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Synchronous Generator Parameter Estimation Using Data Collected with Machine in Closed-loop Operation

机译:闭环运行中使用机器收集的数据进行同步发电机参数估计

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摘要

Knowledge of synchronous generator physical parameters (such as rotor inertia, inductances, etc.) is desirable for power system analysis and control. Experiments for parameter identification of a synchronous generator, multi-variable, non-linear system can be carried out only with the controllers in action. In this article, estimation of the physical parameters of such systems is investigated using data collected from the machine in closed-loop operation. To obtain good accuracy of parameter estimates, both discrete and continuous-time model structures have been considered. Continuous-time generalized Poisson moment functional method has proven to be very effective. Results of simulation studies with the machine in closed-loop operation show the effectiveness of this approach. Monte Carlo simulations are also used to show the low variance of the estimates in a noisy environment.
机译:同步发电机物理参数(例如转子惯性,电感等)的知识对于电力系统分析和控制是理想的。同步发电机,多变量,非线性系统的参数识别实验只能在使用控制器的情况下进行。在本文中,使用从机器在闭环操作中收集的数据来研究此类系统的物理参数估计。为了获得良好的参数估计精度,已经考虑了离散和连续时间模型结构。连续时间广义泊松矩函数方法已被证明是非常有效的。机器在闭环运行中的仿真研究结果表明了这种方法的有效性。蒙特卡洛模拟还用于显示嘈杂环境中估计值的低方差。

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