| 配电网线损异常数据的辨识与修正方法 |
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| 引用本文： | 夏 懿 1,丁 坤 1 ,马慧莲 1,王 鹏 1 ,张 铄 2. 配电网线损异常数据的辨识与修正方法[J]. 机械与电子, 2023, 41(2): 13-17 |
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| 作者姓名： | 夏 懿 1 丁 坤 1 马慧莲 1 王 鹏 1 张 铄 2 |
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| 作者单位： | 1. 国网甘肃省电力公司临夏供电公司,甘肃 临夏 731100 ;2. 兰州理工大学电气工程与信息工程学院,甘肃 兰州 730050 |
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| 摘 要： | 提出一种针对配电网线损异常数据问题的多级辨识与修正方法。首先，运用基于DBSCAN-新息序列算法做初级辨识，识别出异常数据和可疑数据，进而根据线损数据的时间惯性对可疑数据进行二次辨识以减少误判率；然后，采用改进的LSTM算法对异常数据进行修正；最后，在IEEE-69节点配电系统中应用甘肃临夏某配电台区的实际线损数据验证了所提方法的有效性。
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| 关 键 词： | 线损数据 多级辨识 异常数据 改进LSTM算法 |
Identification and Correction Method for Abnormal Data of Distribution Network Line Loss |
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| XIA Yi1,DING Kun1,MA Huilian1,WANG Peng1,ZHANG Shuo2. Identification and Correction Method for Abnormal Data of Distribution Network Line Loss[J]. Machinery & Electronics, 2023, 41(2): 13-17 |
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| Authors: | XIA Yi1 DING Kun1 MA Huilian1 WANG Peng1 ZHANG Shuo2 |
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| Affiliation: | ( 1.Linxia Power Supply Company , State Grid Gansu Electric Power Company , Linxia 731100 , China ; 2.College of Electrical and Information Engineering , Lanzhou University of Technology , Lanzhou 730050 , China ) |
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| Abstract: | This paper presents a multi-level identification and correction method to address the problem of abnormal line loss data in distribution networks.Firstly , the primary identification based on density-based spatial clustering of applications with noise( DBSCAN ) clustering algorithm and innovation sequence algorithm is used to identify abnormal data and suspicious data.Then , according to the time inertia of the line loss data , the suspicious data is identified again to reduce the misjudgment rate.In addition , the improved long short term memory ( LSTM ) algorithm is used to correct the abnormal data.Finally , the effectiveness of the proposed method is verified by the actual line loss data of a distribution station in Linxia , Gansu Province in the IEEE-69 node distribution system. |
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| Keywords: | line loss data multistage identification abnormal data improved LSTM algorithm |
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