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基于轨迹特征关键点匹配的电压暂降同源数据精确检测算法
作者:
作者单位:

1.东南大学电气工程学院,江苏省南京市 210096;2.河海大学能源与电气学院,江苏省南京市 211100;3.中国电力科学研究院有限公司(南京),江苏省南京市 210003;4.国网江苏省电力有限公司电力科学研究院,江苏省南京市 211103

摘要:

为弥补现有电压暂降同源检测算法的不足,提高同源检测算法的精度,提出了一种基于轨迹特征关键点匹配的电压暂降同源数据精确检测算法。首先,将电压暂降数据有效值(RMS)波形转换为灰度轨迹图片,基于尺度不变特征转换算法对电压暂降灰度轨迹图片进行分析,提取RMS轨迹的特征关键点。然后,利用特征关键点的梯度方向信息与待检测电压暂降数据的RMS轨迹进行匹配计算,最后,以匹配规则作为电压暂降同源数据判断的标准。所提算法可以很好地弥补现有同源检测算法中的不足,降低了对检测数据集的客观要求,具有更强的工程适用性及实际应用价值。

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基金项目:

国家重点研发计划资助项目(2018YFB1500800)。

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作者简介:


Accurate Detection Algorithm for Homologous Voltage Sag Data Based on Matching of Feature Key Point for Trajectories
Author:
Affiliation:

1.School of Electrical Engineering, Southeast University, Nanjing 210096, China;2.College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China;3.China Electric Power Research Institute (Nanjing), Nanjing 210003, China;4.Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China

Abstract:

To make up for the shortcomings of the homologous voltage sag detection algorithm and improve the accuracy of the algorithm, this paper proposes an accurate detection algorithm of homologous voltage sag data based on the matching of feature key point for trajectories. First, the root mean square (RMS) waveform of the voltage sag data is converted into a gray-scale trajectory image. Then the gray-scale trajectory image of voltage sag is analyzed based on the scale-invariant feature transform (SIFT) algorithm, and the feature key points of the RMS trajectory are extracted. Secondly, the gradient direction information of the feature key points is used to match the RMS trajectories of voltage sag data to be detected. Finally, the matching rule is used as the criterion for the judgment of voltage sag homologous data. The proposed algorithm can make up for the shortcomings of the existing homologous detection algorithms, reduce the requirements for the detection data set, and have stronger engineering applicability and practical application value.

Keywords:

Foundation:
This work is supported by National Key R&D Program of China (No. 2018YFB1500800).
引用本文
[1]沙浩源,郑建勇,梅飞,等.基于轨迹特征关键点匹配的电压暂降同源数据精确检测算法[J/OL].电力系统自动化,http://doi. org/10.7500/AEPS20210830009.
SHA Haoyuan, ZHENG Jianyong, MEI Fei, et al. Accurate Detection Algorithm for Homologous Voltage Sag Data Based on Matching of Feature Key Point for Trajectories[J/OL]. Automation of Electric Power Systems, http://doi. org/10.7500/AEPS20210830009.
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  • 收稿日期:2021-08-30
  • 最后修改日期:2021-12-29
  • 录用日期:2021-10-20
  • 在线发布日期: 2022-01-10
  • 出版日期: