Slow Coherency Identification and Power System Dynamic Model Reduction by Using Orthogonal Structure of Electromechanical Eigenvectors
Slow Coherency Identification and Power System Dynamic Model Reduction by Using Orthogonal Structure of Electromechanical Eigenvectors
复制标题
利用机电特征向量正交结构的慢相干识别和电力系统动态模型简化
DOI：
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发表时间：
2020
影响因子：
6.6
通讯作者：
V. Terzija
中科院分区：
文献类型：
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作者：
I. Tyuryukanov;M. Popov;Mart A. M. M. van der Meijden;V. Terzija
识别发电机相对于慢振荡模式的一致性有许多电力系统用例，包括动态模型简化、动态安全分析或系统完整性保护方案(例如，电力系统孤岛)。尽管经典的基于特征向量的慢相关技术在研究和工业中都很受欢迎，但它们可能并不总是返回准确的结果。过去为提高它们的准确性所做的多次努力往往缺乏坚实的数学基础。基于这些不足，我们提出了一种替代的一致性方法来解决生成器的慢一致性问题。首先，提出了一种通过有效地最小化通用归一化割集来准确检测慢相干发生器的新方法。作为一个副产品，新的方法还可以指导慢相干群数量的选择。其次，证明了所提出的慢同调方法与改进的惯性发电机集结方法相结合，即使在选择的发电机组数目相对较少的情况下，也可以产生准确的动态等值。
Identifying generator coherency with respect to slow oscillatory modes has numerous power system use cases including dynamic model reduction, dynamic security analysis, or system integrity protection schemes (e.g., power system islanding). Despite their popularity in both research and industry, classic eigenvector-based slow coherency techniques may not always return accurate results. The multiple past endeavors to improve their accuracy often lack a solid mathematical foundation. Motivated by these deficiencies, we propose an alternative consistent approach to generator slow coherency. Firstly, a new approach is introduced to accurately detect slow coherent generators by effectively minimizing generic normalized cuts. As a by-product, the new approach can also guide the choice of the number of slow coherent groups. Secondly, it is shown that the combination of the the proposed slow coherency approach and an enhanced version of the inertial generator aggregation method allows to produce accurate dynamic equivalents even if the selected number of generator groups is relatively low.
影响因子：
6.6
作者：
Rubén J. Sánchez-García;Max Fennelly;S. Norris;N. Wright;Graham A. Niblo;J. Brodzki;J. Bialek
通讯作者：
Rubén J. Sánchez-García;Max Fennelly;S. Norris;N. Wright;Graham A. Niblo;J. Brodzki;J. Bialek
影响因子：
2.5
作者：
Quiros-Tortos, Jairo;Sanchez-Garcia, Ruben;Terzija, Vladimir
通讯作者：
Terzija, Vladimir