Privacy preserving decentralized power system state estimation with phasor measurement units

Neelabh Kashyap, S. Werner, Yih-Fang Huang, R. Arablouei
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引用次数: 5

Abstract

This paper presents a privacy preserving approach to decentralized state estimation in multi-area power systems. By formulating state estimation as a model-distributed regularized least-squares (MDRLS) problem, we ensure that the state variables and system matrix of each area are hidden from all other areas in order to protect privacy and sensitive information. We present a scheme that solves the primal MDRLS problem using the alternating direction method of multipliers, and a second method that solves the dual problem using a distributed form of the coordinate descent algorithm. Only information related to current measurements on tie-lines linking neighboring areas is exchanged between those areas. The proposed schemes enable the local state estimator in each area to estimate the voltage magnitude and phase angle of each bus in its own control area from phasor measurement units (PMU) without the need for full local PMU-observability. The novelty of the proposed methods is in that they employ the inherently hierarchical architecture of the wide-area monitoring system to perform decentralized state estimation. Our simulation results show that the estimation error of both methods converges to that of the centralized approach.
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基于相量测量单元的分散电力系统状态估计
提出了一种保护隐私的多区域电力系统分散状态估计方法。通过将状态估计表述为一个模型分布正则化最小二乘(MDRLS)问题,我们确保每个区域的状态变量和系统矩阵对所有其他区域都是隐藏的,以保护隐私和敏感信息。我们提出了一种使用乘法器交替方向法解决原始MDRLS问题的方案,以及使用坐标下降算法的分布式形式解决对偶问题的第二种方法。这些地区之间只交换与连接邻近地区的联络线当前测量值有关的信息。提出的方案使每个区域的局部状态估计器能够从相量测量单元(PMU)估计其控制区域内每个母线的电压幅度和相角,而无需完全的局部PMU可观测性。所提方法的新颖之处在于它们利用广域监测系统固有的层次结构来执行分散的状态估计。仿真结果表明,两种方法的估计误差都收敛于集中式方法的估计误差。
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