基于Hausdorff距离与OPTICS聚类的电压暂降同源识别方法

Same-source identification method of voltage sags based on Hausdorff distance and OPTICS clustering

为合理评估、治理电压暂降问题,电网公司大量安装电能质量监测终端,实现电压暂降监测和感知,但同时造成暂降事件被不同监测终端重复记录的数据冗余问题。为此,该文提出基于Hausdorff距离的电压暂降波形相似度计算方法。将波形相似度和持续时间作为同源识别特征,构建电压暂降同源识别特征矩阵;提出基于多维尺度分析(multi-dimensional scaling,MDS)算法的同源识别矩阵数据降维方法,保证识别准确度,提高计算效率。提出基于OPTICS聚类算法的电压暂降同源识别方法,通过聚类可达图得到同源识别结果。最后,选取我国中部某地区电网的实测数据验证所提方法的可行性与准确性。

In order to evaluate and manage the voltage sag problem reasonably,the power grid company installed a large number of power quality monitoring terminals to realize the voltage sag monitoring and perception,but at the same time it caused the data redundancy problem that the sag events were repeatedly recorded by different monitoring terminals.The similarity calculation method of voltage sags’waveforms based on Hausdorff distance is proposed.The waveform similarity and duration are used as the same-source identification characteristics to construct the voltage sags’same-source identification matrix,and the samesource identification matrix data reduction method based on the multi-dimensional scaling algorithm is proposed to ensure the identification accuracy and improve the calculation efficiency.A same-source identification method of voltage sags based on OPTICS clustering algorithm is proposed,and the same-source identification result is obtained through clustering reachability-plot.Finally,the measurement data of the power grid of a region in the middle of China are selected to verify the feasibility and correctness of the proposed method.