This paper investigates phasor measurement unit (PMU) placement for informative state estimation in smart grid by incorporating various constraints for observability. Observability constitutes an important property for PMU placement to characterize the depth of the buses’ reachability by the placed PMUs, but addressing it solely by binary linear programming as in many works still does not guarantee a good estimate for the grid state. Some existing works have considered optimization of some estimation indices by ignoring the observability requirements for computational ease and thus potentially lead to trivial results such as acceptance of the estimate for an unobserved state component as its unconditional mean. In this work, the PMU placement optimization problem is considered by minimizing the mean squared error or maximizing the mutual information between the measurement output and grid state subject to observability constraints, which incorporate operating conditions such as presence of zero injection buses, contingency of measurement loss, and limitation of communication channels per PMU. The proposed design is thus free from the fundamental shortcomings in the existing PMU placement designs. The problems are posed as large scale binary nonlinear optimization problems involving thousands of binary variables, for which this paper develops efficient algorithms for computational solutions. Their performance is analyzed in detail through numerical examples on large scale IEEE power networks. The solution method is also shown to be extendable to AC power flow models, which are formulated by nonlinear equations.

中文翻译：

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用于智能电网中有效状态估计的 PMU 布局优化

本文通过结合各种可观察性约束，研究智能电网中信息状态估计的相量测量单元 (PMU) 布置。可观察性构成了 PMU 放置的一个重要属性，用于表征放置的 PMU 对总线可达性的深度，但在许多工作中仅通过二进制线性规划解决它仍然不能保证对网格状态的良好估计。一些现有的工作已经考虑通过忽略可观察性要求来优化某些估计指数以简化计算，从而可能导致微不足道的结果，例如接受对未观察到的状态分量的估计作为其无条件均值。在这项工作中，PMU 布局优化问题是通过最小化均方误差或最大化测量输出和电网状态​​之间的互信息来考虑的，受可观察性约束，其中包括诸如存在零注入总线、测量损失的偶然性和限制每个 PMU 的通信通道。因此，所提出的设计没有现有 PMU 布局设计中的根本缺陷。这些问题被提出为涉及数千个二元变量的大规模二元非线性优化问题，为此本文开发了用于计算解决方案的有效算法。通过大规模 IEEE 电力网络的数值例子详细分析了它们的性能。该求解方法也被证明可扩展到交流潮流模型，