Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems
Due to the rapid advancement in the use of photovoltaic (PV) energy systems, it has become critical to look for ways to improve the energy generated by them. The extracted power from the PV modules is proportional to the output voltage. The relationship between output power and array voltage has onl...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/13/5228 |
| _version_ | 1797591774721474560 |
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| author | Ali M. Eltamaly Zeyad A. Almutairi Mohamed A. Abdelhamid |
| author_facet | Ali M. Eltamaly Zeyad A. Almutairi Mohamed A. Abdelhamid |
| author_sort | Ali M. Eltamaly |
| collection | DOAJ |
| description | Due to the rapid advancement in the use of photovoltaic (PV) energy systems, it has become critical to look for ways to improve the energy generated by them. The extracted power from the PV modules is proportional to the output voltage. The relationship between output power and array voltage has only one peak under uniform irradiance, whereas it has multiple peaks under partial shade conditions (PSCs). There is only one global peak (GP) and many local peaks (LPs), where the typical maximum power point trackers (MPPTs) may become locked in one of the LPs, significantly reducing the PV system’s generated power and efficiency. The metaheuristic optimization algorithms (MOAs) solved this problem, albeit at the expense of the convergence time, which is one of these algorithms’ key shortcomings. Most MOAs attempt to lower the convergence time at the cost of the failure rate and the accuracy of the findings because these two factors are interdependent. To address these issues, this work introduces the dandelion optimization algorithm (DOA), a novel optimization algorithm. The DOA’s convergence time and failure rate are compared to other modern MOAs in critical scenarios of partial shade PV systems to demonstrate the DOA’s superiority. The results obtained from this study showed substantial performance improvement compared to other MOAs, where the convergence time was reduced to 0.4 s with zero failure rate compared to 0.9 s, 1.25 s, and 0.43 s for other MOAs under study. The optimal number of search agents in the swarm, the best initialization of search agents, and the optimal design of the dc–dc converter are introduced for optimal MPPT performance. |
| first_indexed | 2024-03-11T01:42:08Z |
| format | Article |
| id | doaj.art-89201088e9f9424d9e5a3da04d05bffc |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T01:42:08Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-89201088e9f9424d9e5a3da04d05bffc2023-11-18T16:32:17ZengMDPI AGEnergies1996-10732023-07-011613522810.3390/en16135228Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV SystemsAli M. Eltamaly0Zeyad A. Almutairi1Mohamed A. Abdelhamid2Sustainable Energy Technologies Center, King Saud University, Riyadh 11421, Saudi ArabiaSustainable Energy Technologies Center, King Saud University, Riyadh 11421, Saudi ArabiaDepartment of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, ChileDue to the rapid advancement in the use of photovoltaic (PV) energy systems, it has become critical to look for ways to improve the energy generated by them. The extracted power from the PV modules is proportional to the output voltage. The relationship between output power and array voltage has only one peak under uniform irradiance, whereas it has multiple peaks under partial shade conditions (PSCs). There is only one global peak (GP) and many local peaks (LPs), where the typical maximum power point trackers (MPPTs) may become locked in one of the LPs, significantly reducing the PV system’s generated power and efficiency. The metaheuristic optimization algorithms (MOAs) solved this problem, albeit at the expense of the convergence time, which is one of these algorithms’ key shortcomings. Most MOAs attempt to lower the convergence time at the cost of the failure rate and the accuracy of the findings because these two factors are interdependent. To address these issues, this work introduces the dandelion optimization algorithm (DOA), a novel optimization algorithm. The DOA’s convergence time and failure rate are compared to other modern MOAs in critical scenarios of partial shade PV systems to demonstrate the DOA’s superiority. The results obtained from this study showed substantial performance improvement compared to other MOAs, where the convergence time was reduced to 0.4 s with zero failure rate compared to 0.9 s, 1.25 s, and 0.43 s for other MOAs under study. The optimal number of search agents in the swarm, the best initialization of search agents, and the optimal design of the dc–dc converter are introduced for optimal MPPT performance.https://www.mdpi.com/1996-1073/16/13/5228photovoltaicMPPTpartial shading conditionsconvergence timefailure ratemetaheuristic |
| spellingShingle | Ali M. Eltamaly Zeyad A. Almutairi Mohamed A. Abdelhamid Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems Energies photovoltaic MPPT partial shading conditions convergence time failure rate metaheuristic |
| title | Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems |
| title_full | Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems |
| title_fullStr | Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems |
| title_full_unstemmed | Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems |
| title_short | Modern Optimization Algorithm for Improved Performance of Maximum Power Point Tracker of Partially Shaded PV Systems |
| title_sort | modern optimization algorithm for improved performance of maximum power point tracker of partially shaded pv systems |
| topic | photovoltaic MPPT partial shading conditions convergence time failure rate metaheuristic |
| url | https://www.mdpi.com/1996-1073/16/13/5228 |
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