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Dynamic compensator design for HV AC power system using artificial neural networks

机译:利用人工神经网络的HV交流电力系统动态补偿器设计

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This paper presents a method for designing a dynamic compensator based on artificial neural networks (ANN). The ANN is trained to give the proper compensator parameters (X, Tz) so as to always assign certain eigenvalues to desired locations in the output feedback system. The eigenvalues of concern are those associated with the angle /spl delta/ and speed /spl omega/. These eigenvalues are to be assigned to the specified locations under variations in several system parameters [static nonlinear load parameters A/sub p/ and A/sub q/, transmission line reactance, x/sub e/, and generated real power, P/sub G/]. The exact and ANN's results of compensator's parameters are plotted. In addition speed response is provided for the compensated and uncompensated systems. Results show that the ANN can be used on line once the off line training is performed to determine the compensator data so as to maintain the desired response of the system under variations in system parameters.
机译:本文介绍了一种基于人工神经网络(ANN)设计动态补偿器的方法。 ANN受过培训,以提供适当的补偿器参数(x,tz),以便始终将某些特征值分配给输出反馈系统中的所需位置。关注的特征值是与角度/ SPLδ和速度/ SPL omega /相关联的特征值。这些特征值将被分配给在若干系统参数中的变化下的指定位置[静态非线性负载参数a / sub p / a / sub q /,传输线电抗,x / sub e /,和生成的实力,p /子g /]。绘制了补偿器参数的确切和Ann的结果。此外,还提供了补偿和未补偿的系统的速度响应。结果表明,一旦执行偏差训练以确定补偿器数据,可以在线使用ANN,以便在系统参数的变化下维持系统的所需响应。

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