SVD-Based Voltage Stability Assessment From Phasor Measurement Unit Data
SVD-Based Voltage Stability Assessment From Phasor Measurement Unit Data
复制标题
DOI：
10.1109/tpwrs.2015.2487996
复制
发表时间：
2016-07
影响因子：
6.6
通讯作者：
J. Lim;C. DeMarco
中科院分区：
文献类型：
--
作者：
J. Lim;C. DeMarco
电力系统可能显示出一系列不期望的动态现象，通过这些现象，可接受的稳定操作可能会丢失。准稳态运行问题，如电压不稳定现象，就是其中之一。反映在总线电压幅值对负载变化的高灵敏度中的功率流的病态是经常观察到的这种准稳态操作问题的前兆。受此启发，这里的工作将提出一个电压稳定性和调节监视器，是无模型的实时，仅基于相量测量单元（PMU）的数据，认为这种方法非常适合于近实时应用。我们回顾了电压稳定评估中的模型相关奇异值分析，并将这些现有方法与我们提出的实时应用中的无模型方法联系起来。该算法首先适用于所有总线的完整测量数据的理想化假设下。这项工作，然后扩展的算法，适用于更实际的情况下，只有子集的总线有可用的测量数据。所提出的方法在IEEE的测试案例中说明，增强，包括重负荷条件下，应力电压稳定。有效的算法计算的小数目的奇异值，以及利用低秩更新数据的手段，进行审查，以证明快速计算的机会，使这些SVD方法在大型系统中的近实时操作。
Electric power systems can display a range of undesirable dynamic phenomena by which acceptable, stable operation may be lost. Quasi-steady-state operational problems such as the voltage instability phenomena are among these. Ill-conditioning of the power flow, reflected in high sensitivity of bus voltage magnitudes to load variation is an often observed precursor to such quasi-steady state operational problems. Motivated by this insight, work here will propose a voltage stability and conditioning monitor that is model-free in real-time, based solely on phasor measurement unit (PMU) data, arguing that such an approach is well suited to near-real-time application. We review model-dependent singular value analysis in voltage stability assessment, and relate these existing approaches to our proposed model-free method in real-time application. The proposed algorithm is first applied under the idealized assumption of full measurement data at all buses. This work then extends the algorithm to apply in the more practical case for which only subset of buses have available measurement data. The proposed approach is illustrated in IEEE test cases, augmented to include heavy load conditions that stress voltage stability. Algorithms for efficient computation of small numbers of singular values, as well as means to exploit low-rank updates in data, are reviewed to demonstrate opportunities for fast computation that allow these SVD methods to operate in near-real-time in large systems.