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Spectral fitting approach to estimate electromechanical oscillation modes and mode shapes by using vector fitting

机译:使用矢量拟合估计机电振荡模式和模式形状的频谱拟合方法

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Wide-area monitoring systems (WAMS) based on phasor measurement units (PMUs) provide the essential information of an electric power system (EPS) in order to face the challenges of generation, operation, and planning. The PMUs are used to obtain the power system ringdown responses. These signals can be analyzed by advanced signal-processing techniques for the estimation of electromechanical modes. This paper proposes a new spectral fitting (SF) approach to estimate these electromechanical oscillation modes and mode shapes by using vector fitting (VF) under noisy conditions. This methodology combines the numerical Laplace transform (NLT) with the VF method. A participation factor is also proposed to identify and detect the system's dominant oscillatory modes. The proposed methodology is demonstrated for a synthetic multi-component signal, a set of noisy synthetic multi-component signals, and numerical simulations of a 16-machine and 68-bus test power system. Results indicate that the proposed technique has the ability and accuracy to carry out a complete identification of electromechanical modes and mode shapes from several ringdown responses, under noisy conditions.
机译:基于相量测量单元(PMU)的广域监视系统(WAMS)提供电力系统(EPS)的基本信息,以应对发电,运行和计划方面的挑战。 PMU用于获取电源系统的振铃响应。这些信号可以通过先进的信号处理技术进行分析,以估计机电模式。本文提出了一种新的频谱拟合(SF)方法,通过在噪声条件下使用矢量拟合(VF)来估计这些机电振荡模式和模式形状。该方法将数值拉普拉斯变换(NLT)与VF方法结合在一起。还提出了一个参与因子,以识别和检测系统的主要振荡模式。演示了所提出的方法,用于合成多分量信号,一组嘈杂的合成多分量信号以及16机和68总线测试电源系统的数值模拟。结果表明,所提出的技术具有在嘈杂条件下从几个振铃响应中完全识别出机电模式和模式形状的能力和准确性。

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