Topology identification method of low voltage distribution network based on segmented current characteristics and random forest algorithm
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(Marketing Service Center, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210019, China)

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TM727;TK018

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    Abstract:

    The topology of low-voltage distribution network is of great significance to realize the application functions such as line loss analysis, fault diagnosis, power theft early warning and demand response. Aiming at the problem of inaccurate and missing topology of low-voltage distribution network, a topology identification method of low- voltage distribution network based on segmented current characteristics and random forest algorithm is proposed. Firstly,based on the current similarity mechanism, the current characteristic index is proposed, and the current time series is segmented for feature extraction. Secondly, the feature vector set is generated according to the segmented current characteristics, and the topology recognition model based on random forest algorithm is established,which can quickly and effectively identify the relationship between users and transformers. Finally, an example is analyzed by using the measured data of the actual distribution network. The results show that the topology recognition accuracy of this method is 98.02%, the sample time is short, and it can quickly and effectively identify the topology relationship of low-voltage distribution network.

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黄艺璇,杨世海,曹晓冬,方凯杰,程含渺.基于分段电流特征和随机森林算法的低压配电网拓扑识别方法[J].电力需求侧管理英文版,2023,25(2):63-69.

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History
  • Received:November 16,2022
  • Revised:January 02,2023
  • Adopted:
  • Online: March 22,2023
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