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On-line measurement-based model parameter estimation for synchronous generators: model development and identification schemes

机译:基于在线测量的同步发电机模型参数估计:模型开发和识别方案

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摘要

Accurate generator modeling allows for more precise calculations of power system control and stability limits. In this paper, a procedure using a set of measured data from an online plant transient recording and analysis system to develop the synchronous generator model for the Taipower system is described. A continuous-time transfer function matrix is derived for a popular sixth-order synchronous generator model. In order to accommodate the nature of online digital measurements, the transfer function matrix is transformed into a simple discrete-time linear regression model. A measure of discrepancy between the generator model outputs and the online measurements from generators is employed. A modified conjugate gradient method suitable for identifying generator parameters is developed to minimize the measure of discrepancy, from which a set of accurate generator parameter values can be obtained. The merits of the modified conjugate gradient method include its computational efficiency and numerical reliability. The proposed procedure allows simultaneous estimation of all generator parameter values.
机译:精确的发电机建模可以更精确地计算电力系统控制和稳定性极限。在本文中,描述了一种程序,该程序使用来自在线工厂暂态记录和分析系统的一组测量数据来开发台电系统的同步发电机模型。对于流行的六阶同步发电机模型,导出了一个连续时间传递函数矩阵。为了适应在线数字测量的性质,将传递函数矩阵转换为简单的离散时间线性回归模型。使用发电机模型输出与发电机在线测量之间的差异度量。开发了一种适合于识别发电机参数的改进的共轭梯度方法,以最小化差异的度量,从中可以获得一组准确的发电机参数值。改进的共轭梯度法的优点包括其计算效率和数值可靠性。所提出的过程允许同时估计所有发电机参数值。

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