E3S Web Conf.
Volume 152, 20202019 International Conference on Power, Energy and Electrical Engineering (PEEE 2019)
|Number of page(s)||5|
|Section||Photovoltaic Power Generation System and Technology|
|Published online||14 February 2020|
Maximum Power Point tracking for a stand-alone photovoltaic system using Artificial Neural Network
Department of Electronic Engineering University of Science and Technology Houari Boumedien Algiers, Algeria
2 Department of Electrical Engineering High school of Polytechnic ENP Algiers, Algeria
* Corresponding author: firstname.lastname@example.org
This paper presents an intelligent method to extract the maximum power from the photovoltaic panel using artificial neural network (ANN). The inputs data required for training the ANN controller are obtained from real weather conditions and the desired output is obtained from perturb and observe (P&O) method. The proposed model is capable to improve the dynamic response and steady-state performance of the system, provides an accurate identification of the optimal operating point and an accurate estimation of the maximum power from the photovoltaic panels. The proposed ANN model is compared with conventional P&O model and shown that ANN controller could increase the power output by approximately 20%. The system is simulated and studied using MATLAB software.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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