Abstract In this paper the Selective Modal Analysis (SMA) method is used for reproducing the eigenvalues involved in subsynchronous control interactions (SSCI) between DFIG-based wind farms and series compensated transmission lines. The SMA method provides a reduced system matrix containing a desired part of the eigenstructure of a system without computing the eigenvalues and eigenvectors of the full system. The key concept for obtaining such reduced matrix resides in an appropriate identification of a subset of state variables and eigenvalues of the system. The intrinsic problems in identifying the corresponding subset for analyzing the SSCI phenomenon are explored and illustrated using a simplified radial system. In addition, a systematic approach for obtaining a subset with minimum dimension is proposed. The methodology consists in a two-phase iterative procedure that reduces the computational load and promotes the convergence of the SMA method to the desired eigenstructure. The proposed algorithm is validated on a relative large power system derived from a practical network.

中文翻译：

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使用选择性模态分析的双馈风电场次同步控制交互研究

摘要 在本文中，选择性模态分析 (SMA) 方法用于再现基于 DFIG 的风电场和串联补偿输电线路之间的次同步控制交互 (SSCI) 中涉及的特征值。SMA 方法提供包含系统特征结构的所需部分的简化系统矩阵，而无需计算整个系统的特征值和特征向量。获得这种简化矩阵的关键概念在于适当识别系统的状态变量和特征值的子集。使用简化的径向系统探索和说明了识别用于分析 SSCI 现象的相应子集的内在问题。此外，还提出了一种获得最小维度子集的系统方法。该方法包括两阶段迭代过程，该过程减少了计算负载并促进了 SMA 方法向所需特征结构的收敛。所提出的算法在一个来自实际网络的相对较大的电力系统上得到了验证。