Modeling monthly insolation data

Abdulmunim Guwaeder; Salah Eltief; Ibrahim Aldaouab; Ali Mustafa Madi

doi:10.1117/12.2571736

20 August 2020 Modeling monthly insolation data

Abdulmunim Guwaeder, Salah Eltief, Ibrahim Aldaouab, Ali Mustafa Madi

Author Affiliations +

Proceedings Volume 11495, Nonimaging Optics: Efficient Design for Illumination and Solar Concentration XVII; 114950Q (2020) https://doi.org/10.1117/12.2571736
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Abstract

This paper discusses the probability distribution functions (PDF) of monthly insolation for four locations in Libya based on analysis of 30 years of historical weather data calculated by National Renewable Energy Laboratory (NREL), in order to get appropriate probability distribution that best fits the data for a given month of the year. The frequency distributions used for solar irradiation data include Weibull, Normal, Lognormal and Gamma. The observed radiation at four locations in Libya on a monthly basis are analyzed to evaluate the suitability of the probability distribution functions based on the mean square errors. The analysis showed all the probability functions are appropriate for all the locations where weather conditions are relatively steady throughout the year. From the analysis it is concluded that Normal and Weibull distributions gives the best fit for observed solar radiation.

Conference Presentation

Citation Download Citation

Abdulmunim Guwaeder, Salah Eltief, Ibrahim Aldaouab, and Ali Mustafa Madi "Modeling monthly insolation data", Proc. SPIE 11495, Nonimaging Optics: Efficient Design for Illumination and Solar Concentration XVII, 114950Q (20 August 2020); https://doi.org/10.1117/12.2571736

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