基于IncCond算法的神经网络MPP跟踪器

Jinbang Xu, A. Shen, Cheng Yang, Wenpei Rao, Xuan Yang
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引用次数: 28

摘要

在光伏发电系统中,太阳能输出功率的最大化是提高整个系统效率的关键环节。本文提出了一种新的基于人工神经网络的最大功率点跟踪算法。利用传统增量电导(IncCond)方法的最优结果生成的占空比数据作为神经网络训练数据,构建DC-DC升压跟踪器在Saber仿真软件中进行测试,仿真结果表明了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANN Based on IncCond Algorithm for MPP Tracker
In photovoltaic (PV) generation systems, to get the maximum of the solar output power is the essential part to raise the efficiency of the whole system. A new Artificial Neural Network (ANN) based algorithm for Maximum Power Point Tracking (MPPT) has been proposed in this work. By using the duty ratio data generated from the finest results of the traditional Incremental Conductance (IncCond) method as the neural network training data, and building the DC-DC boost tracker to test it in Saber simulation software, the simulation results are shown to clarity the effectiveness of the proposed method.
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