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ISSN No: 2349-2287 (P) | E-ISSN: 2349-2279 (O) | E-mail: editor@ijiiet.com

Title : ARTIFICIAL NEURAL FUZZY BASED MPPT FOR HIGH GAIN ZETA CONVERTER FOR STANDALONE PV APPLICATION WITH GALVANIC ISOLATION

Author : Mr. Gandham Srinivasa Rao, Mr. Gandham Srinivasa Rao

Abstract :

The installation of photovoltaic (PV) systems is on the rise globally because they provide the most direct connection to the power grid. It takes a lot of work for photovoltaic (PV) systems to work as intended. Therefore, with the help of the ANFIS MPPT method, this project aims to stabilize the DC-link voltage of the ZETA Converter. The suggested method employs a ZETA converter, which enhances voltage gain and decreases ripple content in the current and voltage outputs. To provide galvanic isolation, the system incorporates an isolation transformer. By separating the high-frequency converter's output from the PV system and other parts, this transformer improves safety. Protecting linked loads from electrical fault transfer is the purpose of galvanic isolation. A rectifier is used to provide a DC load with the output of the isolation transformer. The rectifier is designed to power DC loads by converting the transformer's alternating current (AC) output to direct current (DC). Using an

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