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PV Maximum Power-Point Tracking by Using Artificial Neural Network

机译:人工神经网络跟踪光伏最大功率点

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摘要

In this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under different atmospheric conditions. By properly controling of dc-dc boost converter, tracking of maximum power point is feasible. To verify theory analysis, simulation result is obtained by using MATLAB/SIMULINK.
机译:本文讨论了使用人工神经网络(ANN)跟踪最大功率点。使用误差反向传播方法来训练神经网络。神经网络的优点是可以快速精确地跟踪最大功率点。在这种方法中,使用神经网络来指定不同大气条件下最大功率点的参考电压。通过适当地控制dc-dc升压转换器,跟踪最大功率点是可行的。为了验证理论分析,使用MATLAB / SIMULINK获得了仿真结果。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第3期|p.506709.1-506709.10|共10页
  • 作者单位

    Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, Iran;

    Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, Iran;

    Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, Iran;

    Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, Iran;

    Department of Mechanical and Industrial Engineering, Concordia University, Montreal, QC, Canada;

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