基于最小变异系数的配电网电压暂降源模型识别方法

Fault location of distribution network based on minimal coefficient of variation using identifying model

提出了一种基于最小变异系数的配电网电压暂降源模型识别故障定位方法。该方法通过获得配电网中各个节点短路时监测点所测得的电压暂降特性,建立在不同故障类型条件下的电压暂降源识别模型,根据实际配电网发生故障时监测点所测得的电压暂降数据,用电压不平衡度公式区分出故障类型后,再与相应故障类型的电压暂降源识别模型进行比对,得到最小平均变异系数的区段则具有最大概率为故障区段。该方法将配电网故障选线和配电网故障区段定位融合在一起,经EMTDC仿真验证,有较高的准确性和有效性。

This paper presents a method for locating short-circuit faults using voltage sags identifying model based on the minimal coefficient of variation. When we know the characteristic of the voltage sags in different place, it is possible to find the fault section. The basic idea of this paper is to build a voltage sags identifying model under different type of faults, and comparing the voltage sags measured by the monitors on-line with the model to compute the coefficient of variation, then the minimal coefficient of variation corresponds to the fault section. This method combines the fault line selection and fault section location in distribution network, and the results of the simulations emulated by EMTDC show that the method is accurate and effective.