Battery Charge Control in Solar Photovoltaic Systems Based on Fuzzy Logic and Jellyfish Optimization Algorithm

The study focuses on the integration of a fuzzy logic-based Maximum Power Point Tracking (MPPT) system, an optimized proportional Integral-based voltage controller, and the Jellyfish Optimization Algorithm into a solar PV battery setup. This integrated approach aims to enhance energy harvesting effi...

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Bibliographic Details
Published in:Applied sciences 2023-10, Vol.13 (20), p.11409
Main Authors: Ahmed Ali Agoub, Ramadan, Hançerlioğullari, Aybaba, Rahebi, Javad, Lopez-Guede, Jose Manuel
Format: Article
Language:English
Subjects:
Algorithms
Alternative energy sources
battery storage
Efficiency
Electric current regulators
Electric power production
Energy resources
Fuzzy algorithms
Fuzzy logic
fuzzy MPPT
Fuzzy systems
Innovations
Integrated approach
Mathematical optimization
MPPT
Optimization algorithms
Photovoltaic cells
PSO
PV system
Radiation
Renewable resources
Solar energy
Solar energy industry
Voltage regulators
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Summary:The study focuses on the integration of a fuzzy logic-based Maximum Power Point Tracking (MPPT) system, an optimized proportional Integral-based voltage controller, and the Jellyfish Optimization Algorithm into a solar PV battery setup. This integrated approach aims to enhance energy harvesting efficiency under varying environmental conditions. The study’s innovation lies in effectively addressing challenges posed by diverse environmental factors and loads. The utilization of MATLAB 2022a Simulink for modeling and the Jellyfish Optimization Algorithm for PI-controller tuning further strengthens our findings. Testing scenarios, including constant and variable irradiation, underscore the significant enhancements achieved through the integration of fuzzy MPPT and the Jellyfish Optimization Algorithm with the PI-based voltage controller. These enhancements encompass improved power extraction, optimized voltage regulation, swift settling times, and overall efficiency gains.
ISSN:2076-3417
2076-3417
DOI:10.3390/app132011409