Extracting electrical parameters of solar cells using Lambert function
1
Department of Sciences and Technology, Faulty of Sciences and Technology, University of Tamanrasset, Algeria
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Energy and Materials Laboratory, University of Tamanghasset, Algeria.
3
Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria
4
laboratory Smart Grid and Renewable Energy SGRE University Tahri Mohamed Bechar Algeria
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Faculty of Sciences and Technology, University of Ahmed Draia, Adrar, Algeria
6
Department of Energy Technology, DDI Laboratory, Ahmed Draia University, 01000Adrar, Algeria
Submission date: 2024-01-25
Final revision date: 2024-05-08
Acceptance date: 2024-05-09
Online publication date: 2024-05-28
Publication date: 2024-05-28
Corresponding author
Mohammed Bouzidi
Department of Sciences and Technology, Faulty of Sciences and Technology, University of Tamanrasset, Algeria
Department of Sciences and Technology, Faulty of Sciences and Technology, University of Tamanrasset, Algeria
Diagnostyka 2024;25(2):2024214
KEYWORDS
TOPICS
ABSTRACT
Photovoltaic cells are intricate systems that transform solar energy into electrical power. Certain internal parameters, such as diode saturation current, conversion resistance, and series resistance, significantly influence the performance of electrical components. Frequently, manufacturers do not provide these parameters. At the moment, researchers need new and clear ways to measure these factors so they can get a better idea of how solar cells work and improve efficiency through simulations. We present a novel approach to accurately determining the five parameters (series resistance, shunt resistance, photovoltaic cell current, and diode saturation current) for multi-crystalline silicon solar cell models. This approach employs the Lambert function and the curve of parasitic resistance. By utilizing the extracted internal electrical parameters, this method will enhance the efficiency of solar cells through the facilitation of more accurate simulations.
FUNDING
This research received no external funding.
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