International Journal of Mathematical Analysis and Applications
Manuscript Information

Improved Mathematical Modeling of the Hourly Solar Diffuse Fraction (HSDF) - Adrar, Algeria Case Study
International Journal of Mathematical Analysis and Applications
Vol.4 , No. 2, Publication Date: Jul. 5, 2017, Page: 8-12
523 Views Since July 5, 2017, 317 Downloads Since Jul. 5, 2017

Authors

 [1] Nadjem Bailek, Department of Physics, Faculty of Science, University Djilali Liabes of Sidi Bel-Abbes, Sidi Bel-Abbes, Algeria. [2] Kada Bouchouicha, Research Unit in Renewable Energies in Saharan Medium (URER.MS), Renewable Energies Development Center (CDER), Bouzaréah, Algeria. [3] Mohamed EL-Shimy, Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt. [4] Abdeldjalil Slimani, Research Unit in Renewable Energies in Saharan Medium (URER.MS), Renewable Energies Development Center (CDER), Bouzaréah, Algeria. [5] Keh-Chin Chang, Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan, Taiwan. [6] Abdalhe Djaafari, Department of Physics, Faculty of Science, University of Tamanghasset, Tamanghasset, Algeria.

Abstract

Solar energy is among the excellent alternative energy resources; however, it suffers from significant problems. These problems are mainly due to the inherent variability, and intermittency of the solar resource; however, proper predictability of the resource can reduce the consequent impacts of the mentioned problems. Enhancing the predictability of the solar resource provides an essential tool for the design, performance analysis, and economic evaluation of various solar energy projects. In this paper, highly accurate mathematical models for estimating the hourly diffuse solar fraction are presented for enhancing the predictability of the solar resource over Adrar, Algeria big south desert. The presented modeling is based on clearance index measurements. The best found model for the considered site is found to be the sigmoid logistic empirical model. This model shows the highest accuracy in comparison with other models where its correlation coefficient (R), and the Nash-Sutcliffe NSE are found to be 93.7% and 84.2% respectively. In addition, the segmoid logistic model shows very low values of the mean bias error (MBE), and root mean square error (RMSE).

Keywords

Solar Diffuse Fraction, Multiple Regression, Mathematical Modeling

Reference