A Fast Fault Detection and Identification Approach in Power Distribution Systems

被引：28
作者：
Mohammadi, Fazel [1 ]
Nazri, Gholam-Abbas [2 ]
Saif, Mehrdad [1 ]
机构：
[1] Univ Windsor, Elect & Comp Engn ECE Dept, Windsor, ON N9B 1K3, Canada
[2] Wayne State Univ, Elect & Comp Engn, Detroit, MI 48202 USA
来源：
2019 5TH INTERNATIONAL CONFERENCE ON POWER GENERATION SYSTEMS AND RENEWABLE ENERGY TECHNOLOGIES (PGSRET-2019) | 2019年
关键词：
Fault Detection; Fault Identification; Power Distribution Systems; Modified Multi-Class Support Vector Machines (MMC-SVM);
D O I：
10.1109/pgsret.2019.8882676
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
In this paper, a Modified Multi-Class Support Vector Machines (MMC-SVM) technique is developed to simultaneously detect and classify different types of open-circuit faults in power distribution systems. This technique is capable of detecting and identifying open-circuit faults considering the impact of variations in the voltage of different nodes in power distribution systems. The RMS (Root Mean Square) voltage of the power grid is used as the input signal to diagnose the faults. Simulations are carried out on the IEEE 13-node test system considering temporary open-circuit faults in MATLAB software. The simulation results show the accuracy, effectiveness, and robustness of the proposed method.
引用
收藏
页码：74 / 77
页数：4
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