首页> 外文期刊>IEEE Transactions on Energy Conversion >Artificial neural network power system stabilizers in multi-machine power system environment
【24h】

Artificial neural network power system stabilizers in multi-machine power system environment

机译:多机电力系统环境中的人工神经网络电力系统稳定器

获取原文
获取原文并翻译 | 示例

摘要

The effectiveness of an artificial neural network (ANN), functioning as a power system stabilizer (PSS), in damping multi-mode oscillations in a five-machine power system environment is investigated in this paper. Accelerating power of the generating unit is used as the input to the ANN PSS. The proposed ANN PSS using a multilayer neural network with error-backpropagation training method was trained over the full working range of the generating unit with a large variety of disturbances. The ANN was trained to memorize the reverse input/output mapping of the synchronous machine. Results show that the proposed ANN PSS can provide good damping for both local and inter-area modes of oscillations.
机译:本文研究了人工神经网络(ANN)作为电力系统稳定器(PSS)在五机电力系统环境中阻尼多模振荡的有效性。发电单元的加速功率用作ANN PSS的输入。拟议的ANN PSS使用带有误差反向传播训练方法的多层神经网络,在具有各种干扰的发电机组的整个工作范围内进行了训练。对ANN进行了培训,以记住同步电机的反向输入/输出映射。结果表明,所提出的ANN PSS可以为局部和区域间振荡模式提供良好的阻尼。

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