基于多测点正序电压相关性与典型模式匹配寻优的电压暂降源定位

为解决故障类型和过渡电阻对电压暂降源定位结果的影响,提出了一种基于多测点正序电压相关性与典型模式匹配寻优的电压暂降源定位方法。该方法首先采用多个测点故障前后的正序电压变化量作为特征量构建故障模式,采用欧式距离测度和Spearman秩相关系数定义模式之间的相似度。在各支路中点预设故障形成典型模式群,此后将测点正序电压量测量构成的待识别模式与典型模式群进行相似匹配,根据相似度将典型模式聚类为多个子群,将相似度最大的子群所对应的线路组成初选故障线路集,缩小定位搜索空间。最后建立最优估计模型,以相似度最大为目标函数,以初选故障线路集中的故障线路号及故障距离为优化变量,寻找最优匹配的故障模式,利用自适应粒子群优化算法对模型进行求解,确定故障线路和故障位置。采用IEEE 30和IEEE 33节点系统验证了该方法的可行性和有效性,结果表明该方法能有效克服故障类型和过渡电阻对电压暂降源定位的影响,定位精度高。

Voltage Sag Source Location Based on the Correlation of Multipoint Positive Sequence Voltage and the Typical Pattern Matching Optimization

A novel method of voltage sag source location based on the correlation of multipoint positive sequence voltage and the typical pattern matching optimization is proposed to make the location results independent of fault type and transition resistance.Firstly,it builds the fault pattern using the positive sequence voltage variation at measuring points and defines the pattern similarity based on the Euclidean distance measure and the Spearman rank correlation coefficient.Then it forms the set of typical patterns by setting up a preset fault at the middle of each branch and clusters it into several subgroups according to the similarity of the measuring sequence and typical patterns.It chooses the corresponding lines of the subgroup with the highest similarity to make up the primary fault line set,which can effectively narrow the searching space.Finally,an optimal estimation model is built to find the optimal matching fault pattern.The object function is to maximize the similarity,the primary fault line and fault distance are chosen as optimization variables.The model is solved by particle swarm optimization algorithm,fault line and fault position can be obtained.The numerical examples of IEEE 30 and IEEE 33 system show the feasibility and validity of the proposed method.The results show that the method can effectively eliminate the influence of fault type and transition resistance and has higher location accuracy than previous methods.