• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Energy Conversion & Management >Power factor correction technique based on artificial neural networks
【24h】

Power factor correction technique based on artificial neural networks

机译：基于人工神经网络的功率因数校正技术

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents a novel technique based on artificial neural networks (ANNs) to correct the line power factor with variable loads. A synchronous motor controlled by the neural compensator was used to handle the reactive power of the system. The ANN compensator was trained with the extended delta-bar-delta learning algorithm. The parameters of the ANN were then inserted into a PIC 16F877 controller to get a better and faster compensation. The results have shown that the proposed novel technique developed in this work overcomes the problems occurring in conventional compensators including over or under compensation, time delay and step changes of reactive power and provides accurate, low cost and fast compensation compared to the technique with capacitor groups.
机译：本文提出了一种基于人工神经网络（ANN）的新技术，以校正可变负载下的线路功率因数。由神经补偿器控制的同步电动机用于处理系统的无功功率。 ANN补偿器使用扩展的delta-bar-delta学习算法进行了训练。然后将ANN的参数插入PIC 16F877控制器中，以获得更好，更快的补偿。结果表明，这项工作中提出的新技术克服了常规补偿器中出现的问题，包括过补偿或欠补偿，延时和无功功率的阶跃变化，并且与使用电容器组的技术相比，提供了准确，低成本和快速的补偿。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号