Automatic Classification Method of Fault Data in Low Voltage Distribution Network Based on SVM
Author:
Affiliation:
1. State Grid Zhejiang Electric Power Research Institute,Hangzhou,China,310014
2. State Grid Zhejiang Electric Power Co., Ltd.,Hangzhou,China,310007
3. Shanghai SHR Automation Co., Ltd.,Shanghai,China,201108
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9723821/9723822/09723900.pdf?arnumber=9723900
Reference11 articles.
1. Incipient Fault Diagnosis in the Distribution Network Based on S-Transform and Polarity of Magnitude Difference
2. Fault identification based on LOF and SVM for smart distribution network;wei;Electric Power Automation Equipment,2016
3. SVM‐based method for high‐impedance faults detection in distribution networks
4. Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis
5. Fault Section Identification in Smart Distribution Systems Using Multi-Source Data Based on Fuzzy Petri Nets
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1. Low-Voltage Distribution Network Topology Identification Method Based on Segmented Current Features and CNN-LSTM Deep Learning;2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE);2023-05-12
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