机电模式识别的proony与特征系统实现算法的比较研究

Niloy Sarkar, Krishna Rao, K. Shubhanga
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引用次数: 3

摘要

对基于测量的两种机电模式识别算法proony和特征系统实现算法(ERA)进行了比较研究。在实际的电力系统中,励磁模式的数目可能会发生变化,因此模型的顺序不容易确定。在proony中,这需要一个迭代过程,而在ERA中,基于奇异值分解(SVD)的技术直接实现了这一点,通过两个案例研究进行了演示。进一步表明,与proony相比,ERA对信号的估计更好,产生的平凡模式数量更少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparative Study Between Prony and Eigensystem Realization Algorithm for Identification of Electromechanical Modes
Two measurement-based ring-down electromechanical mode identification algorithms, namely Prony and Eigensystem Realization Algorithm (ERA) are taken up for a comparative study. Since the number of excited modes might vary in a practical power system, it is not easy to determine the model order. This requires an iterative procedure in case of Prony whereas a Singular Value Decomposition (SVD)-based technique achieves this directly in case of ERA as demonstrated through two case studies. It is further shown that ERA estimates the signal better and generates less number of trivial modes as compared to Prony.
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