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Neuro-fuzzy based power system stabilizer of a multi-machine system

机译:多机器系统的基于神经模糊的电力系统稳定器

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摘要

This thesis presents a study of neuro-fuzzy power system stabilizer (PSS) for stability enhancement of a multi-machine power system. In order to accomplish a stability enhancement, speed deviation (??) and acceleration (? ) of the rotor synchronous generator were taken as the input to the neuro-fuzzy controller. These variables take significant effects on damping the generator shaft mechanical oscillations. The stabilizing signals were computed using the neuro-fuzzy membership function depending on these variables. Simulink Block Design and Matlab 7.6 were utilized in implementing the study. The simulations were tested under different types of conditions; the steady state operation, the three phases to ground fault, with load connected to the system, mechanical input power changes and reference voltage (Vref) step changes. The performance of the neuro-fuzzy power system stabilizer was compared with the conventional power system stabilizer and without power system stabilizer
机译:本文提出了一种用于提高多机电力系统稳定性的神经模糊电力系统稳定器(PSS)的研究。为了实现稳定性的提高,将转子同步发电机的速度偏差(Δω)和加速度(Δ)作为神经模糊控制器的输入。这些变量对衰减发电机轴的机械振动有重要影响。根据这些变量,使用神经模糊隶属函数计算稳定信号。 Simulink模块设计和Matlab 7.6用于实施研究。模拟在不同类型的条件下进行了测试;在稳态操作中,三相接地故障,负载连接到系统,机械输入功率变化,参考电压(Vref)阶跃变化。将神经模糊电力系统稳定器的性能与常规电力系统稳定器和不具有电力系统稳定器的性能进行了比较

著录项

  • 作者

    Md. Hasnan Syamzurina;

  • 作者单位
  • 年度 2009
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

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