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An Early Warning Method of Distribution System Fault Risk Based on Data Mining
Joint Authors
Huang, Zhengyu
Chen, Hui
Mao, Yeying
Feng, Changsen
Yang, Qiming
Ma, Junchang
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-07
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Accurate warning information of potential fault risk in the distribution network is essential to the economic operation as well as the rational allocation of maintenance resources.
In this paper, we propose a fault risk warning method for a distribution system based on an improved RelieF-Softmax algorithm.
Firstly, four categories including 24 fault features of the distribution system are determined through data investigation and preprocessing.
Considering the frequency of distribution system faults, and then their consequences, the risk classification method of the distribution system is presented.
Secondly, the K-maxmin clustering algorithm is introduced to improve the random sampling process, and then an improved RelieF feature extraction method is proposed to determine the optimal feature subset with the strongest correlation and minimum redundancy.
Finally, the loss function of Softmax is improved to cope with the influence of sample imbalance on the prediction accuracy.
The optimal feature subset and Softmax classifier are applied to forewarn the fault risk in the distribution system.
The 191-feeder power distribution system in south China is employed to demonstrate the effectiveness of the proposed method.
American Psychological Association (APA)
Mao, Yeying& Huang, Zhengyu& Feng, Changsen& Chen, Hui& Yang, Qiming& Ma, Junchang. 2020. An Early Warning Method of Distribution System Fault Risk Based on Data Mining. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1201819
Modern Language Association (MLA)
Mao, Yeying…[et al.]. An Early Warning Method of Distribution System Fault Risk Based on Data Mining. Mathematical Problems in Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1201819
American Medical Association (AMA)
Mao, Yeying& Huang, Zhengyu& Feng, Changsen& Chen, Hui& Yang, Qiming& Ma, Junchang. An Early Warning Method of Distribution System Fault Risk Based on Data Mining. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1201819
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201819