Maximum Power Point Tracking Algorithms for Solar Photovoltaic Configurations using ANN optimized Fuzzy-PID controller

dc.contributor.advisorDr. Shubhashish Bhakta (Ph.D. Engg.)
dc.contributor.authorBinyam, Beyene
dc.date.accessioned2025-12-17T11:02:06Z
dc.date.issued2023-06
dc.description.abstractElectricity is the main source of energy all over the world. Today most of the energy used comes from fossil fuels. The constant exploitation of fossil fuels creates an adverse effect on the environment. Due to increasing energy demand and global warming identification and utilization of new renewable sources of energy site is crucial importance to reduce the energy shortage and fossil fuel dependency throughout the country. In this thesis the three PV configuration series, series-parallel and total cross tied are considered. This thesis investigates Optimal Maximum Power Point Tracking Algorithms for Solar Photovoltaic Configurations. An optimal maximum power point tracking of PV Configurations incorporation with adaptive neural network optimized fuzzy-PI controller are modeled, designed, and simulated by using MATLAB/Simulink software. A simulation result is observed by using a ANN based fuzzy-PI. It is observed from the MATLAB simulation results, the effects of system performance measuring variables by using ANN optimized fuzzy-PI controller are tested for different PV configuration and the TCT configuration is the better performed PV configuration. The effects of system performance measuring variables by using ANN optimized Fuzzy Logic PI controller are tested for different PV configuration and it have good controllable effect in the three configurations. Generally, fuzzy-PI controller by itself is poor control system stability performance measuring variables, it only considers steady-state frequency error approaches to zero at various load changes. Therefore, both the transient and steady-state control system stability performance measuring variables in all the three configurations are improved by ANN optimized Fuzzy-PI controller. The controller works efficiently under all PV configurations because, this controller is suitable for complex, nonlinear, uncertain, higher-order, and time-delay systems.en_US
dc.description.sponsorshipASTUen_US
dc.identifier.urihttp://10.240.1.28:4000/handle/123456789/2006
dc.language.isoen_USen_US
dc.publisherASTUen_US
dc.subjectMaximum Power Point Tracking (MPPT), Photovoltaic (PV), Fuzzy-PI Controller, MATLAB/Simulink, Renewable Energy Sourceen_US
dc.titleMaximum Power Point Tracking Algorithms for Solar Photovoltaic Configurations using ANN optimized Fuzzy-PID controlleren_US
dc.typeThesisen_US

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