Comparisons and critical assessment of global and diffuse solar irradiation estimation methodologies

Date

2018-01-01

Author

Karaveli, Abdullah Bugrahan
Akınoğlu, Bülent Gültekin

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Defining better methodologies of accurate predictions of the amount of monthly mean daily global and diffuse solar irradiation exposed is of utmost importance in order to determine the potential for utilizing the solar energy. This study compares and discusses the main methodologies, databases, and software that are used in estimating the solar irradiation to be used for the short- and long-term performances and feasibilities of solar energy systems, especially photovoltaic power plants in Turkey, and addresses the best one to be used to make the most accurate estimations. The comparisons are carried out between the recent methodologies developed by the authors, some models taken from the related literature that are concluded to be better, a widely used database, namely Meteonorm, and a widely used software, namely EU PVGIS. The reference data to develop the methodologies and to make comparison are provided from the State Meteorological Service of Turkey, which is the responsible body in Turkey to make measurements of solar irradiation. The comparisons are based on monthly mean daily values of global and diffuse solar irradiation and are carried out by statistical errors: mean bias error and root mean square error. The results showed that the methodology developed by the authors has shown better performances in estimating the monthly mean daily global and diffuse solar irradiation amount for Turkey.

Subject Keywords

Renewable Energy, Sustainability and the Environment

URI

https://hdl.handle.net/11511/46627

Journal

INTERNATIONAL JOURNAL OF GREEN ENERGY

DOI

https://doi.org/10.1080/15435075.2018.1452743

Collections

Department of Physics, Article

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Citation Formats

A. B. Karaveli and B. G. Akınoğlu, “Comparisons and critical assessment of global and diffuse solar irradiation estimation methodologies,” INTERNATIONAL JOURNAL OF GREEN ENERGY, pp. 325–332, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46627.