Fault Type & Section Detection Method in a Distribution Network with Distributed Generations Based on the Separated Phase ANN-Model

被引：0

作者：

Kang S.-J. ^{[1
]}

Lee H.-J. ^{[2
]}

Choi M.-C. ^{[2
]}

Kim D.-K. ^{[2
]}

Hyun S.-H. ^{[2
]}

机构：

[1] School of Electrical Electronic Engineering, Korea University

[2] School of Electrical Engineering, University of Ulsan

来源：

Transactions of the Korean Institute of Electrical Engineers | 2023年 / 72卷 / 04期

关键词：

Artificial Neural Network; Deep Learning; Distributed Generation; Distribution Network; Fault Allocation; Fault Type Classification;

D O I：

10.5370/KIEE.2023.72.4.484

中图分类号：

学科分类号：

摘要：

In recent years, the number of distributed generation (DG) in distribution network (DN) has increased. The increasing proportion of DG in DN brings benefits through improved network reliability and reduced transmission power losses. However the connection of DG makes network be more complicated, it changes the unidirectional flow of currents and power to bidirectional flow and thus protection based on over-current relay has limitations of protection coordination. These limitations may occur malfunction or misbehavior of protective devices so it requires new protection methods. This paper proposes a new method using artificial neural network (ANN) can adjust on DN with DG to allocate fault section and to classify fault type as part of solving limitations of protection coordination. This ANN model is separated to each phase and use magnitude and phasor of voltages and currents extracted from each generation sides. The new proposed method is applied to unbalanced distribution network model and verified to be useful in DN through computer simulations. Copyright © The Korean Institute of Electrical Engineers.

引用

页码：484 / 495

页数：11

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