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Power system dynamic state estimation considering correlation ofmeasurement error from PMU and SCADA

机译:电力系统动态状态估计考虑PMU和SCADA的逐误差相关

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摘要

It is well known that measurements from phasor measurement unit (PMU) or supervisory controland data acquisition (SCADA) are not generally independent. Since the correlation of measurementerror is a very representative feature of the actual measurement system, traditionalassumptions on error independency are not adequate. In this paper, taking the correlation of measurementerror of both PMU and SCADA measurements into consideration, a novel correlatedextended Kalman filter (CEKF) is proposed. The actual measurement configurations are analyzedwith the consideration of measurement error transfer characteristics. Then, the modified measurementerror covariance matrix is calculated by using the point estimation method, which willreplace the traditional diagonal variance matrix. At last, IEEE 14-bus system and 57-bus systemare provided to illustrate the effectiveness and superiority of the method, respectively.
机译:众所周知,量相测量单元(PMU)或监控控制的测量和数据采集(SCADA)通常不是独立的。自测量的相关性错误是实际测量系统,传统的非常代表性的特征错误独立性的假设不足。本文采取了测量的相关性考虑到PMU和SCADA测量的错误,一种新颖的相关性提出了扩展卡尔曼滤波器(CEKF)。分析了实际测量配置考虑到测量误差传递特性。然后,修改的测量通过使用点估计方法计算错误协方差矩阵,将替换传统的对角线方差矩阵。最后,IEEE 14-Bus系统和57总线系统提供以分别说明方法的有效性和优越性。

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