| 引用本文: | 李克明,江亚群,黄世付,李建奇,杨民生.基于DTW距离和聚类分析的配电台区低压拓扑结构辨识方法[J].电力系统保护与控制,2021,49(14):29-36.[点击复制] |
| LI Keming,JIANG Yaqun,HUANG Shifu,LI Jianqi,YANG Minsheng.Topology identification method of a low-voltage distribution station area based on DTW distance and cluster analysis[J].Power System Protection and Control,2021,49(14):29-36[点击复制] |
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| 摘要: |
| 针对低压配电台区拓扑结构中存在错误的问题，提出了一种基于动态时间弯曲(Dynamic Time Warping, DTW)距离和聚类分析的台区拓扑辨识方法。首先利用电压序列之间的DTW距离度量用户电压曲线之间的相似性，然后基于最小最大距离原则对用户电压曲线进行聚类分析，辨识低压用户所属台区，并对同一台区内的用户进行相别辨识。该方法能够对时间间隔不同、不等长的电压时间序列进行分析，对电压数据缺失或异常数据不敏感，且不需要人为设定阈值，拓扑结构辨识准确性高。算例仿真结果验证了所提方法的正确性与有效性。 |
| 关键词: 低压配电台区 电压序列 DTW距离 聚类分析 拓扑辨识 |
| DOI：DOI: 10.19783/j.cnki.pspc.201142 |
| 投稿时间：2020-09-17修订日期：2020-12-24 |
| 基金项目:湖南省战略性新兴产业科技攻关与重大科技成果转化项目资助(2018GK4025)；湖南省自然科学基金项目资助(2019JJ60012) |
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| Topology identification method of a low-voltage distribution station area based on DTW distance and cluster analysis |
| LI Keming1,JIANG Yaqun1,HUANG Shifu2,LI Jianqi3,YANG Minsheng3 |
| (1. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; 2. Changde GuoLi
Transformer Co., Ltd., Changde 415000, China; 3. Department of Computer and Electrical Engineering,
Hunan University Arts and Science, Changde 415000, China) |
| Abstract: |
| There is a problem of errors in identifying the topology of a low-voltage distribution station area. Thus a topology identification method based on Dynamic Time Warping (DTW) distance and cluster analysis is proposed. First, the DTW distance between voltage sequences is used to measure the similarity between voltage curves. Then, based on the principle of minimum and maximum DTW distance, cluster analysis is carried out on the voltage sequence data of users in a low-voltage distribution station area to identify which station the user belongs to in the area, and then this paper performs phase identification for users in the same station area. The method can measure voltage time series with different time intervals and lengths, is not sensitive to missing voltage or abnormal data, does not need to set a threshold artificially, and has high accuracy in topological structure identification. Finally, a simulation analysis of an example verifies the correctness and effectiveness of the proposed method.
This work is supported by the Strategic Emerging Industry Science and Technology Research and Major Science and Technology Achievement Transformation Project of Hunan Province (No. 2018GK4025) and the Natural Science Foundation of Hunan Province (No. 2019JJ60012). |
| Key words: low-voltage substation voltage sequence DTW distance cluster analysis topology identification |
