Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt Method
Accurate modeling and simulation of solar photovoltaic (PV) systems are critical for optimizing their performance and efficiency. This requires precise determination of electrical parameters of solar cells, such as photocurrent (Iph), saturation current (I0), series resistance (Rs), shunt resistance...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
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| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00053.pdf |
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| _version_ | 1832098664649064448 |
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| author | Herbazi Rachid Amechnoue Khalid Chahboun Adil |
| author_facet | Herbazi Rachid Amechnoue Khalid Chahboun Adil |
| author_sort | Herbazi Rachid |
| collection | DOAJ |
| description | Accurate modeling and simulation of solar photovoltaic (PV) systems are critical for optimizing their performance and efficiency. This requires precise determination of electrical parameters of solar cells, such as photocurrent (Iph), saturation current (I0), series resistance (Rs), shunt resistance (Rsh), and ideality factor (n). Traditional numerical methods for parameter extraction often face limitations in complexity, speed, and assumption dependencies. To address these issues, this study proposes a hybrid method that combines a genetic algorithm with the Levenberg-Marquardt algorithm (GALM) for solar cell parameter extraction. The genetic algorithm provides a robust initial estimate of the parameters, which is then refined by the Levenberg-Marquardt algorithm to achieve high accuracy. The performance of the proposed GALM method is validated using experimental data from a 57-mm silicon solar cell from R.T.C. France. Results indicate that the GALM method achieves one of the lowest RMSE values compared to other optimization techniques, demonstrating its effectiveness in accurately extracting solar cell parameters and closely matching the experimental I-V data. This contributes significantly to optimizing the performance and efficiency of PV systems. |
| format | Article |
| id | doaj-art-f750e989fbaa45cd8836b5e4ee27b132 |
| institution | Kabale University |
| issn | 2267-1242 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj-art-f750e989fbaa45cd8836b5e4ee27b1322025-02-05T10:46:25ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016010005310.1051/e3sconf/202560100053e3sconf_icegc2024_00053Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt MethodHerbazi Rachid0Amechnoue Khalid1Chahboun Adil2Intelligent Systems and Applications Laboratory (LSIA), Moroccan School of Engineering Sciences (EMSI)ERMIA, National School of Applied Sciences (ENSA), Abdelmalek Essaadi UniversityERCMN, Faculty of Science and Technology (FST), Abdelmalek Essaadi UniversityAccurate modeling and simulation of solar photovoltaic (PV) systems are critical for optimizing their performance and efficiency. This requires precise determination of electrical parameters of solar cells, such as photocurrent (Iph), saturation current (I0), series resistance (Rs), shunt resistance (Rsh), and ideality factor (n). Traditional numerical methods for parameter extraction often face limitations in complexity, speed, and assumption dependencies. To address these issues, this study proposes a hybrid method that combines a genetic algorithm with the Levenberg-Marquardt algorithm (GALM) for solar cell parameter extraction. The genetic algorithm provides a robust initial estimate of the parameters, which is then refined by the Levenberg-Marquardt algorithm to achieve high accuracy. The performance of the proposed GALM method is validated using experimental data from a 57-mm silicon solar cell from R.T.C. France. Results indicate that the GALM method achieves one of the lowest RMSE values compared to other optimization techniques, demonstrating its effectiveness in accurately extracting solar cell parameters and closely matching the experimental I-V data. This contributes significantly to optimizing the performance and efficiency of PV systems.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00053.pdfphotovoltaicparameters extractiongenetic algorithmlevenberg-marquardtsolar cell |
| spellingShingle | Herbazi Rachid Amechnoue Khalid Chahboun Adil Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt Method E3S Web of Conferences photovoltaic parameters extraction genetic algorithm levenberg-marquardt solar cell |
| title | Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt Method |
| title_full | Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt Method |
| title_fullStr | Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt Method |
| title_full_unstemmed | Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt Method |
| title_short | Enhancement of Electrical Parameter Extraction from Solar Cells Using a Hybrid Genetic Algorithm with the Levenberg-Marquardt Method |
| title_sort | enhancement of electrical parameter extraction from solar cells using a hybrid genetic algorithm with the levenberg marquardt method |
| topic | photovoltaic parameters extraction genetic algorithm levenberg-marquardt solar cell |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00053.pdf |
| work_keys_str_mv | AT herbazirachid enhancementofelectricalparameterextractionfromsolarcellsusingahybridgeneticalgorithmwiththelevenbergmarquardtmethod AT amechnouekhalid enhancementofelectricalparameterextractionfromsolarcellsusingahybridgeneticalgorithmwiththelevenbergmarquardtmethod AT chahbounadil enhancementofelectricalparameterextractionfromsolarcellsusingahybridgeneticalgorithmwiththelevenbergmarquardtmethod |