Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm
Abstract The escalating global population and energy demands underscore the critical role of renewable energy sources, particularly solar power, in mitigating environmental degradation caused by traditional fossil fuels. This paper emphasizes the advantages of solar energy, especially photovoltaic (...
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| Format: | Article |
| Language: | English |
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Wiley
2024-11-01
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| Series: | IET Generation, Transmission & Distribution |
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| Online Access: | https://doi.org/10.1049/gtd2.13279 |
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| author | Mostafa Jabari Amin Rad Morteza Azimi Nasab Mohammad Zand Sanjeevikumar Padmanaban S. M. Muyeen Josep M. Guerrero |
| author_facet | Mostafa Jabari Amin Rad Morteza Azimi Nasab Mohammad Zand Sanjeevikumar Padmanaban S. M. Muyeen Josep M. Guerrero |
| author_sort | Mostafa Jabari |
| collection | DOAJ |
| description | Abstract The escalating global population and energy demands underscore the critical role of renewable energy sources, particularly solar power, in mitigating environmental degradation caused by traditional fossil fuels. This paper emphasizes the advantages of solar energy, especially photovoltaic (PV) systems, which have become pivotal in hybrid energy systems. However, accurate modelling and identification of PV cell parameters pose challenges, prompting the adoption of meta‐heuristic optimization algorithms. This work explores the limitations of existing algorithms and introduces a novel approach, the bio‐dynamics grasshopper optimization algorithm (BDGOA). The BDGOA addresses deficiencies in both exploration and exploitation phases, exhibiting exceptional convergence speed and efficiency. The algorithm's simplicity, achieved through the implementation of an elimination phase and controlled search space, enhances its performance without intricate calculations. The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. The paper concludes with insights into the impact of radiation and temperature on module parameters. The subsequent sections of the paper delve into the intricacies of the PV cell and module model, articulate the formulation of the proposed algorithm, present simulations, and analyse the obtained results. The BDGOA emerges as a promising solution, overcoming the limitations of existing algorithms and contributing significantly to the advancement of accurate and efficient PV cell parameter identification, thereby propelling progress towards a sustainable energy future. |
| format | Article |
| id | doaj-art-59f6d17c3a344935b354b39a3642bf79 |
| institution | DOAJ |
| issn | 1751-8687 1751-8695 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Generation, Transmission & Distribution |
| spelling | doaj-art-59f6d17c3a344935b354b39a3642bf792025-08-20T03:08:52ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952024-11-0118213314333810.1049/gtd2.13279Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithmMostafa Jabari0Amin Rad1Morteza Azimi Nasab2Mohammad Zand3Sanjeevikumar Padmanaban4S. M. Muyeen5Josep M. Guerrero6Faculty of Electrical Engineering Sahand University of Technology Tabriz IranFaculty of Electrical Engineering Sahand University of Technology Tabriz IranDepartment of Electrical Engineering, Information Technology and Cybernetic University of South‐Eastern Norway Porsgrunn NorwayDepartment of Electrical Engineering, Information Technology and Cybernetic University of South‐Eastern Norway Porsgrunn NorwayDepartment of Electrical Engineering, Information Technology and Cybernetic University of South‐Eastern Norway Porsgrunn NorwayDepartment of Electrical Engineering Qatar University Doha QatarCenter for Research on Microgrids University of Aalborg Aalborg DenmarkAbstract The escalating global population and energy demands underscore the critical role of renewable energy sources, particularly solar power, in mitigating environmental degradation caused by traditional fossil fuels. This paper emphasizes the advantages of solar energy, especially photovoltaic (PV) systems, which have become pivotal in hybrid energy systems. However, accurate modelling and identification of PV cell parameters pose challenges, prompting the adoption of meta‐heuristic optimization algorithms. This work explores the limitations of existing algorithms and introduces a novel approach, the bio‐dynamics grasshopper optimization algorithm (BDGOA). The BDGOA addresses deficiencies in both exploration and exploitation phases, exhibiting exceptional convergence speed and efficiency. The algorithm's simplicity, achieved through the implementation of an elimination phase and controlled search space, enhances its performance without intricate calculations. The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. The paper concludes with insights into the impact of radiation and temperature on module parameters. The subsequent sections of the paper delve into the intricacies of the PV cell and module model, articulate the formulation of the proposed algorithm, present simulations, and analyse the obtained results. The BDGOA emerges as a promising solution, overcoming the limitations of existing algorithms and contributing significantly to the advancement of accurate and efficient PV cell parameter identification, thereby propelling progress towards a sustainable energy future.https://doi.org/10.1049/gtd2.13279solar cell arrayssolar cellssolar power |
| spellingShingle | Mostafa Jabari Amin Rad Morteza Azimi Nasab Mohammad Zand Sanjeevikumar Padmanaban S. M. Muyeen Josep M. Guerrero Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm IET Generation, Transmission & Distribution solar cell arrays solar cells solar power |
| title | Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm |
| title_full | Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm |
| title_fullStr | Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm |
| title_full_unstemmed | Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm |
| title_short | Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm |
| title_sort | parameter identification of pv solar cells and modules using bio dynamics grasshopper optimization algorithm |
| topic | solar cell arrays solar cells solar power |
| url | https://doi.org/10.1049/gtd2.13279 |
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