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Voltage Sag State Estimation For Power Distribution Systems Using Kalman Filter

机译:使用Kalman滤波器配电系统的电压SAG状态估计

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The increased awareness on power quality has resulted in the need to quantify the voltage sag performance of a distribution feeder, similar to what has been done on characterizing the reliability performance of a feeder. Since it is impossible to measure the sag level at every node of a distribution feeder, estimation of sag characteristics at unmetered nodes becomes necessary. This paper proposes the concept of "voltage sag state estimation" using a Kalman filter. The applied technique has the following characteristics: 1)It makes use of the model characteristics of a distribution feeder, 2) It is based on a limited number of metering points, and 3) It employs a Kalman filter to estimate the sag profile along a distribution line. The procedure is then applied to part of an IEEE 123 bus distribution test system and the results have been compared with least mean square approach. The comparison shows the improvements provided by this method. The results of the sag state estimator can then be used to calculate the feeder power quality performance indices such as the System Average RMS Frequency Index (SARFIx).
机译:提高对电力质量的认识导致需要量化分配馈线的电压下垂性能,类似于在表征馈线的可靠性性能的情况下进行的。由于不可能测量分配馈线的每个节点处的SAG电平,因此需要在未啮盘节点处的SAG特性的估计。本文提出了使用卡尔曼滤波器的“电压下滑状态估计”的概念。应用技术具有以下特点:1)利用分配馈线的模型特性,2)它基于有限数量的计量点,3)它采用卡尔曼滤波器来估计沿A的凹凸剖视图分销线。然后将过程应用于IEEE 123总线分配测试系统的一部分,并将结果与​​最小均方的方形方法进行了比较。比较显示了该方法提供的改进。然后可以使用SAG状态估计器的结果来计算馈线电力质量性能指标,例如系统平均RMS频率指数(SARFIX)。

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