Research Article | OPEN ACCESS
Design of a Neural Controller for Single Phase Inverter in Grid Connected Photovoltaic System
1A. Ndiaye, 1L. Thiaw, 1G. Sow, 1S.S. Fall, 1M. Thiam, 1M. Kasse and 2G. Sissoko
1Laboratory of Renewable Energy, Polytechnic Higher School,
University Cheikh Anta Diop, Dakar-Fann, Senegal
2Laboratory of Semiconductors and Solar Energy, Physics Department, Faculty of
Science and Technology, University Cheikh Anta Diop, Dakar, Senegal
Research Journal of Applied Sciences, Engineering and Technology 2014 6:1149-1155
Received: February 27, 2013 | Accepted: March 27, 2013 | Published: February 15, 2014
Abstract
This study shows a neural network based control strategy of the current injected into a single-phase grid via an inverter. The inverter is supplied by a Photovoltaic Generator (PVG). The optimal control of PVG is ensured by an MPPT algorithm of type P and O (Perturbation-Observation). The synchronization of the inverter with the electrical grid is ensured by a Phase-Locked Loop (PLL) device. The sizing and the modeling of the system components have been presented. A Neural Network Controller (NNC) and a Proportional Integral (PI) controller have been implemented and compared. Obtained results show that the NNC have faster response and lower THD without overshoots.
Keywords:
Modeling, MPPT, neural network controller, proportional integral controller, single-phase inverter,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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The authors have no competing interests.
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