首页> 外文期刊>International journal of electrical power and energy systems >Optimal PMU placement approach for power systems considering non-Gaussian measurement noise statistics
【24h】

Optimal PMU placement approach for power systems considering non-Gaussian measurement noise statistics

机译:考虑非高斯测量噪声统计的电力系统的最佳PMU放置方法

获取原文
获取原文并翻译 | 示例
           

摘要

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.
机译:本文调查了如何为现有监测系统添加有限数量的相量测量单位(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)估计器。然而,现实中,高斯噪声假设并不总是如此,并且在这种情况下,WLS是非稳健的。本文提出了一种新的最佳PMU放置方法,其中测量噪声的分布可以是非高斯或高斯和高斯和许多稳健估计器,例如最大似然估计器,多个段,二次线性,方形 - 根和Schweppe-Huber Generalization-M估计器被考虑。基于从影响函数近似获得的新增益矩阵,在最佳PMU放置问题中利用D-OPTEMAL和E-OPTEMAL实验标准。利用基于Fedorov Exchange算法的优化改进方法的凸松弛来解决优化问题。对IEEE 57总线系统的模拟和波兰2383总线系统进行了评估所提出的方法的有效性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号