Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions
Abstract This study addresses the pressing need for optimized solar power systems in the context of climate change concerns. Focusing on Maximum Power Point Tracking (MPPT) techniques, the research evaluates various models to enhance energy generation in solar systems under fluctuating solar irradia...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-90417-1 |
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| author | Mutiu Shola Bakare Abubakar Abdulkarim Aliyu Nuhu Shuaibu Mundu Mustafa Muhamad |
| author_facet | Mutiu Shola Bakare Abubakar Abdulkarim Aliyu Nuhu Shuaibu Mundu Mustafa Muhamad |
| author_sort | Mutiu Shola Bakare |
| collection | DOAJ |
| description | Abstract This study addresses the pressing need for optimized solar power systems in the context of climate change concerns. Focusing on Maximum Power Point Tracking (MPPT) techniques, the research evaluates various models to enhance energy generation in solar systems under fluctuating solar irradiation conditions. The Adaptive Neural-Fuzzy Inference System (ANFIS) is chosen for its responsiveness, but designing an efficient ANFIS-MPPT system requires precise training data. The study introduces a novel approach, combining ANFIS with Gene Expression Programming (GEP), aimed at optimizing the reference maximum power output using solar irradiance and temperature as input parameters. The integration was tested on a boost converter via Matlab/Simulink simulations, which reveals the GEP-ANFIS double diode model’s exceptional 99.84% efficiency under high solar irradiation. This underscores the substantial potential of GEP-ANFIS for improving solar power efficiency and MPPT performance in diverse environments, contributing to the advancement of solar energy utilization. |
| format | Article |
| id | doaj-art-a6889cb9a4884ea28d2396a94b26d00f |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-a6889cb9a4884ea28d2396a94b26d00f2025-08-20T03:10:57ZengNature PortfolioScientific Reports2045-23222025-02-0115111810.1038/s41598-025-90417-1Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditionsMutiu Shola Bakare0Abubakar Abdulkarim1Aliyu Nuhu Shuaibu2Mundu Mustafa Muhamad3Department of Electrical Engineering, Kampala International UniversityDepartment of Electrical Engineering, Kampala International UniversityDepartment of Electrical Engineering, Kampala International UniversityDepartment of Electrical Engineering, Kampala International UniversityAbstract This study addresses the pressing need for optimized solar power systems in the context of climate change concerns. Focusing on Maximum Power Point Tracking (MPPT) techniques, the research evaluates various models to enhance energy generation in solar systems under fluctuating solar irradiation conditions. The Adaptive Neural-Fuzzy Inference System (ANFIS) is chosen for its responsiveness, but designing an efficient ANFIS-MPPT system requires precise training data. The study introduces a novel approach, combining ANFIS with Gene Expression Programming (GEP), aimed at optimizing the reference maximum power output using solar irradiance and temperature as input parameters. The integration was tested on a boost converter via Matlab/Simulink simulations, which reveals the GEP-ANFIS double diode model’s exceptional 99.84% efficiency under high solar irradiation. This underscores the substantial potential of GEP-ANFIS for improving solar power efficiency and MPPT performance in diverse environments, contributing to the advancement of solar energy utilization.https://doi.org/10.1038/s41598-025-90417-1MPPTANFISGEPBoost converterSolar PVDynamic weather and load |
| spellingShingle | Mutiu Shola Bakare Abubakar Abdulkarim Aliyu Nuhu Shuaibu Mundu Mustafa Muhamad Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions Scientific Reports MPPT ANFIS GEP Boost converter Solar PV Dynamic weather and load |
| title | Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions |
| title_full | Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions |
| title_fullStr | Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions |
| title_full_unstemmed | Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions |
| title_short | Enhancing solar power efficiency with hybrid GEP ANFIS MPPT under dynamic weather conditions |
| title_sort | enhancing solar power efficiency with hybrid gep anfis mppt under dynamic weather conditions |
| topic | MPPT ANFIS GEP Boost converter Solar PV Dynamic weather and load |
| url | https://doi.org/10.1038/s41598-025-90417-1 |
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