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Optimal PMU placement approach for power systems considering non-Gaussian measurement noise statistics
International Journal of Electrical Power & Energy Systems ( IF 5.0 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.ijepes.2020.106577
Tengpeng Chen , Yuhao Cao , Xuebing Chen , Lu Sun , Jingrui Zhang , Gehan A.J. Amaratunga

Abstract This paper investigates how to add a limited number of Phasor Measurement Units (PMUs) to the existing monitoring system so as to improve the estimation accuracy further. The existing methods are usually based on Gaussian noise assumption and the weighted least squares (WLS) estimator is taken into account. However, the Gaussian noise assumption is not always true in reality and the WLS is non-robust in this case. This paper proposes a new optimal PMU placement approach where the distribution of measurement noise can be non-Gaussian or Gaussian and many robust estimators such as the maximum likelihood estimator, Multiple-Segment, Quadratic-Linear, Square-Root and Schweppe-Huber Generalized-M estimator are considered. Based on the new Gain matrix obtained from the influence function approximation, the D-optimal and E-optimal experiment criterions are exploited in the optimal PMU placement problem. A convex relaxation in conjunction with an optimization improvement method based on the Fedorov exchange algorithm is utilized to solve the optimizing problem. Simulations on the IEEE 57-bus system and the Polish 2383-bus system are carried out to evaluate the effective performance of the proposed approach.

中文翻译:

考虑非高斯测量噪声统计的电力系统优化 PMU 布置方法

摘要 本文研究如何在现有监测系统中加入有限数量的相量测量单元(PMU),以进一步提高估计精度。现有方法通常基于高斯噪声假设并考虑加权最小二乘(WLS)估计量。然而,高斯噪声假设在现实中并不总是正确的,并且 WLS 在这种情况下是不稳健的。本文提出了一种新的最优 PMU 放置方法,其中测量噪声的分布可以是非高斯或高斯分布,以及许多稳健的估计器,例如最大似然估计器、多段、二次线性、平方根和 Schweppe-Huber Generalized-考虑了 M 估计量。基于影响函数近似得到的新增益矩阵,D 最优和 E 最优实验标准被用于最优 PMU 放置问题。利用凸松弛结合基于 Fedorov 交换算法的优化改进方法来解决优化问题。对 IEEE 57 总线系统和波兰 2383 总线系统进行了仿真,以评估所提出方法的有效性能。
更新日期:2021-03-01
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