PMU Placement Optimization for Efficient State Estimation in Smart Grid
PMU Placement Optimization for Efficient State Estimation in Smart Grid
复制标题
DOI：
10.1109/jsac.2019.2951969
复制
发表时间：
2020-01-01
影响因子：
16.4
通讯作者：
Savkin, Andrey, V
中科院分区：
文献类型：
--
作者：
Shi, Ye;Hoang Duong Tuan;Savkin, Andrey, V
通过引入各种可观测性约束，研究了智能电网中相量测量单元（PMU）的信息状态估计问题。可观察性是PMU放置的一个重要属性，用来表征PMU放置的总线可达性深度，但在许多工作中，仅通过二进制线性规划来解决这一问题仍然不能保证对电网状态的良好估计。一些现有的工作已经考虑了一些估计指标的优化，通过忽略可观测性要求来简化计算，从而可能导致琐碎的结果，例如接受对未观测状态分量的估计作为其无条件平均值。在这项工作中，PMU放置优化问题是通过最小化均方误差或最大化测量输出和受可观测性约束的电网状态之间的互信息来考虑的，这些约束包括零注入总线的存在、测量损失的偶然性和每个PMU通信信道的限制等运行条件。因此，提出的设计是自由的，从现有的PMU安置设计的根本缺点。该问题被提出为涉及数千个二元变量的大型二元非线性优化问题，本文为此开发了有效的计算解算法。通过大型IEEE电网的数值算例，详细分析了它们的性能。该方法也可推广到用非线性方程表示的交流潮流模型。
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.