GSR estimation where a = 0.5 and b = 0.11. The mean percentage error (MPE) of the GSR estimation was found to be 3.4. Therefore, the estimation of GSR in Putrajaya have been successful for the first-time using sunshine-based data from dual locations method. The GSR estimation of Putrajaya in this study could benefit stakeholders in civil development sectors, policy and energy authorities.

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Estimation of mean monthly global solar radiation using sunshine hours for Nairobi City, Kenya

Cited by 22 publications

References 37 publications

Performance Evaluation and Statistical Analysis of Solar Energy Modeling: A Review and Case Study

Performance Evaluation and Statistical Analysis of Solar Energy Modeling: A Review and Case Study

Estimation of Monthly Mean Global Solar Radiation Over Semi-arid Region, Kadapa Using Meteorological Parameters

Sunshine-based Global Solar Radiation Modelling: Case Study of Putrajaya, Malaysia

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