General Models for Monthly Average Daily Global Solar Irradiation

With the world’s growing demand for electricity and the crucial need to reduce greenhouse gas emissions, it’s more important than ever to develop renewable energies, particularly solar power. The study carried out in this document is in line with the same principle, i.e. to improve the exploitation of solar energy. Its aim is to develop a mathematical model for mean monthly daily global solar irradiation that is independent of measurement data and suitable for all sites worldwide. For this study, we used daily global solar irradiation data for a horizontal surface. These data are from 60 sites worldwide and cover the period from 2000 to 2023. To examine the quality of the models established in the document, we carried out an investigation into performance tools. We have presented two, including MAPE (Mean Absolute Percentage Error) and Pearson’s correlation coefficient. Based on the daily global solar irradiance data from the 60 sites, the empirical model of extraterrestrial daily solar irradiance, and computational tools, we have formulated mathematical expressions of solar irradiance. It has the particularity of being independent of measurement data such as the duration of the day and temperature of the sites. It requires only the latitudes of the locations to estimate the solar potential values of the sites. A study of the performance of the established model showed that the model of monthly mean daily global solar irradiation values has fairly acceptable accuracy and fairly good correlation.

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Publication Details

Journal
Science Journal of Energy Engineering
Published
2024-12-03
DOI
https://doi.org/10.11648/j.sjee.20241204.12
Citations
1
Primary Topic
Solar Radiation and Photovoltaics
Type
article
Field-Weighted Citation Impact
0.35
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article

General Models for Monthly Average Daily Global Solar Irradiation

Zacharie Koalaga, Jacques Marie Ilboudo, Sosthène Tassembédo, Dominique Bonkoungou
1 citations
Science Journal of Energy Engineering
Solar Radiation and Photovoltaics
0.35
article

General Models for Monthly Average Daily Global Solar Irradiation

Zacharie Koalaga, Jacques Marie Ilboudo, Sosthène Tassembédo, Dominique Bonkoungou
article en
1 citations

Abstract

With the world’s growing demand for electricity and the crucial need to reduce greenhouse gas emissions, it’s more important than ever to develop renewable energies, particularly solar power. The study carried out in this document is in line with the same principle, i.e. to improve the exploitation of solar energy. Its aim is to develop a mathematical model for mean monthly daily global solar irradiation that is independent of measurement data and suitable for all sites worldwide. For this study, we used daily global solar irradiation data for a horizontal surface. These data are from 60 sites worldwide and cover the period from 2000 to 2023. To examine the quality of the models established in the document, we carried out an investigation into performance tools. We have presented two, including MAPE (Mean Absolute Percentage Error) and Pearson’s correlation coefficient. Based on the daily global solar irradiance data from the 60 sites, the empirical model of extraterrestrial daily solar irradiance, and computational tools, we have formulated mathematical expressions of solar irradiance. It has the particularity of being independent of measurement data such as the duration of the day and temperature of the sites. It requires only the latitudes of the locations to estimate the solar potential values of the sites. A study of the performance of the established model showed that the model of monthly mean daily global solar irradiation values has fairly acceptable accuracy and fairly good correlation.

Science Journal of Energy EngineeringVol. 12(4)
Université Joseph Ki-Zerbo (BF), Université Ouaga II (BF)
Openalex Percentile: Top 31%
Solar Radiation and Photovoltaics
0.35
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General Models for Monthly Average Daily Global Solar Irradiation — Zacharie Koalaga, Jacques Marie Ilboudo, et al. · Science Journal of Energy Engineering (2024) | TGRS Research Map | TGRS