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A Method for Variance-Based Sensitivity Analysis of Cascading Failures
IEEE Transactions on Power Delivery ( IF 3.8 ) Pub Date : 8-15-2022 , DOI: 10.1109/tpwrd.2022.3199150
Aaron S. C. Leavy 1 , Georgios A. Nakas 1 , Panagiotis N. Papadopoulos 1
Affiliation  

Cascading failures of relay operations in power systems are inherently linked with the propagation of wide-area power system blackouts. In this paper, we consider a power system cascading failure as an indicator matrix encoding: what power system relays operated within a cascading failure inherently capturing the component and the sequence of tripping events. We propose that this matrix may then be used with extended forms of variance-based sensitivity estimators to quantitatively rank how sensitive observed power system cascading failures are to power system variables, considering overall system cascading failures as well as cascading failures grouped by network area and relay types. We demonstrate our proposed method by investigating the sensitivity of cascading failures to relay parameters, system conditions, and fault location using a version of the IEEE 39 bus model modified to include protection relays, wind farms, and tap-changing transformers. Input power system variables included: system operational scenario, disturbance location, relay parameters or thresholds. The Case Studies' results confirm the method's utility by successfully generating relative rankings of input variables' importance with respect to cascading failure propagation. The results also show cascading failures' sensitivity to input variables to be high due to non-linear relationships between input variables and cascading failures.

中文翻译:


一种基于方差的连锁故障敏感性分析方法



电力系统中继电器操作的级联故障与大范围电力系统停电的蔓延有着内在的联系。在本文中,我们将电力系统级联故障视为指标矩阵编码:在级联故障中哪些电力系统继电器运行,固有地捕获组件和跳闸事件的序列。我们建议,然后将该矩阵与基于方差的敏感性估计器的扩展形式一起使用,以定量排列观察到的电力系统级联故障对电力系统变量的敏感程度,考虑整个系统级联故障以及按网络区域和继电器分组的级联故障类型。我们通过使用经过修改以包括保护继电器、风电场和抽头变换变压器的 IEEE 39 总线模型版本来调查级联故障对继电器参数、系统条件和故障定位的敏感性,从而演示了我们提出的方法。输入电力系统变量包括:系统运行场景、扰动位置、继电器参数或阈值。案例研究的结果通过成功生成输入变量相对于级联故障传播的重要性的相对排名,证实了该方法的实用性。结果还表明,由于输入变量和级联故障之间的非线性关系,级联故障对输入变量的敏感性很高。
更新日期:2024-08-26
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