Simulation and control of intelligent photovoltaic system using new hybrid fuzzy-neural method

Simulation and control of intelligent photovoltaic system using new hybrid fuzzy-neural method Nowadays, photovoltaic (PV) generation is growing fast as a renewable energy source. Nevertheless, the drawback of PV system is intermittent for depending on weather conditions. In this paper, a novel topology of intelligent PV system is presented. In order to capture the maximum power, hybrid fuzzy-neural maximum power point tracking method is applied in PV system. As a result, the effectiveness of the proposed method is represented and average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional methods. It has the advantages of robustness, fast response and good performance. Detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have proposed using MATLAB/Simulink. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neural Computing and Applications Springer Journals

Simulation and control of intelligent photovoltaic system using new hybrid fuzzy-neural method

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Publisher
Springer London
Copyright
Copyright © 2016 by The Natural Computing Applications Forum
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Probability and Statistics in Computer Science; Computational Science and Engineering; Image Processing and Computer Vision; Computational Biology/Bioinformatics
ISSN
0941-0643
eISSN
1433-3058
D.O.I.
10.1007/s00521-016-2210-2
Publisher site
See Article on Publisher Site

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