Real-time execution of linear ringdown analysis methods for identifying dominant modes

2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA) Pub Date : 2022-05-24 DOI:10.1109/SGSMA51733.2022.9806011

F. E. Reyes, M. G. Juarez, A. Zamora, J. Ortiz, J. C. Silva, M. Paternina, C. Toledo-Santos

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Abstract

This paper specializes in the real-time execution of three mature linear ringdown analysis methods for modal identification in power systems. Data-based identification methods such as Prony’s method, eigensystem realization algorithm, and matrix pencil are embedded into a Matlab & Simulink-powered real-time simulation environment. Their implementations are achieved by using a sliding window approach, are profited by the inherent features of a parallel computing software architecture, reduce the computational complexity of the methods through shorttime windows length, and provide instantaneous modal information (damping and frequency). These enhancements make part of a user-friendly tool to effectively deal with the modal identification issue. This tool is successfully tested using two test power systems: the two-area Kundur system and a reduced-order representation of the New England power grid. Its effectiveness and performance are demonstrated with the attained results and its validation.

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实时执行线性铃响分析方法，以识别优势模式

本文研究了三种成熟的线性衰荡分析方法在电力系统模态识别中的实时执行。基于数据的识别方法，如proony方法，特征系统实现算法和矩阵铅笔嵌入到Matlab和simulink驱动的实时仿真环境中。它们的实现是通过使用滑动窗口方法实现的，得益于并行计算软件架构的固有特征，通过短时间窗口长度减少了方法的计算复杂性，并提供瞬时模态信息(阻尼和频率)。这些增强功能构成了用户友好工具的一部分，可以有效地处理模态识别问题。该工具已成功地使用两种测试电力系统进行了测试:两区Kundur系统和新英格兰电网的降阶表示。通过所获得的结果及其验证，证明了该方法的有效性和性能。

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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来源期刊

2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)

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