Agoub, R.A.A.Hancerliogullari, A.Rahebi, J.Lopez-Guede, J.M.2023-11-102023-11-102023.01.01https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=dspace_ku&SrcAuth=WosAPI&KeyUT=WOS:001090602500001&DestLinkType=FullRecord&DestApp=WOShttps://hdl.handle.net/20.500.12597/17858The 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.eninfo:eu-repo/semantics/openAccessPV systembattery storageMPPTfuzzy MPPTPSOGAjellyfish optimizationArticle10.3390/app13201140900109060250000113202076-3417