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ARMAX-based transfer function model identification using wide-area measurement for adaptive and coordinated damping control

机译:基于广域测量的基于ARMAX的传递函数模型识别,用于自适应和协调阻尼控制

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摘要

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. This paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-output (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. The results demonstrate that the measurementbased model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.
机译:基于离线动态模型设计的现有振荡阻尼控制器的主要缺点之一是对电力系统运行条件的适应性。随着广域测量可用性的提高和系统识别技术的迅速发展,可以在线识别基于测量的传递函数模型,该模型可用于调整振荡阻尼控制器。这样的模型可以捕获所有主导振荡模式,以进行自适应和协调的振荡阻尼控制。本文介绍了一种使用多输入多输出(MIMO)自回归移动平均外生(ARMAX)模型来识别电力系统低阶传递函数模型的综合方法。该方法包括五个步骤:1)输入选择; 2)输出选择; 3)识别触发; 4)模型估计; 5)模型验证。通过在16机68辆东北电力协调委员会系统中使用环境数据和振铃数据验证了该方法的有效性。结果表明,使用MIMO ARMAX的基于测量的模型可以捕获所有主要的振荡模式。与MIMO子空间状态空间模型相比,MIMO ARMAX模型具有相同的精度,但具有较低的阶数并提高了计算效率。所提出的模型可以用于自适应和协调的振动阻尼控制。

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