Input signals selection for measurement-based power system ARX dynamic model response estimation

F. Bai, Yilu Liu, K. Sun, N. Bhatt, A. del Rosso, E. Farantatos, Xiaoru Wang
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引用次数: 5

Abstract

This paper proposes a measurement-based approach to optimize the inputs of Auto-Regressive with eXogenous input (ARX) model identification in large power systems. Correlation Coefficient Index (CCI) is defined in this paper and Correlation Coefficient Map (CCM) is developed for the US Eastern Interconnection (EI) to show the correlation between any two power system output measurement signals visually. This approach is verified with EI system simulation data and applied to Frequency Disturbance Recorder (FDR) measurement data to estimate system dynamic response. The verification result shows that the number of ARX model inputs can be decreased and the estimation accuracy can be ensured by using the proposed approach.
基于测量的电力系统ARX动态模型响应估计的输入信号选择
本文提出了一种基于测量的方法来优化大型电力系统中带有外生输入的自回归(ARX)模型辨识。本文定义了相关系数指数(CCI),并针对美国东部电网(EI)开发了相关系数图(CCM),以直观地显示任意两个电力系统输出测量信号之间的相关性。通过EI系统仿真数据验证了该方法的有效性,并将其应用于频率扰动记录仪(FDR)的测量数据中进行系统动态响应估计。验证结果表明,采用该方法可以减少ARX模型输入的数量,保证估计精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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