Simplified Artificial Neural Network based Fault Classification and Location for Transmission Line

被引：0
|
作者：
Ahmed, Shihab [1 ]
Islam, Md Rashidul [1 ]
机构：
[1] Rajshahi Univ Engn & Technol, Dept Elect & Elect Engn, Rajshahi, Bangladesh
来源：
2019 5TH INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL ENGINEERING (ICAEE) | 2019年
关键词：
ANN; Transmission line; Fault; 'Training; Classification; Location; POWER DISTRIBUTION-SYSTEMS; SCHEME;
D O I：
10.1109/icaee48663.2019.8975567
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper employs an Artificial Neural Network (ANN) based approach directly to the accumulated fault current in a simple manner to classify and locate the fault occurring in a three-phase transmission network. As a precise tool to solve non-linear relationships, ANN is used to generate the desired output efficiently. The proposed method uses only the instantaneous fault current values to generate the output. The classification is provided for the phase-to-ground faults only. The developed model has been tested for random line faults to check integrity. The designing of the power system model and the development of the neural networks have been carried out in the MATLAB/Simulink environment.
引用
收藏
页码：485 / 489
页数：5
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