Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method.
Maximum Power Point Tracking (MPPT) is a promising technology for extracting peak power from single or multiple solar modules for improving Photovoltaic (PV) system performance and satisfying economic operation. The tracker should continuously follow the MPP of the PV module at all operating and wea...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0327542 |
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| author | Montaser Abdelsattar Hamdi Ali Mohamed Mohamed A Ismeil Ahmed A Zaki Diab |
| author_facet | Montaser Abdelsattar Hamdi Ali Mohamed Mohamed A Ismeil Ahmed A Zaki Diab |
| author_sort | Montaser Abdelsattar |
| collection | DOAJ |
| description | Maximum Power Point Tracking (MPPT) is a promising technology for extracting peak power from single or multiple solar modules for improving Photovoltaic (PV) system performance and satisfying economic operation. The tracker should continuously follow the MPP of the PV module at all operating and weather conditions. The Particle Swarm Optimization (PSO) algorithm represents a powerful optimal MPP tracker due to its simplicity and has enhanced greatest exploration characteristics. This article proposes a new technique based on PSO enhanced with Quasi-Newton local search for improving power quality while minimizing oscillation. This tracking process is making the MPPT comparable between high accuracy and fast tracking speed. MPPT proposal algorithm results are compared to the results of the hybrid PSO-P&O algorithm at different operating conditions. The proposed algorithm results show that MPP extraction has been done with a high-speed response and the best efficiency. Moreover, the PSO is enhanced with a Quasi-Newton (QN) local search method for tuning the optimal MPP. |
| format | Article |
| id | doaj-art-77a7f15a1edb4749a58f39d4590aaa03 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-77a7f15a1edb4749a58f39d4590aaa032025-08-20T02:40:24ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01207e032754210.1371/journal.pone.0327542Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method.Montaser AbdelsattarHamdi Ali MohamedMohamed A IsmeilAhmed A Zaki DiabMaximum Power Point Tracking (MPPT) is a promising technology for extracting peak power from single or multiple solar modules for improving Photovoltaic (PV) system performance and satisfying economic operation. The tracker should continuously follow the MPP of the PV module at all operating and weather conditions. The Particle Swarm Optimization (PSO) algorithm represents a powerful optimal MPP tracker due to its simplicity and has enhanced greatest exploration characteristics. This article proposes a new technique based on PSO enhanced with Quasi-Newton local search for improving power quality while minimizing oscillation. This tracking process is making the MPPT comparable between high accuracy and fast tracking speed. MPPT proposal algorithm results are compared to the results of the hybrid PSO-P&O algorithm at different operating conditions. The proposed algorithm results show that MPP extraction has been done with a high-speed response and the best efficiency. Moreover, the PSO is enhanced with a Quasi-Newton (QN) local search method for tuning the optimal MPP.https://doi.org/10.1371/journal.pone.0327542 |
| spellingShingle | Montaser Abdelsattar Hamdi Ali Mohamed Mohamed A Ismeil Ahmed A Zaki Diab Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. PLoS ONE |
| title | Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. |
| title_full | Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. |
| title_fullStr | Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. |
| title_full_unstemmed | Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. |
| title_short | Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. |
| title_sort | maximum power point tracking of photovoltaic module based on particle swarm optimization enhanced with quasi newton method |
| url | https://doi.org/10.1371/journal.pone.0327542 |
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