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首页> 外文期刊>Electric power systems research >An Intelligent Power Factor Corrector For Power System Using Artificial Neural Networks
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An Intelligent Power Factor Corrector For Power System Using Artificial Neural Networks

机译：基于人工神经网络的电力系统智能功率因数校正器

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摘要

An intelligent power factor correction approach based on artificial neural networks (ANN) is introduced. Four learning algorithms, backpropagation (BP), delta-bar-delta (DBD), extended delta-bar-delta (EDBD) and directed random search (DRS), were used to train the ANNs. The best test results obtained from the ANN compensators trained with the four learning algorithms were first achieved. The parameters belonging to each neural compensator obtained from an off-line training were then inserted into a microcontroller for on-line usage. The results have shown that the selected intelligent compensators developed in this work might overcome the problems occurred in the literature providing accurate, simple and low-cost solution for compensation.
机译：介绍了一种基于人工神经网络的智能功率因数校正方法。四种学习算法，反向传播（BP），delta-bar-delta（DBD），扩展delta-bar-delta（EDBD）和定向随机搜索（DRS）被用于训练ANN。首先获得了用四种学习算法训练的ANN补偿器获得的最佳测试结果。然后，将从离线训练中获得的属于每个神经补偿器的参数插入到微控制器中以进行在线使用。结果表明，在这项工作中选择的智能补偿器可以克服文献中出现的问题，从而为补偿提供准确，简单和低成本的解决方案。

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