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Measurement-Based Estimation of the Power Flow Jacobian Matrix

机译:潮流雅可比矩阵的基于测量的估计

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摘要

In this paper, we propose a measurement-based method to compute the power flow Jacobian matrix, from which we can infer pertinent information about the system topology in near real-time. A salient feature of our approach is that it readily adapts to changes in system operating point and topology; this is desirable as it provides power system operators with a way to update, as the system evolves, the models used in many reliability analysis tools. The method uses high-speed synchronized voltage and current phasor data collected from phasor measurement units to estimate entries of the Jacobian matrix through linear total least-squares (TLS) estimation. In addition to centralized TLS-based algorithms, we provide distributed alternatives aimed at reducing computational burden. Through numerical case studies, we illustrate the effectiveness of our proposed Jacobian-matrix estimation approach as compared with the conventional model-based one.
机译:在本文中,我们提出了一种基于测量的方法来计算潮流雅可比矩阵,从中我们可以近似实时地推断出有关系统拓扑的信息。我们方法的一个突出特点是它可以轻松适应系统工作点和拓扑的变化。这是理想的,因为它为电力系统运营商提供了一种随着系统发展而更新许多可靠性分析工具中使用的模型的方法。该方法使用从相量测量单元收集的高速同步电压和电流相量数据,通过线性总最小二乘(TLS)估计来估计Jacobian矩阵的项。除了基于TLS的集中式算法外,我们还提供了旨在减少计算负担的分布式替代方案。通过数值案例研究,我们说明了与传统的基于模型的方法相比,我们提出的雅可比矩阵估计方法的有效性。

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