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Neural Computing and Applications

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31-03-2018 | Original Article

Fuzzy logic controller-based MPPT for hybrid photo-voltaic/wind/fuel cell power system

Authors: Mohammad Junaid Khan, Lini Mathew

Published in: Neural Computing and Applications | Issue 10/2019

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Abstract

The non-conventional energy sources possess a major problem of power reliability due to their dependencies on the environment. Advance research and development in solar, wind and other renewable energy sources are needed to solve the problem of power demand and reliability. The proposed hybrid system incorporates three renewable energy systems consisting of photo-voltaic (PV), wind turbine (WT) and fuel cell (FC) systems working together to provide maximum power at DC-link. A vast deal of novel research is done for improving the efficiency of an overall system using maximum power point tracking (MPPT) method. In this paper, the developed fuzzy logic controller (FLC)-based MPPT method has been used to analyze PV, WT and FC with DC–DC converters. The FLC-based MPPT control method optimizes the output of the proposed hybrid system with variable inputs to extract maximum power. In order to fabricate a reliable hybrid system, there is a massive scope of research to develop multi-input renewable energy systems.

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Title: Fuzzy logic controller-based MPPT for hybrid photo-voltaic/wind/fuel cell power system
Authors: Mohammad Junaid Khan
Lini Mathew
Publication date: 31-03-2018
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 10/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-018-3456-7

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