Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation Systems
INTRODUCTION: Significant advances have been made in photovoltaic (PV) systems, resulting in the development of new Maximum Power Point Tracking (MPPT) methods. The output of PV systems is heavily influenced by the varying performance of solar-facing PV panels under different weather conditions. Par...
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| Format: | Article |
| Language: | English |
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European Alliance for Innovation (EAI)
2024-11-01
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| Series: | EAI Endorsed Transactions on Energy Web |
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| Online Access: | https://publications.eai.eu/index.php/ew/article/view/7325 |
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| author | Lei Shi Zongyu Zhang Yongrui Yu Chun Xie Tongbin Yang |
| author_facet | Lei Shi Zongyu Zhang Yongrui Yu Chun Xie Tongbin Yang |
| author_sort | Lei Shi |
| collection | DOAJ |
| description | INTRODUCTION: Significant advances have been made in photovoltaic (PV) systems, resulting in the development of new Maximum Power Point Tracking (MPPT) methods. The output of PV systems is heavily influenced by the varying performance of solar-facing PV panels under different weather conditions. Partial shading (PS) conditions pose additional challenges, leading to multiple peaks in the power-voltage (P-V) curve and reduced output power. Therefore, controlling MPPT under partial shading conditions is a complex task.
OBJECTIVES: This study aims to introduce a novel MMPT algorithm based on the ant colony incorporated bald eagle search optimization (AC-BESO) method to enhance the efficiency of PV systems.
METHODS: The effectiveness of the proposed MPPT algorithm was established through a series of experiments using MATLAB software, tested under various levels of solar irradiance.
RESULTS: Compared to existing methods, the proposed AC-BESO algorithm stands out for its simplicity in implementation and reduced computational complexity. Furthermore, its tracking performance surpasses that of conventional methods, as validated through comparative analyses.
CONCLUSION: This study confirms the efficacy of the AC-BESO method over traditional strategies. It serves as a framework for selecting an MPPT approach when designing PV systems.
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| format | Article |
| id | doaj-art-ace7130b968744758a13bd3d013ef4a7 |
| institution | DOAJ |
| issn | 2032-944X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | European Alliance for Innovation (EAI) |
| record_format | Article |
| series | EAI Endorsed Transactions on Energy Web |
| spelling | doaj-art-ace7130b968744758a13bd3d013ef4a72025-08-20T02:49:46ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Energy Web2032-944X2024-11-011210.4108/ew.7325Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation SystemsLei Shi0Zongyu Zhang1Yongrui Yu2Chun Xie3Tongbin Yang4Guizhou Power Grid Co.Guizhou Power Grid Co.Guizhou Power Grid Co.Guizhou Power Grid Co.Guizhou Power Grid Co.INTRODUCTION: Significant advances have been made in photovoltaic (PV) systems, resulting in the development of new Maximum Power Point Tracking (MPPT) methods. The output of PV systems is heavily influenced by the varying performance of solar-facing PV panels under different weather conditions. Partial shading (PS) conditions pose additional challenges, leading to multiple peaks in the power-voltage (P-V) curve and reduced output power. Therefore, controlling MPPT under partial shading conditions is a complex task. OBJECTIVES: This study aims to introduce a novel MMPT algorithm based on the ant colony incorporated bald eagle search optimization (AC-BESO) method to enhance the efficiency of PV systems. METHODS: The effectiveness of the proposed MPPT algorithm was established through a series of experiments using MATLAB software, tested under various levels of solar irradiance. RESULTS: Compared to existing methods, the proposed AC-BESO algorithm stands out for its simplicity in implementation and reduced computational complexity. Furthermore, its tracking performance surpasses that of conventional methods, as validated through comparative analyses. CONCLUSION: This study confirms the efficacy of the AC-BESO method over traditional strategies. It serves as a framework for selecting an MPPT approach when designing PV systems. https://publications.eai.eu/index.php/ew/article/view/7325PV SystemsMPPTIrradiationPower outputAnt-colony integrated bald eagle search optimization (AC-BESO) |
| spellingShingle | Lei Shi Zongyu Zhang Yongrui Yu Chun Xie Tongbin Yang Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation Systems EAI Endorsed Transactions on Energy Web PV Systems MPPT Irradiation Power output Ant-colony integrated bald eagle search optimization (AC-BESO) |
| title | Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation Systems |
| title_full | Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation Systems |
| title_fullStr | Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation Systems |
| title_full_unstemmed | Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation Systems |
| title_short | Research on a New Maximum Power Tracking Algorithm for Photovoltaic Power Generation Systems |
| title_sort | research on a new maximum power tracking algorithm for photovoltaic power generation systems |
| topic | PV Systems MPPT Irradiation Power output Ant-colony integrated bald eagle search optimization (AC-BESO) |
| url | https://publications.eai.eu/index.php/ew/article/view/7325 |
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