Hybrid Classifier for Fault Location in Active Distribution Networks

Sadegh Jamali; Alireza Bahmanyar; Siavash Ranjbar

doi:10.1186/s41601-020-00162-y

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

Hybrid Classifier for Fault Location in Active Distribution Networks

Original Research | 更新时间：2026-09-30

- Hybrid Classifier for Fault Location in Active Distribution Networks
- Hybrid classifier for fault location in activedistribution networks
- 现代电力系统保护与控制（英文） 2020年5卷第2期页码：1-9
- 作者机构：
  
  Centre of Excellence for Power System Automation and Operation, School of Electrical Engineering, Iran University of Science and Technology, Tehran,Iran
- 作者简介：
- 基金信息：
- DOI：10.1186/s41601-020-00162-y
  中图分类号：
- 纸质出版：2020-04-01
- 稿件说明：
移动端阅览
Sadegh Jamali, Alireza Bahmanyar, Siavash Ranjbar. Hybrid Classifier for Fault Location in Active Distribution Networks[J]. 现代电力系统保护与控制（英文）, 2020,5(2):1-9.

Sadegh Jamali, Alireza Bahmanyar, Siavash Ranjbar. Hybrid classifier for fault location in activedistribution networks[J]. Protection and Control of Modern Power Systems, 2020, 5(2): 1-9.
Sadegh Jamali, Alireza Bahmanyar, Siavash Ranjbar. Hybrid Classifier for Fault Location in Active Distribution Networks[J]. 现代电力系统保护与控制（英文）, 2020,5(2):1-9. DOI： 10.1186/s41601-020-00162-y.

Sadegh Jamali, Alireza Bahmanyar, Siavash Ranjbar. Hybrid classifier for fault location in activedistribution networks[J]. Protection and Control of Modern Power Systems, 2020, 5(2): 1-9. DOI： 10.1186/s41601-020-00162-y.

摘要

This paper presents a fast hybrid fault location method for active distribution networks with distributed generation (DG) and microgrids. The method uses the voltage and current data from the measurement points at the main substation

and the connection points of DG and microgrids. The data is used in a single feedforward artificial neural network (ANN) to estimate the distances to fault from all the measuring points. A k-nearest neighbors (KNN) classifier then interprets the ANN outputs and estimates a single fault location. Simulation results validate the accuracy of the fault location method under different fault conditions including fault types

fault points

and fault resistances. The performance is also validated for non-synchronized measurements and measurement errors.

Abstract

fault points

and fault resistances. The performance is also validated for non-synchronized measurements and measurement errors.

关键词

Keywords

references

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

Improved voltage tracking of autonomous microgrid technology using a combined resonant controller with lead-lag compensator adopting negative imaginary theorem

ANN-based model predictive control for hybrid energy storage systems in DC microgrid

Integrated Energy-Water Nexus Optimization in Rural Microgrids: Leveraging Quantum-classical Robust Optimization for Sustainability

Low-Carbon Economic Dispatch in Integrated Energy Systems: A Set-Based Interval Optimization with Decision Support Under Uncertainties

Two-stage distributionally robust optimization-based coordinated scheduling of integrated energy system with electricity-hydrogen hybrid energy storage