American Journal of Energy Research
ISSN (Print): 2328-7349 ISSN (Online): 2328-7330 Website: http://www.sciepub.com/journal/ajer Editor-in-chief: Apply for this position
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American Journal of Energy Research. 2017, 5(2), 41-50
DOI: 10.12691/ajer-5-2-3
Open AccessArticle

Simulation and Prediction of the Power Output and the Photocurrent for Photovoltaic Systems

Kossi Kety1, Apélété Komi Amou1, Koffi Sagna1, , Yendoubé Lare1 and Kossi Napo1

1Solar Energy Laboratory, Department of Physics, Faculty of Sciences, University of Lomé, Lomé, Togo

Pub. Date: August 24, 2017

Cite this paper:
Kossi Kety, Apélété Komi Amou, Koffi Sagna, Yendoubé Lare and Kossi Napo. Simulation and Prediction of the Power Output and the Photocurrent for Photovoltaic Systems. American Journal of Energy Research. 2017; 5(2):41-50. doi: 10.12691/ajer-5-2-3

Abstract

We study in this paper, based on comparison already made in the literature concerning photovoltaic generator power models, the most optimal model applied to the operation of the photovoltaic generator of Sévagan (Togo). The comparison with the experimental data is carried out, which allowed us to verify the validity of the model. Finally, the influence of the characteristic parameters on the photovoltaic module ECO LINE LX-260P used to make the photovoltaic generator of the Sévagan dispensary (in Togo) is studied in order to predict the power production of the module according to the meteorological conditions(temperature-Irradiation). The comparison with the experimental data will be carried out in order to verify the validity of the model. To verify the validity of the model throughout the range of weather conditions, the process was done in two steps: on a sunny day and a cloudy day. A good agreement was observed with 95%, 97% and 99% correlation coefficients for cloudy, sunny days and the generator photocurrent simulation respectively. The results demonstrate an acceptable accuracy of the power model under different environmental conditions.

Keywords:
simulation photovoltaic generator power output models - prediction optimization

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